Contrasting cognitive control in the Simon and spatial Stroop tasks regarding their interference with the control of standing balance

Contrasting cognitive control in the Simon and spatial Stroop tasks regarding their interference with the control of standing balance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Contrasting cognitive control in the Simon and spatial Stroop tasks regarding their interference with the control of standing balance Leif Johannsen, Anton Koger, Elisa Ruth Straub, Denise Nadine Stephan, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8884917/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The scientific understanding of any interaction between cognition and balance control is advanced by methods that capture event-related effects of cognitive processes on balance with high temporal resolution and precision. We developed such an approach to examine how cognitive conflict interferes with the control of body balance during upright standing. Participants stood on a force plate while performing two cognitive conflict paradigms: a Simon task, which induces spatial stimulus–response conflict during response selection, and a Spatial Stroop task, which elicits an additional stimulus–stimulus conflict during stimulus encoding. By aligning force plate time series data to the onset events of target and response across all trials, we assessed the temporal dynamics of spatial congruency effects on force moment variability as a marker of balance control activity. Across both experimental cognitive tasks, incongruent trials produced strong congruency effects in cognitive task performance and systematically caused transient reductions in force moment variability along the mediolateral axis in balance control. These observations suggest that the recruitment of cognitive processes for conflict resolution temporarily inhibits, suppresses, or postpones balance adjustments. Importantly, regarding the impact of cognitive interference on body balance, we confirm our previous observations using improved methods and demonstrate that reduction in balance control activity during resolution of cognitive conflict generalizes to a task with multiple conflict loci (Spatial Stroop task). However, this extended range of conflict does not result in correspondingly stronger interference effects in balance control. These findings suggest that conflict-related demands in cognitive control robustly permeate into balance control. From a theoretical perspective, the results align with predictive models of postural regulation and intermittent, event-driven accounts of balance control. Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology balance control cognitive conflict resolution cognitive-motor interference Simon task Spatial Stroop task Figures Figure 1 Figure 2 Figure 3 Figure 4 Public significance This study shows evidence that tasks that create cognitive conflicts, such as a Simon task or a Spatial Stroop task, interfere with our ability to maintain balance. By measuring posture on a fine-grained, moment-to-moment basis, we found that resolving cognitive conflict seems to temporarily reduce the likelihood to perform corrective balance adjustments. Our findings highlight that balance control and cognitive control are closely linked functionally, suggesting that everyday situations requiring cognitive processing of ambiguous information and quick decision-making in the light of distracting information may momentarily compromise balance stability. Introduction Maintaining body balance ("balance control") while quietly standing upright appears motionless but represents a continuously active and dynamic activity. This results from the interplay between gravitational forces on the body and counteracting muscle-generated forces. Stability in standing balance is maintained if the vertical projection of the body's Centre-of-Mass (CoM) remains within the boundaries of the base of support. The sensorimotor control loop that ensures successful balance control fundamentally requires combining information from various sensory systems that monitor the body's oscillatory movements relative to the surrounding environment, along with choosing and implementing adequate balance adjustments at the motor level [1-4]. Balance control during standing is frequently evaluated using posturographic methods that employ force plates to measure body sway through ground-reaction force dynamics [5]. According to Newton's third law of motion, the ground-reaction force represents the total of forces and moments generated by the neuromuscular system of an individual regulating the angular velocity and acceleration of the body's Centre-of-Mass as it is affected by gravitational pull, other external and also internal forces acting upon the body [6]. The context-dependent regulation of body oscillation can be examined comprehensively through diverse measures of body motion over a specified time period in addition to measures that capture the complex, longer-term dynamics of body sway [7]. Cognitive control comprises those executive processes that adapt goal-directed behaviour in dynamic environments that become challenging by changing task demands [8]. The capability to inhibit inappropriate responses and to resolve conflict between competing stimuli is a central aspect. The Simon effect [9] refers to the interference when there is a stimulus-response (S-R) conflict, where responses are faster when the stimulus location corresponds with the response location than when it does not, even though stimulus location is not part of the instructed task. Presumably, the Simon effect arises because the irrelevant spatial location of the stimulus automatically activates a spatially congruent response tendency [10]. This creates competition between the correct task-relevant response and the automatically activated spatial response. The conflict occurs at the response selection stage when competing motor programmes must be resolved. Similarly, the Spatial Stroop effect [11] also refers to interference when two attributes of the same stimulus conflict with each other (e.g., left vs. right pointing arrows presented at a right or left location on the screen), where the conflict mechanism involves conflict between the relevant spatial dimension (direction) and the irrelevant spatial dimension (target location). The Spatial Stroop task requires processing of a spatial target while ignoring spatial position, creating stimulus-stimulus (S-S) conflict in addition to a S-R conflict as in the Simon task. Therefore, the Spatial Stroop task interference is thought to occur during stimulus processing and response selection before response onset [12]. Two lines of research have been followed to investigate how control of balance and of cognition is mutually linked. First, several recent studies explored whether standing compared to sitting results in interference on the cognitive task using motor requirements as independent variable. Here findings are mixed, while some studies reported some impact of a standing posture (relative to sitting) on performance in diverse cognitive tasks [13-15], such as the Stroop or the Navon tasks, other studies could not replicate these findings [16-18]. Second, another line of research assessed the impact of a cognitive task on balance control while standing. Consequently, in this second line of research, balance performance becomes the dependent variable, which necessitates an appropriate and sensitive quantification of balance performance. The impact of a cognitive task on balance control while standing can only be determined by assessing how variations in cognitive demands influence balance performance. Cognitive and sensorimotor processes are known to interfere with one another [19-21]. This is illustrated by balance control as it requires anticipatory planning, multisensory integration to estimate postural state [22], and the selection of corrective responses that become more reliant on higher-order cognition when aging or pathology slows processing [23-25]. Earlier studies examining how cognition interacts with balance control typically used dual-task paradigms assessing balance with a concurrent cognitive task. When balance remained unaffected but cognitive performance declined, researchers inferred that balance control relies on domain-specific cognitive processes [26, 27]. Typically, balance measures are aggregated across a longer period of time and thus across a number of individual trials with the cognitive task. Only a few studies have tested cognition–balance interference using conflict tasks like the Stroop task. Melzer et al. [28] showed that a modified Stroop task altered sway in older adults depending on stance width, with reduced sway in narrow stance likely reflecting increased postural stiffness. Similarly, Patterson et al. [29] reported that older adults performing a spatial Stroop-like task exhibited longer reaction times and less accurate responses in combination with reduced body sway, again suggesting a strategy shift toward postural stiffening. Barra et al. [30] used auditory verbal and spatial Stroop tasks of varying difficulty together with different stance conditions and observed reduced body sway under dual-tasking, which they interpreted as increased automatization of balance control or postural stiffening. While these studies following a traditional approach demonstrated that cognitive control and balance control interfere with each other, the approach used cannot pinpoint how specific cognitive processes (such as conflict resolution during stimulus or response processing) affect balance with the precise timing needed for detailed process analysis. Consequently, these studies typically led to broad generalizations about shared cognitive and motor resources rather than specific mechanistic insights. The research examining how attentional control tasks affect standing balance has not produced clear findings regarding the timing of cognitive processes within individual trials. This limitation likely stems from how balance performance is typically measured by averaging time series data over extended periods (tens of seconds to minutes). In contrast, cognitive dual-task research has established that cognitive resource sharing operates at the micro-level (i.e., at the millisecond scale) of specific processing stages during task execution, including response selection processes [see 31, 32, for reviews]. Therefore, we conjecture that investigating the interaction between cognitive control and balance control would benefit from research methods that enable event-related analysis of how cognitive processes influence balance control with high temporal precision. Johannsen et al. [33] developed an event-related methodology to investigate how cognitive control during cognitive conflict tasks influences balance control during normal upright standing. For this purpose, we utilized the Simon task paradigm as our main focus, which involves discrete stimulus-response (S-R) processing episodes only, in contrast to a Spatial Stroop task, which represents a combination of S-S and S-R conflicts. Participants stood on a force plate while performing a Simon task. Instead of investigating the effect of cognitive control on body sway during upright standing estimated over an extended stance period, we applied an event-related paradigm, in which the immediate effect of a single cognitive operation in the Simon task on balance control is determined from force moments on a sub-second time scale. We aggregated force-plate data in time bins of 150 ms around visual target onset and onset of motor responses (presses of hand-held keys) for examining process-specific interactions between cognitive processes and balance control during standing. First, we investigated balance control while performing the Simon task in a target-aligned way, so that differences would reflect predominantly stimulus-based processing conflicts. Second, we assessed balance control in a response-aligned way to isolate the effect of cognitive processing preceding overt response production in the Simon task [for similar analysis on EEG distinguishing stimulus- and response-lateralized readiness potential see 34]. We expected that if cognitive control processes interfered with balance control, we would observe correlates of cognitive conflict in the Simon task in the balance control domain. Our study showed that resolving response conflict in the Simon task not only produced the expected congruency effect in cognitive performance but also reduced mediolateral sway variability in the temporal period of 150 ms before response onset. This indicates that cognitive conflict resolution processes can momentarily influence balance control in a direction-specific manner. Current study In the present study, we aimed to extend our understanding of interference between balance control and cognitive control by comparing the cognitive conflicts induced by the Simon and the Spatial Stroop tasks. To specifically focus on cognitive conflict processing, in Johannsen et al. [33], we initially decided against using the Stroop task, which Kornblum et al.'s [35] dimensional overlap model indicates involves both perceptual conflict and potentially response conflict as well. We instead employed the Simon task as our experimental framework, a paradigm widely recognized for examining cognitive conflict specifically during response selection processes [36, 37]. The taxonomy of Kornblum et al. [35] classified cognitive tasks with respect to the question whether dimensions of stimuli and responses overlap. Overlap within a stimulus set would lead to the potential of stimulus-stimulus conflict, while overlap between stimulus and response sets could lead to stimulus-response conflict. When stimulus and response dimensions overlap, task-irrelevant stimulus information can involuntarily activate a response. However, if the activated response is incorrect, this response tendency based on irrelevant information would require some degree of cognitive control intervention to prevent it from corrupting actual performance. Any differences between the Simon task and the Spatial Stroop task congruency effects lie in the fundamental nature of the conflict being processed according to Kornblum’s dimensional overlap model [38]. In previous studies, two types of conflict were addressed: S-S and S-R conflict [e.g. see review of 39]. In the current study, therefore, we compared the Simon task with the Spatial Stroop task with the assumption that the Spatial Stroop task would generate even stronger and earlier conflict. With respect to balance control, the interference effect of the Simon task may emerge later during response selection and preparation, while effects of the Spatial Stroop task may manifest themselves earlier during stimulus encoding and persist for a longer duration during response selection. Methods Participants Ninety healthy young adults (M=21.4 years, SD=2.7; female=67, male=23; right-handed=81) were recruited for the current study in two laboratories with basically identical setup in Aachen (n=72) and in Freiburg (n=18). Participants were naïve regarding the hypotheses of the experiment, reported normal or corrected-to-normal vision and had neither neurological, musculoskeletal, psychiatric, nor any other relevant medical diagnoses nor did they show any current balance impairments. Based on Johannsen et al. [33], where a t-test for dependent measures found in a within-subject effect size of congruency in the Simon task in the mediolateral body sway direction of dz=0.41, a sample size of 80 participants was calculated for an actual power of 0.95 [40]. Ten additional participants were recruited to follow a conservative approach. All participants were informed about the study protocol and gave signed written informed consent. Ethical approval was obtained prior to the study from the local faculty’s ethical committee at the RWTH Aachen University (2022_013_FB7_RWTH Aachen) and the study protocol was conducted in accordance with the ethical research standards of the amended declaration of Helsinki. Equipment And Cognitive tasks The experiment was conducted in a dimly lit, quiet laboratory. A 31.5 inch LCD monitor with a refresh rate of 144 Hz and a resolution of 3840×2160 pixels was used for the presentations of visual targets in both cognitive tasks described below. The monitor was placed in front of the participants at about 85 cm distance and a height of 130 cm. Targets were the white-on-black letters T and X (both 1 cm width and 1.5 cm heigh) and left- or right-pointing arrows (both 1.8 cm width and 0.8 cm height) that were presented 16 cm left or right from a fixation cross (1.5 cm width and height, presented horizontally and vertically centralized). The input device for the manual responses was a game controller (Rii PC controller USB gamepad; dimensions: 16 x 11.5 x 7 cm; weight: 161 g). Participants were instructed to press left and right keys on the controller using their left and right index fingers. Participants held the game controller with both hands in front of their upper body and they were told to hold the controller relaxed and rather close to their trunk with the elbows close to both sides of the body and the arms slightly flexed upwards at the elbow joints so that the hands were level with the height of their navel. They did not receive explicit instruction to stand as quietly as possible but were instructed to prevent any voluntary balance disturbance by moving body limbs or shifting weight only. Body sway was recorded using a multi-component force plate type Kistler 9260AA with a temporal resolution of 1000 Hz. The force plate uses piezoelectric 3-component force sensors to register the forces and moments exerted on the plate in the three spatial directions. Sway recordings were performed on a second computer using the BioWare software (version 5.3.0.7; Kistler Group, 2012). The computer running the cognitive tasks communicated via a parallel port interface with the force plate computer, where additional channels were registered as analog input devices sampled also at 1 kHz and synchronized with the force plate data acquisition. These channels recorded uniquely encoded trigger signals sent at several trial events (e.g. fixation onset, target onset, and response onset) in each trial for later processing of behavioural data and force plate time series data [41]. While standing, participants performed the two cognitive tasks (Fig. 1) within a single session (duration 90 min to 2 h). The order of both tasks was counter-balanced across participants to control for any systematic order effects. At the beginning of each part of the session, participants performed at least ten practice trials to familiarize themselves to the experimental procedure of each task. In each task, participant performed ten blocks of roughly 280 s duration of continuous standing. They were offered breaks between the individual blocks. Each of the ten blocks contained 80 trials so that 800 trials were presented in total for each task. --- Insert Figure 1 about here --- The cognitive tasks were run on a computer using PsychoPy [version 2023.2.3; 42]. A Simon task was modelled after the version used in Johannsen et al. [33]. It comprised a visual 2-alternative forced choice task, in which the letters ‘T’ and ‘X’ were presented either on the left or the right of a central fixation. Fixation and target were presented in white on a black background. The letter ‘T’ required participants to respond with a left button press, and the letter ‘X’ asked for a right button response while ignoring the presentation location. A match between the required manual response and the side of the target resulted in a congruent trial, while a mismatch between instructed target response and target location defined an incongruent trial. A Spatial Stroop task [modelled after 43] was designed in analogy to the Simon task with arrows pointing to the left or right that were presented on the left or right side of the fixation. Participants were required to respond to the direction in which an arrow was pointing (left button press when an arrow pointed to the left and right button press when the arrow pointed to the right) while ignoring the presentation location. Again, a match between the required manual response and the side of the target resulted in a congruent trial, while a mismatch between instructed target response and target location defined an incongruent trial. In both cognitive tasks, the sequence of congruent and incongruent trials within a block was random. Following a fixation cross of 200 ms duration, a target was presented horizontally to the left or the right of the fixation cross. The target and fixation cross remained visible until a manual response occurred, or a period of 1.5 s had passed without a response. The reaction time (RT) period was followed by 350 ms of feedback in case of an incorrect response (a correct response resulted in a blank screen) and each trial ended with a 200 ms blank screen inter-trial interval. Hence, the total response-target interval was 750 ms. During data analysis, we considered only trials with RTs shorter than 1250 ms, that is, trials with overall durations shorter than 2 s. Each intertrial interval was further extended by a blank screen before the onset of the next fixation with randomly jittered durations in the range from 500 ms to 2.5 s. This jitter period ensured that participants were unable to anticipate the exact onset of the next trial based on any rhythmic structure in the trial procedure. In addition, the fixation onset jittering decoupled slow oscillations in body sway from trial timing when aggregating over any individual trials. Post ‑Processing Of Force Plate Data And Parameter Extraction Time series data post-processing and parameter extraction were performed in MATLAB 2023b (The Mathworks, Natick, MA) as well as RStudio (version 2025.05.0+496; R version 4.4.2) using custom-prepared algorithms. Forces and moments of the force plate were used to characterize the control of body sway. A dual-pass moving average with sliding window width of 19 ms was applied for general smoothing of all time series data to remove any high frequency signals, artefacts or by-products, which are not directly associated with supraspinal control of sway, such as electromagnetic noise or peripheral and spinal reactions (muscle twitches or spinal reflexes). The experimental blocks for each cognitive task were segmented into individual trials using the trial event signals that indicated the onset of fixation. Single trials were excluded from post-processing if the entire duration of a trial surpassed 2 s, for example responses were not recorded in the 1250 ms interval after target onset. These trials were labelled as “unresponsive” and were not considered for further processing. Additionally, trials with incorrect responses, correct trials following an incorrect response, and the very first trials of each block were excluded. In the Simon task, a total proportion of 7.5% of all trials were excluded from data analysis, of which 3.6% were excluded as response errors, 3.4% as correct responses following an error, and 0.5% as correct responses with RTs longer than 1250 ms. In the Spatial Stroop task, a total of 6.1% of all trials were excluded from data analysis, of which 3.0% were excluded as response errors, 2.9% as correct responses following an error, and 0.2% as correct responses with RTs longer than 1250 ms. Like in Johannsen et al. [33], two major branches of data processing were pursued by aligning all the time series data to the time points of the onset of the target (target-aligned) as well as the onset of the manual response (response-aligned). Around the anteroposterior (AP) and mediolateral (ML) axis for a specified time bin, the current state of balance was analysed as the standard deviation (SD) of the ground reaction force moment (units in Nmm). Variability of the force moment within a time bin expresses the amount of activity applied by the neuromuscular system for the control of standing balance. Greater variability would indicate balance adjustments being more likely to demonstrate their effect within this short period. We chose a temporal bin width of 75 ms (amounts to 75 datapoint at 1 kHz sample rate) duration for improved time course resolution compared to Johannsen et al. [33]. An increased number of temporal bins compared to our precursor study allowed us to describe the moment variability before and after each trial event in more detail. For target-aligned trial time series, therefore, six temporal bins were extracted from 150 ms before until 300 ms after target onset. Six temporal bins were also extracted for the response-aligned trial time series from 300 ms before to 150 ms after response onset. Design Performance in the Simon task and the Spatial Stroop task, in terms of RT and error proportions (EP), needed to be assessed to validate that a robust effect of cognitive conflict was induced by the respective target stimuli. For both cognitive tasks, congruency of the current trial and congruency of the previous trial were used as the independent variables. We considered previous trial congruence as additional independent variable, because ample of research [see also our own previous study, 33, e.g. 44] has shown that the impact of congruency in the current trial is larger after a previous congruent rather than incongruent trial.[1] Potential factors such as laterality of the target stimulus presentation and laterality of the manual reactions were not considered of interest due to lack of any a priori hypotheses because any specific effect of laterality would be cancelled out by calculating averages across sides. The dependent variables were RT and EP. RTs were directly measured by the presentation software and validated by signals of stimulus and response triggers in the force plate data. The dependent variables were based on response timing information acquired through the target stimulus presentation software directly as well as by the trial event trigger signals sent to the data acquisition board of the force plate setup. With respect to replicating our previous study [33], we restricted our analysis of the force-plate data to trials that followed a congruent previous trial because we expected the strongest effects of cognitive conflict in these trials [see also 45 for discussion]. As dependent variables representing balance control in both the AP and ML directions of sway, we calculated the standard deviation of the force moment time series within the respective time bins of each single trial of a participant. [1] While there are several accounts for this so-called ‘congruency sequence effect’ (e.g. Botvinick et al., 2001; Dignath et al., 2020; Egner, 2007; Hommel et al., 2004), for the purpose of controlling for the impact of the current congruency manipulation on balance control, it is sufficient for us to consider congruency in the previous trial only. Results All statistical computations were performed in R Studio (2025.09.1 Build 401; R version 4.4.2). For the force moment parameters, statistical analyses were performed for the target-aligned and the response-aligned time series data. The variability of the moments acting around the anteroposterior and mediolateral axes was analysed in terms of its standard deviation within each 75 ms time bin. Force moment variability was natural log-transformed before statistical analysis to approach an interval scaling of the dependent variable. Statistically significant effects and interactions were evaluated at an alpha level of p < 0.05 in combination with a Bayes Factor [ 46 ] greater than 1.0. Analysis of Manual Reactions Comparison Between Both Cognitive Tasks To look at the effects of conflict in the two cognitive tasks, RT and EP were analysed with congruency as within-subject factor. Previous trial congruency was added as a second within-subject factor to assess specific sequential conflict adaptation effects, and cognitive task (Simon vs. Spatial Stroop) as a third within-subject factor of the repeated-measures analyses of variance (ANOVAs). Table 1 and Table 2 provide the descriptive statistics of the reaction times and error proportions for both cognitive tasks combined and individually and Table 3 summarizes the inferential test statistics of ANOVAs for the manual reaction latencies and the error proportions. Table 1 Descriptive statistics of the reaction times for both cognitive tasks as a function of congruency and previous trial congruency. M: mean, S: standard deviation. Cognitive conflict task Both tasks included Simon task Spatial Stroop task Previous trial congruency Previous trial congruency Previous trial congruency Current trial congruency Congruent Incongruent Congruent Incongruent Congruent Incongruent M SD M SD M SD M SD M SD M SD Incongruent 527 59 495 60 529 63 498 64 525 55 492 56 Congruent 458 57 502 61 468 60 508 70 448 52 495 51 Congruency effect 69 27 -7 26 61 22 -10 26 77 28 -3 26 Table 2 Descriptive statistics of the error proportions for both cognitive tasks as a function of congruency and previous trial congruency. M: mean, S: standard deviation. Cognitive conflict task Both tasks included Simon task Spatial Stroop task Previous trial congruency Previous trial congruency Previous trial congruency Current trial congruency Congruent Incongruent Congruent Incongruent Congruent Incongruent M SD M SD M SD M SD M SD M SD Incongruent 7.1 4.9 2.3 2.3 7.1 5.1 2.4 2.4 7.1 4.7 2.2 2.1 Congruent 0.9 1.2 2.9 3.1 1.2 1.4 3.7 3.6 0.6 1.0 2.1 2.2 Congruency effect 6.3 4.6 -0.6 2.7 5.9 4.7 -1.3 3.0 6.5 4.5 0.1 2.1 Table 3 Test statistics of ANOVAs for manual reaction times and error proportions with task condition as within-subject factor (rows 1 and 2) and for each individual cognitive task (Simon task: rows 3 and 4; Spatial Stroop task: rows 5 and 6). Significant effects or interactions are indicated in bold. F, p, partial eta^2, BF Main effect Main effect Main effect Interaction Interaction Interaction Interaction Task condition Current trial congruency Previous trial Congruency Task condition by current trial congruency Task condition by previous trial congruency Current trial congruency by previous trial congruency Task condition by current trial congruency by previous trial congruency Both tasks included Reaction latencies F(1, 89)= 4.58, p=.04, ƞ p 2 =.05 F(1, 89) = 286.98, p<.001, ƞ p 2 =.76 F(1, 89) = 60.79, p<.001, ƞ p 2 =.41 F(1, 89) = 20.65, p<.001, ƞ p 2 =.19 F(1, 89)= 1.98, p=.16, ƞ p 2 =.02 F(1, 89) = 790.18, p<.001, ƞ p 2 =.90 F(1, 89) = 10.95, p=.001, ƞ p 2 =.11 Error proportion F(1, 89) = 9.84, p=.002, ƞ p 2 =.10 F(1, 89) = 128.42, p<.001, ƞ p 2 =.59 F(1, 89) = 103.71, p<.001, ƞ p 2 =.54 F(1, 89) = 12.92, p<.001, ƞ p 2 =.13 F(1, 89) = 7.50, p=.007, ƞ p 2 =.08 F(1, 89) = 197.46, p<.001, ƞ p 2 =.69 F(1, 89) = 4.34, p=.04, ƞ p 2 =.05 Simon task Reaction latencies F(1, 89) = 193.28, p<.001, ƞ p 2 =.68 F(1, 89) = 17.62, p<.001, ƞ p 2 =.17 F(1, 89) = 414.90, p<.001, ƞ p 2 =.82 Error proportion F(1, 89) = 59.05, p<.001, ƞ p 2 =.40 F(1, 89) = 37.61, p<.001, ƞ p 2 =.30 F(1, 89) = 166.97, p<.001, ƞ p 2 =.65 Spatial Stroop task Reaction latencies F(1, 89) = 214.39, p<.001, ƞ p 2 =.71 F(1, 89) = 57.00, p<.001, ƞ p 2 =.39 F(1, 89) = 866.01, p<.001, ƞ p 2 =.91 Error proportion F(1, 89) = 148.79, p<.001, ƞ p 2 =.63 F(1, 89) = 95.57, p<.001, ƞ p 2 =.52 F(1, 89) = 167.13, p<.001, ƞ p 2 =.65 --- Insert Tables 1 , 2 , and 3 about here --- An ANOVA on RT including both cognitive tasks (Simon task and Spatial Stroop task) indicated that RT were shorter in the Spatial Stroop task (M = 490 ms, SD = 60) than the Simon task (M = 501 ms, SD = 68; F(1, 89) = 4.58, MSE = 4503.04, p=.04, ƞ p 2 =.05, BF = 1.28 ± 1.97%). On congruent trials, RTs (M = 480 ms, SD = 63) were shorter than incongruent RTs (M = 511 ms, SD = 61; F(1, 89) = 286.98, MSE = 606.84, p<.001, ƞ p 2 =.76, BF = 8.30 × 10 25 ±1.18%). Further, a main effect of previous trial congruency was observed (F(1, 89) = 60.79, MSE = 108.35, p<.001, ƞ p 2 =.41, BF = 526898546 ± 1.01%) with faster responses following a previously congruent trial (M = 492 ms, SD = 67) than an incongruent trial (M = 498, SD = 60), which, however, was qualified by an interaction between previous trial congruency and current trial congruency (F(1, 89) = 790.18, MSE = 324.80, p<.001, ƞ p 2 =.90, BF = 4.74 × 10 74 ±2.22%). When the previous trial was congruent, then RTs in congruent trials were shorter than in incongruent trials, resulting in a congruency effect of 69 ms, t(89) = 30.23, p < 0.001, dz = 3.19, but when the previous trial was incongruent, then RTs in congruent trials were longer relative to RT on incongruent trials, resulting in a “reversed” congruency effect of 7 ms (t(89) = 2.93, p = 0.004, dz = 0.31). We also observed an interaction between cognitive task and congruency (F(1, 89) = 20.65, MSE = 260.74, p<.001, ƞ p 2 =.19), which indicated a greater overall congruency effect in the Spatial Stroop task (M = 36 ms; t(89) = 14.64, p < 0.001, dz = 1.54) compared to the Simon task (M = 26 ms; t(89) = 13.90, p < 0.001, dz = 1.47). However, a Bayesian model comparison provided no evidence for a condition by congruency interaction (BF = 0.69 ± 7.43%), indicating that the data were slightly more likely under the model without the interaction. Finally, a three-way interaction between cognitive task, congruency and previous-trial congruency indicated, that the congruency sequence effect described above differed between the two cognitive tasks (F(1, 89) = 10.95, MSE = 112.54, p=.001, ƞ p 2 =.11, BF = 8.74 × 10 49 ±3.82%). Both the Simon task and the Spatial Stroop demonstrated individual main effects of congruency and previous congruency as well as an interaction between both factors (statistic effects for each task are reported in the supplementary materials and Table 4 ). In the Simon task, when the previous trial was congruent, then a Simon effect of 61 ms was observed (t(89) = 25.97, p < 0.001, dz = 2.74) but when the previous trial was incongruent, then a “reversed” Simon effect of 10 ms (incongruent trials resulted in shorter RTs than congruent trials) occurred (t(89) = 3.53, p = 0.0007, dz = 0.37). Figure 2 a shows the reaction times for the Simon task. In the Spatial Stroop task, when the previous trial was congruent, then a Spatial Stroop effect of 77 ms was observed (t(89) = 25.78, p < 0.001, dz = 2.72) but, in contrast to the Simon task, when the previous trial was incongruent, then no difference was observed between congruent and incongruent trials (M=-3 ms; t(89) = 1.40, p = 0.16, dz = 0.15). Figure 3 a shows the reaction times for the Spatial Stroop task. Table 4 Descriptive statistics of the anteroposterior force moment variability for both cognitive tasks as a function of congruency and time bin. M: mean, S: standard deviation. target-aligned Cognitive conflict task Time bin -150 to -75 ms -75 ms to target onset target onset to 75 ms 75 to 150 ms 150 to 225 ms 225 to 300 ms Congruency M SD M SD M SD M SD M SD M SD Both tasks Included Incongruent -2.33 0.52 -2.32 0.52 -2.33 0.53 -2.33 0.52 -2.35 0.52 -2.39 0.51 Congruent -2.33 0.51 -2.32 0.51 -2.32 0.52 -2.33 0.52 -2.35 0.52 -2.39 0.51 Congruency effect 0.006 0.11 0.004 0.11 -0.004 0.11 0.002 0.10 0.002 0.10 0.005 0.10 Simon task Incongruent -2.34 0.52 -2.32 0.51 -2.33 0.52 -2.34 0.52 -2.36 0.53 -2.39 0.51 Congruent -2.34 0.51 -2.32 0.50 -2.33 0.51 -2.33 0.51 -2.36 0.51 -2.40 0.52 Congruency effect -0.008 0.11 -0.003 0.11 -0.006 0.10 -0.007 0.10 -0.004 0.10 0.008 0.10 Spatial Stroop task Incongruent -2.31 0.53 -2.31 0.53 -2.32 0.53 -2.32 0.52 -2.34 0.52 -2.39 0.50 Congruent -2.33 0.51 -2.32 0.53 -2.32 0.53 -2.33 0.53 -2.35 0.53 -2.39 0.51 Congruency effect 0.021 0.11 0.012 0.11 -0.003 0.11 0.012 0.10 0.007 0.10 0.002 0.10 response-aligned Cognitive conflict task Time bin -300 to -225 ms -225 to -150 ms -150 to -75 ms -75 ms to response onset response onset to 75 ms 75 to 150 ms Congruency M SD M SD M SD M SD M SD M SD Both tasks Included Incongruent -2.38 0.51 -2.38 0.50 -2.40 0.49 -2.40 0.49 -2.37 0.48 -2.37 0.49 Congruent -2.37 0.51 -2.37 0.51 -2.39 0.51 -2.38 0.50 -2.35 0.49 -2.36 0.49 Congruency effect -0.018 0.11 -0.012 0.10 -0.005 0.10 -0.018 0.10 -0.017 0.09 -0.007 0.11 Simon task Incongruent -2.39 0.51 -2.38 0.50 -2.41 0.49 -2.41 0.49 -2.38 0.48 -2.38 0.50 Congruent -2.37 0.51 -2.37 0.51 -2.40 0.51 -2.39 0.50 -2.36 0.49 -2.36 0.49 Congruency effect -0.019 0.11 -0.015 0.11 -0.003 0.10 -0.016 0.10 -0.025 0.09 -0.020 0.12 Spatial Stroop task Incongruent -2.38 0.51 -2.38 0.51 -2.39 0.50 -2.40 0.49 -2.35 0.48 -2.35 0.49 Congruent -2.36 0.51 -2.37 0.52 -2.38 0.51 -2.38 0.50 -2.35 0.49 -2.36 0.49 Congruency effect -0.018 0.11 -0.009 0.10 -0.008 0.10 -0.020 0.10 -0.009 0.09 0.008 0.10 The error proportions demonstrated lower error proportions in the Spatial Stroop task (M = 3.0%, SD = 3.8) compared to the Simon task (M = 3.6%, SD = 4.1; F(1, 89) = 9.84, MSE = 7.05, p=.002, ƞ p 2 =.10, BF = 12.16 ± 0.97%). Additionally, we observed an effect of congruency (F(1, 89) = 128.42, MSE = 11.27, p<.001, ƞ p 2 =.59, BF = 1.07 × 10 16 ±1%) with more errors in incongruent trials (M = 4.7%, SD = 4.5) compared to congruent trials (M = 1.9%, SD = 2.6) and an effect of previous trial congruency (F(1, 89) = 103.71, MSE = 3.31, p<.001, ƞ p 2 =.54, BF = 2.50 × 10 13 ±0.99%) with higher error proportions (M = 4.0%, SD = 4.8) when the previous trial was congruent in contrast to when it was incongruent (M = 2.6%, SD = 2.7). An interaction between previous trial congruency and congruency was also found (F(1, 89) = 197.46, MSE = 10.73, p<.001, ƞ p 2 =.69, BF = 5.55 × 10 36 ±6.13%). When the previous trial was congruent, then error proportions in incongruent trials were higher than in congruent trials, resulting in a congruency effect of 6.3% (t(89) = 14.1, p < 0.001, dz = 1.49), but when the previous trial was incongruent, then error proportions in incongruent trials were even lower than in congruent trials, resulting in a “reversed” congruency effect of 0.6% (t(89) = 2.74, p = 0.007, dz = 0.29), mirroring the RT data. An interaction between cognitive task and congruency (F(1, 89) = 12.92, MSE = 3.72, p<.001, ƞ p 2 =.13, BF = 3.20 ± 4.37%) indicated that in the Spatial Stroop task the congruency effect was greater (M = 3.4%; t(89) = 12.20, p < 0.001, dz = 1.29) compared to the Simon task (M = 2.1%; t(89) = 7.68, p < 0.001, dz = 0.81). The interaction between cognitive task and previous trial congruency was also significant but Bayes Factor analysis discounted the influence of the interaction (F(1, 89) = 7.50, MSE = 2.15, p = .007, ƞ p 2 = .08, BF = 0.89 ± 3.52%). Again, like in the RT data, a three-way interaction between cognitive task, congruency and previous-trial congruency was also found. It indicated differences in the congruency sequence effect between the two cognitive tasks (F(1, 89) = 4.34, MSE = 2.01, p=.04, ƞ p 2 =.05, BF = 3.11 × 10 60 ±8.18%). In the Simon task, when the previous trial was congruent, then error proportions in congruent trials were lower than in incongruent trials, resulting in a Simon effect of 5.9% (t(89) = 12.12, p < 0.001, dz = 1.28) but when the previous trial was incongruent, then, consistent with the RT data, error proportions on congruent trials were even higher than on incongruent trials, resulting in a “reversed” Simon effect of 1.3% (t(89) = 4.23, p < 0.001, dz = 0.45). Figure 2 b shows the error proportions for the Simon task. In the Spatial Stroop task, when the previous trial was congruent, then error proportions in congruent trials were lower than in incongruent trials, resulting in a Spatial Stroop effect of 6.5% (t(89) = 13.81, p < 0.001, dz = 1.46), but when the previous trial was incongruent, like for the RTs, then error proportions did not differ between congruent and incongruent trials (M = 0.1%; t(89) = 0.65, p = 0.52, dz = 0.07). Figure 3 b shows the error proportions for the Spatial Stroop task. --- Insert Figs. 2 and 3 about here --- Analysis Of Force Moment Variability The following description of statistical results concerns trials only, where the previous trial was congruent, because for these trials the effects of congruency are larger compared to for trials after incongruent trials. We analysed force moment variability separately in the AP and ML directions for both target-aligned and response-aligned times series. As will be reported below the effect of cognitive task was never significant and also did not interact with congruency and time bin, therefore, Individual analyses of balance performance for each of the two cognitive tasks can be found in the supplementary materials. Target-Aligned And Response-Aligned Time Series Analyses Of Congruency Effects In Both Cognitive Tasks Tables 4 and 5 list the descriptive statistics of the target-aligned and response-aligned force moment variability for both cognitive tasks as well as the Simon task and the Spatial Stroop task and each congruency condition and time bin. Table 6 contains the test statistics of the ANOVAs of the congruency effect for the target-aligned and response-aligned moment variability for both cognitive tasks combined and the individual tasks. The main effects of the two cognitive tasks, congruency and the progression across the time bins were assessed as within-subject factors of a repeated-measures analyses of variance (ANOVA). Table 5 Descriptive statistics of the mediolateral force moment variability for both cognitive tasks as a function of congruency and time bin. M: mean, S: standard deviation. target-aligned Cognitive conflict task Time bin -150 to -75 ms -75 ms to target onset target onset to 75 ms 75 to 150 ms 150 to 225 ms 225 to 300 ms Congruency M SD M SD M SD M SD M SD M SD Both tasks included Incongruent -2.60 0.52 -2.60 0.53 -2.62 0.53 -2.62 0.52 -2.65 0.53 -2.69 0.50 Congruent -2.59 0.53 -2.58 0.54 -2.60 0.54 -2.63 0.54 -2.65 0.53 -2.68 0.50 Congruency effect -0.008 0.12 -0.02 0.12 -0.02 0.12 0.003 0.11 -0.003 0.11 -0.006 0.11 Simon task Incongruent -2.60 0.50 -2.60 0.50 -2.63 0.50 -2.63 0.50 -2.66 0.50 -2.69 0.47 Congruent -2.59 0.51 -2.57 0.53 -2.60 0.53 -2.63 0.53 -2.65 0.50 -2.69 0.49 Congruency effect -0.013 0.11 -0.029 0.12 -0.035 0.12 -0.003 0.13 -0.003 0.13 -0.008 0.11 Spatial Stroop task Incongruent -2.59 0.55 -2.59 0.56 -2.61 0.56 -2.61 0.55 -2.64 0.55 -2.68 0.54 Congruent -2.59 0.54 -2.58 0.56 -2.60 0.55 -2.62 0.55 -2.64 0.55 -2.67 0.52 Congruency effect -0.003 0.12 -0.012 0.11 -0.005 0.11 0.010 0.09 -0.003 0.09 -0.004 0.10 response-aligned Cognitive conflict task Time bin -300 to -225 ms -225 to -150 ms -150 to -75 ms -75 ms to response onset response onset to 75 ms 75 to 150 ms Congruency M SD M SD M SD M SD M SD M SD Both tasks included Incongruent -2.68 0.50 -2.69 0.51 -2.73 0.50 -2.72 0.48 -2.69 0.49 -2.69 0.46 Congruent -2.65 0.51 -2.66 0.52 -2.69 0.51 -2.69 0.50 -2.68 0.50 -2.67 0.47 Congruency effect -0.024 0.11 -0.029 0.12 -0.036 0.12 -0.031 0.10 -0.017 0.12 -0.011 0.12 Simon task Incongruent -2.68 0.47 -2.70 0.48 -2.73 0.48 -2.73 0.45 -2.71 0.45 -2.70 0.43 Congruent -2.66 0.49 -2.67 0.50 -2.69 0.50 -2.70 0.48 -2.69 0.48 -2.68 0.46 Congruency effect -0.021 0.13 -0.030 0.11 -0.036 0.11 -0.025 0.11 -0.017 0.13 -0.012 0.13 Spatial Stroop task Incongruent -2.67 0.53 -2.69 0.53 -2.72 0.52 -2.72 0.51 -2.68 0.52 -2.68 0.50 Congruent -2.64 0.53 -2.66 0.55 -2.68 0.53 -2.68 0.52 -2.67 0.52 -2.67 0.49 Congruency effect -0.028 0.10 -0.029 0.13 -0.037 0.13 -0.038 0.10 -0.016 0.11 -0.010 0.11 Table 6 Test statistics of ANOVAs of the congruency effect for the moment variability in each temporal bin (target-aligned and response-aligned) for the both cognitive tasks in both directions of body sway. Significant effects or interactions are indicated in bold. F, p, partial eta^2 Temporal bin -150 to -75 ms -75 ms to target onset target onset to 75 ms 75 to 150 ms 150 to 225 ms 225 to 300 ms Target-aligned Both cognitive tasks Anteroposterior F(1, 89) = 0.50, p = .48, ƞ p 2 < .01 F(1, 89) = 0.29, p = .59, ƞ p 2 < .01 F(1, 89) = 0.32, p = .57, ƞ p 2 < .01 F(1, 89) = 0.14, p = .71, ƞ p 2 < .01 F(1, 89) = 0.05, p = .82, ƞ p 2 < .01 F(1, 89) = 0.48, p = .49, ƞ p 2 < .01 Mediolateral F(1, 89) = 0.69, p = .41, ƞ p 2 < .01 F(1, 89) = 5.24, p = .02, ƞ p 2 = .06 F(1, 89) = 5.47, p = .02, ƞ p 2 = .06 F(1, 89) = 0.17, p = .679, ƞ p 2 < .01 F(1, 89) = 0.20, p = .656, ƞ p 2 < .01 F(1, 89) = 0.62, p = .435, ƞ p 2 < .01 Simon task Anteroposterior F(1, 89)= 0.51, p=.48, ƞ p 2 <.01 F(1, 89)= 0.08, p=.77, ƞ p 2 <.01 F(1, 89)= 0.26, p=.61, ƞ p 2 <.01 F(1, 89)= 0.46, p=.50, ƞ p 2 <.01 F(1, 89)= 0.12, p=.73, ƞ p 2 <.01 F(1, 89)= 0.58, p=.45, ƞ p 2 <.01 Mediolateral F(1, 89)= 1.21, p=.27, ƞ p 2 =.01 F(1, 89)= 5.31, p=.02, ƞ p 2 =.06 F(1, 89)= 7.68, p=.007, ƞ p 2 =.08 F(1, 89)= 0.06, p=.81, ƞ p 2 <.0 F(1, 89)= 0.05, p=.82, ƞ p 2 <.01 F(1, 89)= 0.44, p=.51, ƞ p 2 <.01 Spatial Stroop task Anteroposterior F(1, 89)= 2.98, p=.09, ƞ p 2 =.03 F(1, 89)= 1.00, p=.32, ƞ p 2 =.01 F(1, 89)= 0.07, p=.79, ƞ p 2 <.01 F(1, 89)= 1.45, p=.23, ƞ p 2 =.02 F(1, 89)= 0.44, p=.51, ƞ p 2 <.01 F(1, 89)= 0.03, p=.87, ƞ p 2 <.01 Mediolateral F(1, 89)= 0.05, p=.83, ƞ p 2 <.01 F(1, 89)= 1.01, p=.32, ƞ p 2 =.01 F(1, 89)= 0.17, p=.68, ƞ p 2 <.01 F(1, 89)= 0.99, p=.32, ƞ p 2 =.01 F(1, 89)= 0.09, p=.76, ƞ p 2 <.01 F(1, 89)= 0.12, p=.73, ƞ p 2 <.01 Temporal bin -300 to -225 ms -225 to -150 ms -150 to -75 ms -75 ms to response onset response onset to 75 ms 75 to 150 ms Response-aligned Both cognitive tasks Anteroposterior F(1, 89) = 6.28, p = .01, ƞ p 2 = .07 F(1, 89) = 2.72, p = .10, ƞ p 2 = .03 F(1, 89) = 0.46, p = .50, ƞ p 2 < .01 F(1, 89) = 5.54, p = .021, ƞ p 2 = .06 F(1, 89) = 7.04, p = .009, ƞ p 2 = .07 F(1, 89) = 0.73, p = .395, ƞ p 2 < .01 Mediolateral F(1, 89) = 7.72, p = .007, ƞ p 2 = .08 F(1, 89) = 10.85, p = .001, ƞ p 2 = .11 F(1, 89) = 14.68, p < .001, ƞ p 2 = .14 F(1, 89) = 14.30, p < .001, ƞ p 2 = .14 F(1, 89) = 3.12, p = .08, ƞ p 2 = .03 F(1, 89) = 1.63, p = .20, ƞ p 2 = .02 Simon task Anteroposterior F(1, 89)= 2.60, p=.11, ƞ p 2 =.03 F(1, 89)= 1.57, p=.21, ƞ p 2 =.02 F(1, 89)= 0.08, p=.79, ƞ p 2 <.01 F(1, 89)= 2.39, p=.13, ƞ p 2 =.03 F(1, 89)= 6.91, p=.01, ƞ p 2 =.07 * F(1, 89)= 2.90, p=.09, ƞ p 2 =.03 Mediolateral F(1, 89)= 2.42, p=.12, ƞ p 2 =.03 F(1, 89)= 6.28, p=.014, ƞ p 2 =.07 F(1, 89)= 9.96, p=.002, ƞ p 2 =.10 F(1, 89)= 5.00, p=.03, ƞ p 2 =.05 F(1, 89)= 1.65, p=.20, ƞ p 2 =.02 F(1, 89)= 0.80, p=.37, ƞ p 2 <.01 Spatial Stroop task Anteroposterior F(1, 89)= 2.50, p=.12, ƞ p 2 =.03 F(1, 89)= 0.82, p=.37, ƞ p 2 <.01 F(1, 89)= 0.54, p=.46, ƞ p 2 <.01 F(1, 89)= 3.86, p=.05, ƞ p 2 =.04 F(1, 89)= 0.88, p=.35, ƞ p 2 <.01 F(1, 89)= 0.56, p=.46, ƞ p 2 <.01 Mediolateral F(1, 89)= 7.14, p=.009, ƞ p 2 =.07 F(1, 89)= 4.72, p=.03, ƞ p 2 =.05 F(1, 89)= 6.93, p=.01, ƞ p 2 =.07 F(1, 89) = 11.97, p<.001, ƞ p 2 =.12 F(1, 89)= 1.77, p=.19, ƞ p 2 =.02 F(1, 89)= 0.80, p=.37, ƞ p 2 <.01 For the target-aligned AP force moment time series, a change across the six time bins was observed (F(2.94, 261.79) = 71.42, MSE = 0.0067, p < .001, ƞ p 2 = .45, BF = 1.56 × 10 51 ±0.59%; Fig. 4 a) only. This was caused by a general reduction in moment variability, independent of congruency, that became observable in the time bin from 150 ms to 225 ms after target onset (M 1 = -2.33, SD 1 0.51; M 2 =-2.32, SD 2 0.52; M 3 = -2.32, SD 3 0.52; M 4 = -2.33, SD 4 0.52; M 5 = -2.35, SD 5 0.52; M 6 =-2.39, SD 6 0.51). A similar change across time bins was also seen in the ML direction (F(2.85, 254.02) = 98.61, MSE = 0.0085, p < .001, ƞ p 2 = .53, BF = 1.17 × 10 66 ±1.85%) but with an earlier start of reduction observable at the time bin from target onset to 75 ms after (M 1 = -2.59, SD 1 0.52; M 2 = -2.59, SD 2 0.54; M 3 =-2.61, SD 3 0.53; M 4 = -2.62, SD 4 0.53; M 5 = -2.65, SD 5 0.53; M 6 = -2.68, SD 6 0.50). In addition, an interaction between change across time bins and the congruency condition occurred (F(3.47, 308.88) = 2.58, MSE = 0.0044, p = .045, ƞ p 2 = .03). Although the frequentist ANOVA suggested a significant interaction, the Bayes Factor analysis provided extreme evidence in favour of the main-effects-only model excluding the interaction (BF = 0.03 ± 1.95%). The time bins from 75 ms before to target onset (F(1, 89) = 5.24, MSE = 0.0035, p = .024, ƞ p 2 = .06, BF = 1.69 ± 0.93%) and from target onset to 75 ms after target onset (F(1, 89) = 5.47, MSE = 0.0035, p = .022, ƞ p 2 = .06; BF = 1.86 ± 0.78%) demonstrated reduced moment variability in incongruent trials (M 2 =-2.60, SD 2 0.53; M 3 =-2.62, SD 3 0.53) compared to congruent trials (M 2 =-2.58, SD 2 0.54; M 3 =-2.60, SD 3 0.54; Fig. 4 c). The reason for this observation lies in an effect pattern demonstrated by the Simon task alone and is presented in more detail in the supplementary materials. For the response-aligned force moment time series, AP moment variability demonstrated significant main effects for congruency (F(1, 89) = 6.07, MSE = 0.0149, p = .016, ƞ p 2 = .06, BF = 2.50 ± 2.43%) and change across time bins (F(2.31, 205.65) = 11.85, MSE = 0.0148, p < .001, ƞ p 2 = .12, BF = 87431211 ± 0.39%; Fig. 4 b) only, but no interaction between both factors. Moment variability was lower in incongruent trials (M= -2.38, SD 0.49) than congruent trials (M=-2.37, SD 0.50). Across the time bins, moment variability reduced until the time bin from 75 ms to response onset and then began to rise again (M 1 =-2.37, SD 1 0.51; M 2 =-2.37, SD 2 0.51; M 3 =-2.39, SD 3 0.50; M 4 =-2.39, SD 4 0.49; M 5 =-2.36, SD 5 0.49; M 6 =-2.36, SD 6 0.49). The cognitive task had no specific influence on moment variability or its time course. For the ML moment variability when aligned to response-onset, significant main effects were observed for congruency (F(1, 89) = 11.98, MSE = 0.0280, p < .001, ƞ p 2 = .12, BF = 30.18 ± 1.54%) and time bins (F(2.22, 197.56) = 14.47, MSE = 0.0164, p < .001, ƞ p 2 = .14, BF = 17664113019 ± 0.46%), in addition to an interaction between both factors (F(3.63, 322.98) = 2.63, MSE = 0.0042, p = .040, ƞ p 2 = .03; Fig. 4 d). Bayes Factor analysis, however, did not calculate a statistical model that includes the interaction as more likely than a model with both main effects only (BF = 0.02 ± 2.33%). Moment variability was lower in incongruent trials (M=-2.70, SD 0.49) than congruent trials (M=-2.67, SD 0.50). Across the time bins, moment variability reduced until the time bin from 75 ms to response onset and then began to rise again (M 1 =-2.66, SD 1 0.504; M 2 =-2.68, SD 2 0.513; M 3 =-2.71, SD 3 0.50; M 4 =-2.71, SD 4 0.490; M 5 =-2.69, SD 5 0.492; M 6 =-2.68, SD 6 0.466). The interaction between congruency and time bins resulted from only the four time bins before response-onset showing reduced moment variability in incongruent trials (M 1 = -2.68, SD 1 0.499; M 2 = -2.69, SD 2 0.506; M 3 =-2.73, SD 3 0.498; M 4 = -2.72, SD 4 0.480) compared to congruent trials (M 1 = -2.65, SD 1 0.510; M 2 = -2.66, SD 2 0.521; M 3 =-2.69, SD 3 0.514; M 4 = -2.69, SD 4 0.499; Fig. 4 d). The cognitive task had no specific influence on moment variability or its time course as a three-way interaction between cognitive task, congruency and time bin was not observed (F(3.84, 341.76) = 0.29, MSE = 0.0033, p=.878, ƞ p 2 <.01, BF = 4.18 × 10 − 8 ±3.33%). Likewise, a comparison between both cognitive tasks regarding their maximum reduction of force moment variability during incongruent trials did not demonstrate a difference in their maximum congruency effect sizes (F(1, 89) = 0.02, MSE = 0.0101, p=.899, ƞ p 2 <.01, BF = 0.16 ± 0.99%). --- Insert Tables 4 , 5 , 6 , and Fig. 4 about here --- Discussion To elucidate the mechanisms behind interference between cognitive processes and the control of body balance, we pursued a novel event-related methodology, which indicated that engagement of cognitive control for the resolution of response selection conflict impacts on the concurrent control of body balance [ 33 , 47 ]. In the present study, we aimed to extend our previous observations regarding the permeation of response selection conflict in a cognitive task into the balance control domain. In a Simon task and a Spatial Stroop task, we found strong cognitive congruency effects in both tasks in combination with reduction in mediolateral force moment variability in incongruent compared to congruent trials. The time range in which congruency influenced moment variability before response onset (e.g. in terms of an earlier onset of a difference between congruent and incongruent trials in the Spatial Stroop task) did not differ qualitatively between the two cognitive tasks (no three-way interaction between cognitive task, congruency, and temporal bin). The Simon task analysis revealed strong sequential conflict adaptation effects, where the typical Simon effect was modulated noticeably by the previous trial's congruency. After congruent trials, participants showed the standard Simon effects (better performance in congruent compared to incongruent trials), but after incongruent trials, these effects disappeared and even reversed. This pattern demonstrates that experiencing response selection conflict on one trial improves performance and eliminates (and even slightly reverses) the typical impact of incongruency [for similar findings see e.g. 10] on the subsequent trial. The Spatial Stroop task showed sequential conflict adaptation effects like the Simon task. After congruent trials, participants displayed the typical Spatial Stroop effects, and after incongruent trials, these congruency effects were eliminated [ 45 ]. This demonstrates that both tasks show conflict adaptation whereby previously incongruent trials improved subsequent performance. Different mechanisms [e.g. cognitive control, 48, cognitive control and mulit-level learning, 49, affect regulation, 50, feature integration, 51, 52] have been discussed to account for this sequential modulation, yet a discussion on these mechanisms is beyond the scope of this study. In our previous study [ 33 ] comparing incongruent and congruent Simon trials, we observed a reduced mediolateral force moment variability within a single time bin of 150 ms width before response onset in the response-aligned time series data. The previous experiment did not include a jittered duration between trials, so that it was possible that the effects we observed were influenced by the periodic predictability of the trial cycle. In the present study, we aimed to improve our temporal resolution by halving the width of the time bins to 75 ms, we increased the entire range of time bins from 300 ms before to 150 ms after response onset, and by including temporal jitter between trials we ensured that the onset of consecutive trials was very hard to predict. The strongest effect of congruency on moment variability, that is the greatest relative reduction in force moment variability in incongruent trials, was detected in the temporal range from 150 ms to 75 ms before response onset. This finding confirms our observations in the previous study and implies that shortly before response onset some critical cognitive process may interfere with balance control. It seems, however, that the relative timing of this interference phenomenon is subject to some variability as less strong effects occurred in the two neighbouring time bins too. Furthermore, it is conceivable that the cognitive process, which causes the interference, is active across this entire period of 3 consecutive time bins from 225 ms before response onset until the onset of a response, when moment variability was reduced in incongruent trials in the Simon task. Provided that balance control is subject to neuromuscular delays and the body’s inertia, the impact of any critical cognitive process may precede any effects observable in the force plate data. Based on Kornblum’s taxonomy [ 35 ], we expected an impact of congruency on response-aligned force moment variability for both the Simon and the Spatial Stroop task. Like in the Simon task, the Spatial Stroop task demonstrated no congruency effects for anteroposterior force moment variability. Also like in the Simon task, the response-aligned data revealed an impact of congruency with reduced mediolateral force moment variability but apparently for a slightly extended time period from 300 ms before response onset to response onset. Nevertheless, these observations indicate that despite the additional stimulus-stimulus conflict in the Spatial Stroop compared to the Simon task, the different dimensional overlap structure did not induce additional interference with balance control. Descriptively, balance appears to vary with the type of cognitive task and, by extension, the nature or strength of cognitive conflict. As these differences are not statistically significant, however, any interpretation remains speculative and primarily serves to highlight avenues for more targeted investigation in future research. Similarly, an impact on target-aligned force moment variability was not observed in the Spatial Stroop task, which contrasts with the observations made in the Simon task discussed above. Based on these qualitative observations the possibility cannot be entirely excluded that the Spatial Stroop task may have induced a slight difference in the temporally structured modulation of balance control interference compared to the Simon task. As we did not find a three-way interaction between cognitive task, current trial congruency and time bin for the response-aligned analysis of mediolateral force moment variability, we can interpret any cognitive task-specific effects with caution only. It might be interesting to follow-up these indications with future research, also to corroborate our current conclusion that S-S conflict resolution does not permeate balance control. Both Simon and Spatial Stroop tasks demonstrated systematic modulation of force moment variability across the entire trial duration with a reduction in moment variability gradually emerging around target onset and the achievement of a relative minimum during response selection before onset of a response. This general dynamic might indicate tighter balance control when specific cognitive processing was required or at least expected. Koger et al. [ 47 ] demonstrated similar general dynamics of moment variability across much longer trial periods in a setup comprising a cognitive dual-task. We believe that the global reduction of moment variability during a trial compared to the leading (and following) intertrial interval is an expression of strategically timed, proactive balance control in anticipation of impending cognitive demands. Thus, in the present study, we can hypothesize that two distinct components modulate moment variability. A global reduction during a cognitive trial irrespective of the congruency condition, and a local reduction during response selection, when conflict resolution is necessary for a correct response. General Role Of Inhibition In Balance Control Balance control requires the selection of appropriate sensory cues (e.g. vestibular, visual, somatosensory, or proprioceptive) and down-weighting or suppressing of misleading inputs. These processes might mirror the role of cognitive control in dealing with task-irrelevant or conflicting information. The fusion of multisensory feedback into an integrated state estimate of self-motion is the prerequisite of stable body balance [ 53 , 54 ]. Cognitive control processes play an important role in maintaining balance under challenging sensory conditions [ 55 , 56 ]. When sensory feedback becomes unreliable or when sensory conflict occurs, for example in situations in which visual feedback and/or proprioception do provide accurate information about the state orientation, the stabilization of balance seems to involve cognitive processes for the selection of relevant, still informative sensory cues (e.g. vestibular sensation) and the suppression of those noninformative, misleading sensory cues [ 55 ]. An association between performance in a Spatial Stroop task and body sway also suggested that the ability to resolve cognitive conflict underlies more effective sensory disambiguation [ 56 ]. Gawthrop et al. [ 57 ] advanced current balance control theory further and suggested that continuously updated state estimates alone are insufficient for explaining the dynamics of body balance. According to their model, human balance control resembles an event-driven intermittent predictive control system, in which short-term predictive control is extended by a mechanism that corrects prediction errors through threshold-based state resets. When a predicted hold-state, which is a body balance state estimate kept active in memory, diverges from an observed-state based on multisensory fusion beyond a defined threshold, then the system triggers a reset that re-initializes the generalized hold-state. This process combines continuous open-loop prediction with intermittent error monitoring and closed-loop state updating [ 58 ]. Johannsen et al. [ 33 ] surmised that the local reduction in force moment variability within 150 ms before response onset was potentially caused by inhibitory suppression or delay of individual balance adjustments that occurred close in time to the resolution of cognitive conflict in the respective cognitive task. It may be the case that the resolution of conflict between a target’s stimulus-response mappings and the currently active task representation activates processes that are involved in the detection of conflicts between observed and hold-state and its updating. As an explanation of the observed reduction in moment variability, we suggested the existence of a “micro-bottleneck” similar to the central bottleneck model [ 32 ]: cognitive processes for response selection or conflict monitoring and resolution [ 48 ] cannot be deployed simultaneously to processes of balance control. At least when they are engaged in disambiguation of intersensory conflict or the resolution of conflict between state estimates. In this sense, our point of view is compatible with the adaptive multiple resource time-sharing theory [ 59 , 60 ], which assumes that adjusting the time scale for balance adjustments directly affects the time available for a cognitive task and vice versa. The notion that cognitive control engagement may inhibit, suppress, or delay activity of balance control can also be explained through neurocognitive mechanisms, such as inhibition and gating [ 61 ]. When cognitive control is strongly engaged by conflict monitoring or response inhibition [ 62 ], the ongoing sensorimotor balance control loop may be actively suppressed or downregulated to prevent lower-level balance control activity from interfering or distracting higher level cognitive control. For instance, the transient reduction of the sensorimotor gain of corrective balance adjustments per se could have two parallel effects, such as reduced moment variability [ 63 , 64 ] as well as less frequent bottom-up calls for high-level involvement. More specifically, when the balance system detects instability, sensorimotor networks may generate signals that demand attention. Over a short period of time, this strategy might not result in noticeable balance instability that would require high-level intervention like over longer durations. Therefore, central mechanisms may try to suppress the intrusion of these sensorimotor signals to shield a cognitive task [ 65 ]. Thus, when cognitive control is activated, the activation of competing sensorimotor representations may be downregulated or suppressed to facilitate the cognitive task set. Direction-specificity of Interference Effects A noticeable observation in our previous [ 33 ] and in our present study is that the effect of incongruency was far stronger in the mediolateral than the anteroposterior direction. Again, we observed a correspondence between the mediolateral direction in which manual response decisions had to be performed and the mediolateral direction of body balance control where the observed congruency effects predominated. Thus, the effect of cognitive interference on balance adjustments in multitasking situations may not only be sensitive to the involvement of any specific cognitive processes, such as the suppression of task-irrelevant target features, but may also be direction-specific based on a task-specific, egocentric frame of reference. It has been argued that the balance control system can independently adapt and respond to challenges in different directional planes through control mechanisms that decouple ML and AP balance control via direction-specific muscle synergies [ 66 – 68 ]. In addition to the evidence that body balance control in the mediolateral and anteroposterior planes can be dissociated, Scholz and Schöner [ 69 ] suggested that the motor system strategically organizes movement variability into two subspaces due to motor system redundancy: it minimizes task-relevant variability that directly affects performance outcomes while it allows or even exploits task-redundant motor variability that does not compromise the task goal. This implies that the balance control system selectively channels variability by tightly constraining joint movements that could destabilize the CoM while permitting compensatory variations across joints that maintain balance [ 70 ] so that structured flexibility and adaptability is enabled through redundant multisegmental joint configurations [ 71 ]. Transient suppression or reduction of variability in directions that threaten the stability of a task-relevant variable is selectively applied at critical task phases [ 72 ]. Possible mechanisms for stricter balance control by means of the reduction of variance could involve increased muscle co-contractions to stiffen joints, alterations in neural feedback control gains, or damping of exploratory behaviour, that are only applied when boundary conditions are approached, constraints encountered, or critical events detected. The integrated control of body balance alongside a secondary task performed while standing, such as tracking moving targets, manipulating objects, reaching, or balancing items, introduce additional, ‘suprapostural’ cognitive performance demands that need to be coordinated with the fundamental requirement of maintaining stable posture. The interference observed between the cognitive task domain and balance control observed in these multitasking contexts has been debated as an indication of a facilitatory role of balance control or adaptive time-sharing of a central capacity [ 73 – 75 ]. In a multitasking situation, where some kind of precision behaviour in the suprapostural task is required, decomposition of joint variability into performance-relevant components and non-relevant components becomes more complex. The assumption is that adaptive motor solutions are produced by the reduction of variability that affects the motion performance across repetitions. To achieve this, the balance control system might exhibit flexible task prioritization by allowing increased (or unaltered) variability in postural degrees of freedom that do not compromise suprapostural performance, while variability on the critical orthogonal direction is reduced. In our present study, both cognitive tasks did not involve explicit precision demands, but minimized retinal slip at the time of target onset in the mediolateral direction might have been implicitly beneficial. In follow-up experiment, we are currently testing if the direction-selective reduction in moment variability is dependent on an egocentric frame of reference that is imposed by the demands of the cognitive task. Summary And Conclusion Our study investigated how cognitive conflict tasks interfere with balance control using an event-related methodology, successfully replicating and extending previous findings [ 33 ] that response selection conflict systematically affects balance control. We examined two conflict paradigms, the Simon task and Spatial Stroop task, while participants maintained upright standing posture. Both tasks produced strong congruency effects alongside reduced mediolateral force moment variability during incongruent compared to congruent trials, confirming that balance adjustments are systematically affected by conflict resolution demands. Both tasks reduced mediolateral postural variability during incongruent trials. Taken together, these findings demonstrate that cognitive conflict consistently permeates into the domain of balance control, manifesting as lower force moment variability during conflict resolution. The effects are temporally discrete and occur only during the very brief period of conflict resolution and can only be detected using a temporally high-resolution event-related analysis. This study provides robust evidence that different types of cognitive conflict engage balance control systems through partially different pathways, with the Spatial Stroop task producing more extensive, robust, and temporally structured interference compared to the Simon task's diffuse and transient patterns. This indicates that while conflict resolution transiently competes with balance control, the underlying cognitive-balance interactions are shaped by task-specific mechanisms. From a theoretical perspective, the results align with predictive models of balance control and theories of intermittent, event-driven postural adjustment systems, which suggest that discrete corrective actions are triggered only when stability estimates fall below critical thresholds. The observed reduction in adjustment rates during conflict trials reflects a temporary suppression or postponement of balance adjustments while cognitive resources are recruited for conflict resolution. This supports the notion that shared cognitive-motor resources operate through temporally specific mechanisms and demonstrates that the interaction between cognition and balance control is intermittent and event-driven, with balance control being adaptively constrained during periods in which higher cognitive demand is present. This provides new insights into the dynamic interplay between cognitive control and the stability of body balance. Declarations Data availability statement All extracted data files are available from the figshare database (https://doi.org/10.6084/m9.figshare.31305772). Acknowledgements We wish to thank Wiebke Janesch and Frida Schulz for their contributions to data collection. Author contributions L.J., A.K., I.K., H.M designed and planned the study. L.J. and E.S. supervised data collection. L.J. processed the data and performed the data analysis. L.J., An.Ko., E.S., D.N.S., A.K., I.K., H.M. prepared the manuscript. 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Additional Declarations No competing interests reported. Supplementary Files JohannsenMuellercognitiveconflictbalancecontrol030226supplementarySciRep.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Apr, 2026 Reviews received at journal 01 Apr, 2026 Reviews received at journal 29 Mar, 2026 Reviewers agreed at journal 10 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers invited by journal 02 Mar, 2026 Editor assigned by journal 20 Feb, 2026 Editor invited by journal 19 Feb, 2026 Submission checks completed at journal 17 Feb, 2026 First submitted to journal 17 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8884917","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":600897324,"identity":"e8813e02-011e-4cb4-aca3-e8f2053e8b25","order_by":0,"name":"Leif Johannsen","email":"data:image/png;base64,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","orcid":"","institution":"RWTH Aachen University","correspondingAuthor":true,"prefix":"","firstName":"Leif","middleName":"","lastName":"Johannsen","suffix":""},{"id":600897329,"identity":"9bfbd604-3915-42ec-be98-618729cf21d0","order_by":1,"name":"Anton Koger","email":"","orcid":"","institution":"RWTH Aachen University","correspondingAuthor":false,"prefix":"","firstName":"Anton","middleName":"","lastName":"Koger","suffix":""},{"id":600897331,"identity":"2c839d4f-ae9d-4161-9c39-cea982081457","order_by":2,"name":"Elisa Ruth Straub","email":"","orcid":"","institution":"University of Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Elisa","middleName":"Ruth","lastName":"Straub","suffix":""},{"id":600897332,"identity":"2f0f8085-7adc-49c7-9e42-11c67dc3fdf1","order_by":3,"name":"Denise Nadine Stephan","email":"","orcid":"","institution":"RWTH Aachen University","correspondingAuthor":false,"prefix":"","firstName":"Denise","middleName":"Nadine","lastName":"Stephan","suffix":""},{"id":600897335,"identity":"8fabb67d-05f8-429a-ae12-5a0301facaba","order_by":4,"name":"Andrea Kiesel","email":"","orcid":"","institution":"University of Freiburg","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Kiesel","suffix":""},{"id":600897337,"identity":"24854c82-2f62-4b32-9e62-ff09523e27e2","order_by":5,"name":"Iring Koch","email":"","orcid":"","institution":"RWTH Aachen University","correspondingAuthor":false,"prefix":"","firstName":"Iring","middleName":"","lastName":"Koch","suffix":""},{"id":600897338,"identity":"33e45d90-c4ac-4180-87b8-11d5155d360d","order_by":6,"name":"Hermann Müller","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Hermann","middleName":"","lastName":"Müller","suffix":""}],"badges":[],"createdAt":"2026-02-15 09:09:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8884917/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8884917/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104404414,"identity":"a41d7086-8299-4789-b599-12c50369212c","added_by":"auto","created_at":"2026-03-11 12:20:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51649,"visible":true,"origin":"","legend":"\u003cp\u003eTarget-response configurations of a Simon task (top row) and a Spatial Stroop task (bottom row). Participants reacted with a button press on a game controller according to the identity of the letter target or the pointing direction of an arrow irrespective of the location.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8884917/v1/10f14c179393d96f22ebde22.png"},{"id":104178622,"identity":"03c580f7-88d6-4c28-94fe-1fae3ebe033d","added_by":"auto","created_at":"2026-03-08 16:58:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":157748,"visible":true,"origin":"","legend":"\u003cp\u003eRaincloud plots of the (A) reaction times and (B) error proportions in the Simon task as a function of the congruency of the current trial and of the previous trial.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8884917/v1/98a41edf5cc8782a95702a41.png"},{"id":104178618,"identity":"c86f1099-7011-49df-8d55-d8975950738c","added_by":"auto","created_at":"2026-03-08 16:58:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":145614,"visible":true,"origin":"","legend":"\u003cp\u003eRaincloud plots of the (A) reaction times and (B) error proportions in the Spatial Stroop task as a function of the congruency of the current trial and of the previous trial.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8884917/v1/4da54fd45ef1fec16e2f1689.png"},{"id":104178620,"identity":"05111cc9-ebdf-4e11-8b3a-5551573a9b47","added_by":"auto","created_at":"2026-03-08 16:58:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":261727,"visible":true,"origin":"","legend":"\u003cp\u003eRaincloud plots of the distributions of the anteroposterior (A) and mediolateral (B) log-transformed standard-deviation of moment variability in both cognitive tasks across the target-aligned temporal bins as a function of congruency of the current trial (only for trials where the previous trial was congruent too) for each extracted time bin (75 ms width; from 150 ms before to 300 ms after target onset). Distributions of the log-transformed standard-deviation of moment variability across the response-aligned temporal bins in the anteroposterior (C) and mediolateral (D: from 300 ms before to 150 ms after response onset).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8884917/v1/52f05bac4c28c46f9c40a471.png"},{"id":104779517,"identity":"b076b65b-fad5-49f5-b41c-87b56a3f98ba","added_by":"auto","created_at":"2026-03-17 07:41:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2591335,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8884917/v1/476702a0-dfe2-4020-a0c1-f578623d8a8a.pdf"},{"id":104178621,"identity":"d659bec9-9a6d-4c25-a361-b116c9a43808","added_by":"auto","created_at":"2026-03-08 16:58:09","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":4949954,"visible":true,"origin":"","legend":"","description":"","filename":"JohannsenMuellercognitiveconflictbalancecontrol030226supplementarySciRep.docx","url":"https://assets-eu.researchsquare.com/files/rs-8884917/v1/12f6ab0a926950b8dbc9d8ab.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contrasting cognitive control in the Simon and spatial Stroop tasks regarding their interference with the control of standing balance","fulltext":[{"header":"Public significance","content":"\u003cp\u003eThis study shows evidence that tasks that create cognitive conflicts, such as a Simon task or a Spatial Stroop task, interfere with our ability to maintain balance. By measuring posture on a fine-grained, moment-to-moment basis, we found that resolving cognitive conflict seems to temporarily reduce the likelihood to perform corrective balance adjustments. Our findings highlight that balance control and cognitive control are closely linked functionally, suggesting that everyday situations requiring cognitive processing of ambiguous information and quick decision-making in the light of distracting information may momentarily compromise balance stability.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eMaintaining body balance (\u0026quot;balance control\u0026quot;) while quietly standing upright appears motionless but represents a continuously active and dynamic activity. This results from the interplay between gravitational forces on the body and counteracting muscle-generated forces. Stability in standing balance is maintained if the vertical projection of the body\u0026apos;s Centre-of-Mass (CoM) remains within the boundaries of the base of support. The sensorimotor control loop that ensures successful balance control fundamentally requires combining information from various sensory systems that monitor the body\u0026apos;s oscillatory movements relative to the surrounding environment, along with choosing and implementing adequate balance adjustments at the motor level [1-4].\u003c/p\u003e\n\u003cp\u003eBalance control during standing is frequently evaluated using posturographic methods that employ force plates to measure body sway through ground-reaction force dynamics [5]. According to Newton\u0026apos;s third law of motion, the ground-reaction force represents the total of forces and moments generated by the neuromuscular system of an individual regulating the angular velocity and acceleration of the body\u0026apos;s Centre-of-Mass as it is affected by gravitational pull, other external and also internal forces acting upon the body [6]. The context-dependent regulation of body oscillation can be examined comprehensively through diverse measures of body motion over a specified time period in addition to measures that capture the complex, longer-term dynamics of body sway [7].\u003c/p\u003e\n\u003cp\u003eCognitive control comprises those executive processes that adapt goal-directed behaviour in dynamic environments that become challenging by changing task demands [8]. The capability to inhibit inappropriate responses and to resolve conflict between competing stimuli is a central aspect. The Simon effect [9] refers to the interference when there is a stimulus-response (S-R) conflict, where responses are faster when the stimulus location corresponds with the response location than when it does not, even though stimulus location is not part of the instructed task. Presumably, the Simon effect arises because the irrelevant spatial location of the stimulus automatically activates a spatially congruent response tendency [10]. This creates competition between the correct task-relevant response and the automatically activated spatial response. The conflict occurs at the response selection stage when competing motor programmes must be resolved. Similarly, the Spatial Stroop effect [11] also refers to interference when two attributes of the same stimulus conflict with each other (e.g., left vs. right pointing arrows presented at a right or left location on the screen), where the conflict mechanism involves conflict between the relevant spatial dimension (direction) and the irrelevant spatial dimension (target location). The Spatial Stroop task requires processing of a spatial target while ignoring spatial position, creating stimulus-stimulus (S-S) conflict in addition to a S-R conflict as in the Simon task. Therefore, the Spatial Stroop task interference is thought to occur during stimulus processing and response selection before response onset [12].\u003c/p\u003e\n\u003cp\u003eTwo lines of research have been followed to investigate how control of balance and of cognition is mutually linked. First, several recent studies explored whether standing compared to sitting results in interference on the cognitive task using motor requirements as independent variable. Here findings are mixed, while some studies reported some impact of a standing posture (relative to sitting) on performance in diverse cognitive tasks [13-15], such as the Stroop or the Navon tasks, other studies could not replicate these findings [16-18]. Second, another line of research assessed the impact of a cognitive task on balance control while standing. Consequently, in this second line of research, balance performance becomes the dependent variable, which necessitates an appropriate and sensitive quantification of balance performance. The impact of a cognitive task on balance control while standing can only be determined by assessing how variations in cognitive demands influence balance performance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCognitive and sensorimotor processes are known to interfere with one another [19-21]. This is illustrated by balance control as it requires anticipatory planning, multisensory integration to estimate postural state [22], and the selection of corrective responses that become more reliant on higher-order cognition when aging or pathology slows processing [23-25]. Earlier studies examining how cognition interacts with balance control typically used dual-task paradigms assessing balance with a concurrent cognitive task. When balance remained unaffected but cognitive performance declined, researchers inferred that balance control relies on domain-specific cognitive processes [26, 27]. Typically, balance measures are aggregated across a longer period of time and thus across a number of individual trials with the cognitive task.\u003c/p\u003e\n\u003cp\u003eOnly a few studies have tested cognition\u0026ndash;balance interference using conflict tasks like the Stroop task. Melzer et al. [28] showed that a modified Stroop task altered sway in older adults depending on stance width, with reduced sway in narrow stance likely reflecting increased postural stiffness. Similarly, Patterson et al. [29] reported that older adults performing a spatial Stroop-like task exhibited longer reaction times and less accurate responses in combination with reduced body sway, again suggesting a strategy shift toward postural stiffening. Barra et al. [30] used auditory verbal and spatial Stroop tasks of varying difficulty together with different stance conditions and observed reduced body sway under dual-tasking, which they interpreted as increased automatization of balance control or postural stiffening.\u003c/p\u003e\n\u003cp\u003eWhile these studies following a traditional approach demonstrated that cognitive control and balance control interfere with each other, the approach used cannot pinpoint how specific cognitive processes (such as conflict resolution during stimulus or response processing) affect balance with the precise timing needed for detailed process analysis. Consequently, these studies typically led to broad generalizations about shared cognitive and motor resources rather than specific mechanistic insights. The research examining how attentional control tasks affect standing balance has not produced clear findings regarding the timing of cognitive processes within individual trials. This limitation likely stems from how balance performance is typically measured by averaging time series data over extended periods (tens of seconds to minutes). In contrast, cognitive dual-task research has established that cognitive resource sharing operates at the micro-level (i.e., at the millisecond scale) of specific processing stages during task execution, including response selection processes [see 31, 32, for reviews].\u003c/p\u003e\n\u003cp\u003eTherefore, we conjecture that investigating the interaction between cognitive control and balance control would benefit from research methods that enable event-related analysis of how cognitive processes influence balance control with high temporal precision. Johannsen et al. [33] developed an event-related methodology to investigate how cognitive control during cognitive conflict tasks influences balance control during normal upright standing. For this purpose, we utilized the Simon task paradigm as our main focus, which involves discrete stimulus-response (S-R) processing episodes only, in contrast to a Spatial Stroop task, which represents a combination of S-S and S-R conflicts. Participants stood on a force plate while performing a Simon task. Instead of investigating the effect of cognitive control on body sway during upright standing estimated over an extended stance period, we applied an event-related paradigm, in which the immediate effect of a single cognitive operation in the Simon task on balance control is determined from force moments on a sub-second time scale. We aggregated force-plate data in time bins of 150 ms around visual target onset and onset of motor responses (presses of hand-held keys) for examining process-specific interactions between cognitive processes and balance control during standing. First, we investigated balance control while performing the Simon task in a target-aligned way, so that differences would reflect predominantly stimulus-based processing conflicts. Second, we assessed balance control in a response-aligned way to isolate the effect of cognitive processing preceding overt response production in the Simon task [for similar analysis on EEG distinguishing stimulus- and response-lateralized readiness potential see 34]. We expected that if cognitive control processes interfered with balance control, we would observe correlates of cognitive conflict in the Simon task in the balance control domain. Our study showed that resolving response conflict in the Simon task not only produced the expected congruency effect in cognitive performance but also reduced mediolateral sway variability in the temporal period of 150 ms before response onset. This indicates that cognitive conflict resolution processes can momentarily influence balance control in a direction-specific manner.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCurrent study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, we aimed to extend our understanding of interference between balance control and cognitive control by comparing the cognitive conflicts induced by the Simon and the Spatial Stroop tasks. To specifically focus on cognitive conflict processing, in Johannsen et al. [33], we initially decided against using the Stroop task, which Kornblum et al.\u0026apos;s [35] dimensional overlap model indicates involves both perceptual conflict and potentially response conflict as well. We instead employed the Simon task as our experimental framework, a paradigm widely recognized for examining cognitive conflict specifically during response selection processes [36, 37]. The taxonomy of Kornblum et al. [35] classified cognitive tasks with respect to the question whether dimensions of stimuli and responses overlap. Overlap within a stimulus set would lead to the potential of stimulus-stimulus conflict, while overlap between stimulus and response sets could lead to stimulus-response conflict. When stimulus and response dimensions overlap, task-irrelevant stimulus information can involuntarily activate a response. However, if the activated response is incorrect, this response tendency based on irrelevant information would require some degree of cognitive control intervention to prevent it from corrupting actual performance. Any differences between the Simon task and the Spatial Stroop task congruency effects lie in the fundamental nature of the conflict being processed according to Kornblum\u0026rsquo;s dimensional overlap model [38]. In previous studies, two types of conflict were addressed: S-S and S-R conflict [e.g. see review of 39]. In the current study, therefore, we compared the Simon task with the Spatial Stroop task with the assumption that the Spatial Stroop task would generate even stronger and earlier conflict. With respect to balance control, the interference effect of the Simon task may emerge later during response selection and preparation, while effects of the Spatial Stroop task may manifest themselves earlier during stimulus encoding and persist for a longer duration during response selection.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNinety healthy young adults (M=21.4 years, SD=2.7; female=67, male=23; right-handed=81) were recruited for the current study in two laboratories with basically identical setup in Aachen (n=72) and in Freiburg (n=18). Participants were na\u0026iuml;ve regarding the hypotheses of the experiment, reported normal or corrected-to-normal vision and had neither neurological, musculoskeletal, psychiatric, nor any other relevant medical diagnoses nor did they show any current balance impairments. Based on Johannsen et al. [33], where a t-test for dependent measures found in a within-subject effect size of congruency in the Simon task in the mediolateral body sway direction of dz=0.41, a sample size of 80 participants was calculated for an actual power of 0.95 [40]. Ten additional participants were recruited to follow a conservative approach. All participants were informed about the study protocol and gave signed written informed consent. Ethical approval was obtained prior to the study from the local faculty\u0026rsquo;s ethical committee at the RWTH Aachen University (2022_013_FB7_RWTH Aachen) and the study protocol was conducted in accordance with the ethical research standards of the amended declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquipment And Cognitive tasks\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was conducted in a dimly lit, quiet laboratory. A 31.5 inch LCD monitor with a refresh rate of 144 Hz and a resolution of 3840\u0026times;2160 pixels was used for the presentations of visual targets in both cognitive tasks described below. The monitor was placed in front of the participants at about 85 cm distance and a height of 130 cm. Targets were the white-on-black letters T and X (both 1 cm width and 1.5 cm heigh) and left- or right-pointing arrows (both 1.8 cm width and 0.8 cm height) that were presented 16 cm left or right from a fixation cross (1.5 cm width and height, presented horizontally and vertically centralized). The input device for the manual responses was a game controller (Rii PC controller USB gamepad; dimensions: 16 x 11.5 x 7 cm; weight: 161 g). Participants were instructed to press left and right keys on the controller using their left and right index fingers. Participants held the game controller with both hands in front of their upper body and they were told to hold the controller relaxed and rather close to their trunk with the elbows close to both sides of the body and the arms slightly flexed upwards at the elbow joints so that the hands were level with the height of their navel. They did not receive explicit instruction to stand as quietly as possible but were instructed to prevent any voluntary balance disturbance by moving body limbs or shifting weight only.\u003c/p\u003e\n\u003cp\u003eBody sway was recorded using a multi-component force plate type Kistler 9260AA with a temporal resolution of 1000 Hz. The force plate uses piezoelectric 3-component force sensors to register the forces and moments exerted on the plate in the three spatial directions. Sway recordings were performed on a second computer using the BioWare software (version 5.3.0.7; Kistler Group, 2012). The computer running the cognitive tasks communicated via a parallel port interface with the force plate computer, where additional channels were registered as analog input devices sampled also at 1 kHz and synchronized with the force plate data acquisition. These channels recorded uniquely encoded trigger signals sent at several trial events (e.g. fixation onset, target onset, and response onset) in each trial for later processing of behavioural data and force plate time series data [41].\u003c/p\u003e\n\u003cp\u003eWhile standing, participants performed the two cognitive tasks (Fig. 1) within a single session (duration 90 min to 2 h). The order of both tasks was counter-balanced across participants to control for any systematic order effects. At the beginning of each part of the session, participants performed at least ten practice trials to familiarize themselves to the experimental procedure of each task. In each task, participant performed ten blocks of roughly 280 s duration of continuous standing. They were offered breaks between the individual blocks. Each of the ten blocks contained 80 trials so that 800 trials were presented in total for each task.\u003c/p\u003e\n\u003cp\u003e--- Insert Figure 1 about here ---\u003c/p\u003e\n\u003cp\u003eThe cognitive tasks were run on a computer using PsychoPy [version 2023.2.3; 42]. A Simon task was modelled after the version used in Johannsen et al. [33]. It comprised a visual 2-alternative forced choice task, in which the letters \u0026lsquo;T\u0026rsquo; and \u0026lsquo;X\u0026rsquo; were presented either on the left or the right of a central fixation. Fixation and target were presented in white on a black background. The letter \u0026lsquo;T\u0026rsquo; required participants to respond with a left button press, and the letter \u0026lsquo;X\u0026rsquo; asked for a right button response while ignoring the presentation location. A match between the required manual response and the side of the target resulted in a congruent trial, while a mismatch between instructed target response and target location defined an incongruent trial.\u003c/p\u003e\n\u003cp\u003eA Spatial Stroop task [modelled after 43] was designed in analogy to the Simon task with arrows pointing to the left or right that were presented on the left or right side of the fixation. Participants were required to respond to the direction in which an arrow was pointing (left button press when an arrow pointed to the left and right button press when the arrow pointed to the right) while ignoring the presentation location. Again, a match between the required manual response and the side of the target resulted in a congruent trial, while a mismatch between instructed target response and target location defined an incongruent trial. In both cognitive tasks, the sequence of congruent and incongruent trials within a block was random.\u003c/p\u003e\n\u003cp\u003eFollowing a fixation cross of 200 ms duration, a target was presented horizontally to the left or the right of the fixation cross. The target and fixation cross remained visible until a manual response occurred, or a period of 1.5 s had passed without a response. The reaction time (RT) period was followed by 350 ms of feedback in case of an incorrect response (a correct response resulted in a blank screen) and each trial ended with a 200 ms blank screen inter-trial interval. Hence, the total response-target interval was 750 ms. During data analysis, we considered only trials with RTs shorter than 1250 ms, that is, trials with overall durations shorter than 2 s. Each intertrial interval was further extended by a blank screen before the onset of the next fixation with randomly jittered durations in the range from 500 ms to 2.5 s. This jitter period ensured that participants were unable to anticipate the exact onset of the next trial based on any rhythmic structure in the trial procedure. In addition, the fixation onset jittering decoupled slow oscillations in body sway from trial timing when aggregating over any individual trials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePost\u003c/strong\u003e\u003cstrong\u003e‑Processing Of Force Plate Data And Parameter Extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTime series data post-processing and parameter extraction were performed in MATLAB 2023b (The Mathworks, Natick, MA) as well as RStudio (version 2025.05.0+496; R version 4.4.2) using custom-prepared algorithms. Forces and moments of the force plate were used to characterize the control of body sway. A dual-pass moving average with sliding window width of 19 ms was applied for general smoothing of all time series data to remove any high frequency signals, artefacts or by-products, which are not directly associated with supraspinal control of sway, such as electromagnetic noise or peripheral and spinal reactions (muscle twitches or spinal reflexes). The experimental blocks for each cognitive task were segmented into individual trials using the trial event signals that indicated the onset of fixation.\u003c/p\u003e\n\u003cp\u003eSingle trials were excluded from post-processing if the entire duration of a trial surpassed 2 s, for example responses were not recorded in the 1250 ms interval after target onset. These trials were labelled as \u0026ldquo;unresponsive\u0026rdquo; and were not considered for further processing. Additionally, trials with incorrect responses, correct trials following an incorrect response, and the very first trials of each block were excluded. In the Simon task, a total proportion of 7.5% of all trials were excluded from data analysis, of which 3.6% were excluded as response errors, 3.4% as correct responses following an error, and 0.5% as correct responses with RTs longer than 1250 ms. In the Spatial Stroop task, a total of 6.1% of all trials were excluded from data analysis, of which 3.0% were excluded as response errors, 2.9% as correct responses following an error, and 0.2% as correct responses with RTs longer than 1250 ms.\u003c/p\u003e\n\u003cp\u003eLike in Johannsen et al. [33], two major branches of data processing were pursued by aligning all the time series data to the time points of the onset of the target (target-aligned) as well as the onset of the manual response (response-aligned). Around the anteroposterior (AP) and mediolateral (ML) axis for a specified time bin, the current state of balance was analysed as the standard deviation (SD) of the ground reaction force moment (units in Nmm). Variability of the force moment within a time bin expresses the amount of activity applied by the neuromuscular system for the control of standing balance. Greater variability would indicate balance adjustments being more likely to demonstrate their effect within this short period. We chose a temporal bin width of 75 ms (amounts to 75 datapoint at 1 kHz sample rate) duration for improved time course resolution compared to Johannsen et al. [33]. An increased number of temporal bins compared to our precursor study allowed us to describe the moment variability before and after each trial event in more detail. For target-aligned trial time series, therefore, six temporal bins were extracted from 150 ms before until 300 ms after target onset. Six temporal bins were also extracted for the response-aligned trial time series from 300 ms before to 150 ms after response onset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerformance in the Simon task and the Spatial Stroop task, in terms of RT and error proportions (EP), needed to be assessed to validate that a robust effect of cognitive conflict was induced by the respective target stimuli. For both cognitive tasks, congruency of the current trial and congruency of the previous trial were used as the independent variables. We considered previous trial congruence as additional independent variable, because ample of research [see also our own previous study, 33, e.g. 44] has shown that the impact of congruency in the current trial is larger after a previous congruent rather than incongruent trial.[1] Potential factors such as laterality of the target stimulus presentation and laterality of the manual reactions were not considered of interest due to lack of any a priori hypotheses because any specific effect of laterality would be cancelled out by calculating averages across sides.\u003c/p\u003e\n\u003cp\u003eThe dependent variables were RT and EP. RTs were directly measured by the presentation software and validated by signals of stimulus and response triggers in the force plate data. The dependent variables were based on response timing information acquired through the target stimulus presentation software directly as well as by the trial event trigger signals sent to the data acquisition board of the force plate setup. With respect to replicating our previous study [33], we restricted our analysis of the force-plate data to trials that followed a congruent previous trial because we expected the strongest effects of cognitive conflict in these trials [see also 45 for discussion]. As dependent variables representing balance control in both the AP and ML directions of sway, we calculated the standard deviation of the force moment time series within the respective time bins of each single trial of a participant.\u003c/p\u003e\n\u003cp\u003e[1] While there are several accounts for this so-called \u0026lsquo;congruency sequence effect\u0026rsquo; (e.g. Botvinick et al., 2001; Dignath et al., 2020; Egner, 2007; Hommel et al., 2004), for the purpose of controlling for the impact of the current congruency manipulation on balance control, it is sufficient for us to consider congruency in the previous trial only.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAll statistical computations were performed in R Studio (2025.09.1 Build 401; R version 4.4.2). For the force moment parameters, statistical analyses were performed for the target-aligned and the response-aligned time series data. The variability of the moments acting around the anteroposterior and mediolateral axes was analysed in terms of its standard deviation within each 75 ms time bin. Force moment variability was natural log-transformed before statistical analysis to approach an interval scaling of the dependent variable. Statistically significant effects and interactions were evaluated at an alpha level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in combination with a Bayes Factor [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] greater than 1.0.\u003c/p\u003e\n\u003ch3\u003eAnalysis of Manual Reactions\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eComparison Between Both Cognitive Tasks\u003c/h2\u003e \u003cp\u003eTo look at the effects of conflict in the two cognitive tasks, RT and EP were analysed with congruency as within-subject factor. Previous trial congruency was added as a second within-subject factor to assess specific sequential conflict adaptation effects, and cognitive task (Simon vs. Spatial Stroop) as a third within-subject factor of the repeated-measures analyses of variance (ANOVAs). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provide the descriptive statistics of the reaction times and error proportions for both cognitive tasks combined and individually and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the inferential test statistics of ANOVAs for the manual reaction latencies and the error proportions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the reaction times for both cognitive tasks as a function of congruency and previous trial congruency. M: mean, S: standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c13\" namest=\"c2\"\u003e \u003cp\u003eCognitive conflict task\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBoth tasks included\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePrevious trial congruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003ePrevious trial congruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003ePrevious trial congruency\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent trial congruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the error proportions for both cognitive tasks as a function of congruency and previous trial congruency. M: mean, S: standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c13\" namest=\"c2\"\u003e \u003cp\u003eCognitive conflict task\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBoth tasks included\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePrevious trial congruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003ePrevious trial congruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003ePrevious trial congruency\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent trial congruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTest statistics of ANOVAs for manual reaction times and error proportions with task condition as within-subject factor (rows 1 and 2) and for each individual cognitive task (Simon task: rows 3 and 4; Spatial Stroop task: rows 5 and 6). Significant effects or interactions are indicated in bold.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eF, p, partial eta^2, BF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMain effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMain effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMain effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTask condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCurrent trial\u003c/p\u003e \u003cp\u003econgruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrevious trial\u003c/p\u003e \u003cp\u003eCongruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTask condition\u003c/p\u003e \u003cp\u003eby current trial\u003c/p\u003e \u003cp\u003econgruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTask condition\u003c/p\u003e \u003cp\u003eby previous trial\u003c/p\u003e \u003cp\u003econgruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCurrent trial\u003c/p\u003e \u003cp\u003econgruency by\u003c/p\u003e \u003cp\u003eprevious trial\u003c/p\u003e \u003cp\u003econgruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTask condition\u003c/p\u003e \u003cp\u003eby current trial\u003c/p\u003e \u003cp\u003econgruency by previous trial congruency\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBoth tasks included\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReaction latencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 4.58, p=.04, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;286.98, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.76\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;60.79, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.41\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;20.65, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 1.98, p=.16, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;790.18, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;10.95, p=.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eError proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;9.84, p=.002, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;128.42, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;103.71, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;12.92, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;7.50, p=.007, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;197.46, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;4.34, p=.04, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReaction latencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;193.28, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.68\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;17.62, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"3\" nameend=\"c7\" namest=\"c6\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;414.90, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eError proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;59.05, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;37.61, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;166.97, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpatial\u003c/p\u003e \u003cp\u003eStroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReaction latencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;214.39, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;57.00, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;866.01, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.91\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eError proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;148.79, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.63\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;95.57, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.52\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;167.13, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e--- Insert Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e about here ---\u003c/p\u003e \u003cp\u003eAn ANOVA on RT including both cognitive tasks (Simon task and Spatial Stroop task) indicated that RT were shorter in the Spatial Stroop task (M\u0026thinsp;=\u0026thinsp;490 ms, SD\u0026thinsp;=\u0026thinsp;60) than the Simon task (M\u0026thinsp;=\u0026thinsp;501 ms, SD\u0026thinsp;=\u0026thinsp;68; F(1, 89)\u0026thinsp;=\u0026thinsp;4.58, MSE\u0026thinsp;=\u0026thinsp;4503.04, p=.04, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.05, BF\u0026thinsp;=\u0026thinsp;1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97%). On congruent trials, RTs (M\u0026thinsp;=\u0026thinsp;480 ms, SD\u0026thinsp;=\u0026thinsp;63) were shorter than incongruent RTs (M\u0026thinsp;=\u0026thinsp;511 ms, SD\u0026thinsp;=\u0026thinsp;61; F(1, 89)\u0026thinsp;=\u0026thinsp;286.98, MSE\u0026thinsp;=\u0026thinsp;606.84, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.76, BF\u0026thinsp;=\u0026thinsp;8.30 \u0026times; 10\u003csup\u003e25\u003c/sup\u003e \u0026plusmn;1.18%). Further, a main effect of previous trial congruency was observed (F(1, 89)\u0026thinsp;=\u0026thinsp;60.79, MSE\u0026thinsp;=\u0026thinsp;108.35, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.41, BF\u0026thinsp;=\u0026thinsp;526898546\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01%) with faster responses following a previously congruent trial (M\u0026thinsp;=\u0026thinsp;492 ms, SD\u0026thinsp;=\u0026thinsp;67) than an incongruent trial (M\u0026thinsp;=\u0026thinsp;498, SD\u0026thinsp;=\u0026thinsp;60), which, however, was qualified by an interaction between previous trial congruency and current trial congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;790.18, MSE\u0026thinsp;=\u0026thinsp;324.80, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.90, BF\u0026thinsp;=\u0026thinsp;4.74 \u0026times; 10\u003csup\u003e74\u003c/sup\u003e \u0026plusmn;2.22%). When the previous trial was congruent, then RTs in congruent trials were shorter than in incongruent trials, resulting in a congruency effect of 69 ms, t(89)\u0026thinsp;=\u0026thinsp;30.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;3.19, but when the previous trial was incongruent, then RTs in congruent trials were longer relative to RT on incongruent trials, resulting in a \u0026ldquo;reversed\u0026rdquo; congruency effect of 7 ms (t(89)\u0026thinsp;=\u0026thinsp;2.93, p\u0026thinsp;=\u0026thinsp;0.004, dz\u0026thinsp;=\u0026thinsp;0.31). We also observed an interaction between cognitive task and congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;20.65, MSE\u0026thinsp;=\u0026thinsp;260.74, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.19), which indicated a greater overall congruency effect in the Spatial Stroop task (M\u0026thinsp;=\u0026thinsp;36 ms; t(89)\u0026thinsp;=\u0026thinsp;14.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;1.54) compared to the Simon task (M\u0026thinsp;=\u0026thinsp;26 ms; t(89)\u0026thinsp;=\u0026thinsp;13.90, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;1.47). However, a Bayesian model comparison provided no evidence for a condition by congruency interaction (BF\u0026thinsp;=\u0026thinsp;0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43%), indicating that the data were slightly more likely under the model without the interaction.\u003c/p\u003e \u003cp\u003eFinally, a three-way interaction between cognitive task, congruency and previous-trial congruency indicated, that the congruency sequence effect described above differed between the two cognitive tasks (F(1, 89)\u0026thinsp;=\u0026thinsp;10.95, MSE\u0026thinsp;=\u0026thinsp;112.54, p=.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.11, BF\u0026thinsp;=\u0026thinsp;8.74 \u0026times; 10\u003csup\u003e49\u003c/sup\u003e \u0026plusmn;3.82%).\u003c/p\u003e \u003cp\u003eBoth the Simon task and the Spatial Stroop demonstrated individual main effects of congruency and previous congruency as well as an interaction between both factors (statistic effects for each task are reported in the supplementary materials and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the Simon task, when the previous trial was congruent, then a Simon effect of 61 ms was observed (t(89)\u0026thinsp;=\u0026thinsp;25.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;2.74) but when the previous trial was incongruent, then a \u0026ldquo;reversed\u0026rdquo; Simon effect of 10 ms (incongruent trials resulted in shorter RTs than congruent trials) occurred (t(89)\u0026thinsp;=\u0026thinsp;3.53, p\u0026thinsp;=\u0026thinsp;0.0007, dz\u0026thinsp;=\u0026thinsp;0.37). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea shows the reaction times for the Simon task. In the Spatial Stroop task, when the previous trial was congruent, then a Spatial Stroop effect of 77 ms was observed (t(89)\u0026thinsp;=\u0026thinsp;25.78, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;2.72) but, in contrast to the Simon task, when the previous trial was incongruent, then no difference was observed between congruent and incongruent trials (M=-3 ms; t(89)\u0026thinsp;=\u0026thinsp;1.40, p\u0026thinsp;=\u0026thinsp;0.16, dz\u0026thinsp;=\u0026thinsp;0.15). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea shows the reaction times for the Spatial Stroop task.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the anteroposterior force moment variability for both cognitive tasks as a function of congruency and time bin. M: mean, S: standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003etarget-aligned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCognitive conflict task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime bin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-150 to -75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-75 ms to target onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003etarget onset to 75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e75 to 150 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e150 to 225 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e225 to 300 ms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBoth tasks\u003c/p\u003e \u003cp\u003eIncluded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003eresponse-aligned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCognitive conflict task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime bin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-300 to -225 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-225 to -150 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e-150 to -75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e-75 ms to response onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eresponse onset to 75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e75 to 150 ms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBoth tasks\u003c/p\u003e \u003cp\u003eIncluded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe error proportions demonstrated lower error proportions in the Spatial Stroop task (M\u0026thinsp;=\u0026thinsp;3.0%, SD\u0026thinsp;=\u0026thinsp;3.8) compared to the Simon task (M\u0026thinsp;=\u0026thinsp;3.6%, SD\u0026thinsp;=\u0026thinsp;4.1; F(1, 89)\u0026thinsp;=\u0026thinsp;9.84, MSE\u0026thinsp;=\u0026thinsp;7.05, p=.002, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.10, BF\u0026thinsp;=\u0026thinsp;12.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97%). Additionally, we observed an effect of congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;128.42, MSE\u0026thinsp;=\u0026thinsp;11.27, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.59, BF\u0026thinsp;=\u0026thinsp;1.07 \u0026times; 10\u003csup\u003e16\u003c/sup\u003e \u0026plusmn;1%) with more errors in incongruent trials (M\u0026thinsp;=\u0026thinsp;4.7%, SD\u0026thinsp;=\u0026thinsp;4.5) compared to congruent trials (M\u0026thinsp;=\u0026thinsp;1.9%, SD\u0026thinsp;=\u0026thinsp;2.6) and an effect of previous trial congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;103.71, MSE\u0026thinsp;=\u0026thinsp;3.31, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.54, BF\u0026thinsp;=\u0026thinsp;2.50 \u0026times; 10\u003csup\u003e13\u003c/sup\u003e \u0026plusmn;0.99%) with higher error proportions (M\u0026thinsp;=\u0026thinsp;4.0%, SD\u0026thinsp;=\u0026thinsp;4.8) when the previous trial was congruent in contrast to when it was incongruent (M\u0026thinsp;=\u0026thinsp;2.6%, SD\u0026thinsp;=\u0026thinsp;2.7). An interaction between previous trial congruency and congruency was also found (F(1, 89)\u0026thinsp;=\u0026thinsp;197.46, MSE\u0026thinsp;=\u0026thinsp;10.73, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.69, BF\u0026thinsp;=\u0026thinsp;5.55 \u0026times; 10\u003csup\u003e36\u003c/sup\u003e \u0026plusmn;6.13%). When the previous trial was congruent, then error proportions in incongruent trials were higher than in congruent trials, resulting in a congruency effect of 6.3% (t(89)\u0026thinsp;=\u0026thinsp;14.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;1.49), but when the previous trial was incongruent, then error proportions in incongruent trials were even lower than in congruent trials, resulting in a \u0026ldquo;reversed\u0026rdquo; congruency effect of 0.6% (t(89)\u0026thinsp;=\u0026thinsp;2.74, p\u0026thinsp;=\u0026thinsp;0.007, dz\u0026thinsp;=\u0026thinsp;0.29), mirroring the RT data. An interaction between cognitive task and congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;12.92, MSE\u0026thinsp;=\u0026thinsp;3.72, p\u0026lt;.001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.13, BF\u0026thinsp;=\u0026thinsp;3.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.37%) indicated that in the Spatial Stroop task the congruency effect was greater (M\u0026thinsp;=\u0026thinsp;3.4%; t(89)\u0026thinsp;=\u0026thinsp;12.20, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;1.29) compared to the Simon task (M\u0026thinsp;=\u0026thinsp;2.1%; t(89)\u0026thinsp;=\u0026thinsp;7.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;0.81). The interaction between cognitive task and previous trial congruency was also significant but Bayes Factor analysis discounted the influence of the interaction (F(1, 89)\u0026thinsp;=\u0026thinsp;7.50, MSE\u0026thinsp;=\u0026thinsp;2.15, p = .007, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .08, BF\u0026thinsp;=\u0026thinsp;0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;3.52%).\u003c/p\u003e \u003cp\u003eAgain, like in the RT data, a three-way interaction between cognitive task, congruency and previous-trial congruency was also found. It indicated differences in the congruency sequence effect between the two cognitive tasks (F(1, 89)\u0026thinsp;=\u0026thinsp;4.34, MSE\u0026thinsp;=\u0026thinsp;2.01, p=.04, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e=.05, BF\u0026thinsp;=\u0026thinsp;3.11 \u0026times; 10\u003csup\u003e60\u003c/sup\u003e \u0026plusmn;8.18%). In the Simon task, when the previous trial was congruent, then error proportions in congruent trials were lower than in incongruent trials, resulting in a Simon effect of 5.9% (t(89)\u0026thinsp;=\u0026thinsp;12.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;1.28) but when the previous trial was incongruent, then, consistent with the RT data, error proportions on congruent trials were even higher than on incongruent trials, resulting in a \u0026ldquo;reversed\u0026rdquo; Simon effect of 1.3% (t(89)\u0026thinsp;=\u0026thinsp;4.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;0.45). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb shows the error proportions for the Simon task. In the Spatial Stroop task, when the previous trial was congruent, then error proportions in congruent trials were lower than in incongruent trials, resulting in a Spatial Stroop effect of 6.5% (t(89)\u0026thinsp;=\u0026thinsp;13.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, dz\u0026thinsp;=\u0026thinsp;1.46), but when the previous trial was incongruent, like for the RTs, then error proportions did not differ between congruent and incongruent trials (M\u0026thinsp;=\u0026thinsp;0.1%; t(89)\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;=\u0026thinsp;0.52, dz\u0026thinsp;=\u0026thinsp;0.07). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb shows the error proportions for the Spatial Stroop task.\u003c/p\u003e \u003cp\u003e--- Insert Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e about here ---\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis Of Force Moment Variability\u003c/h2\u003e \u003cp\u003eThe following description of statistical results concerns trials only, where the previous trial was congruent, because for these trials the effects of congruency are larger compared to for trials after incongruent trials. We analysed force moment variability separately in the AP and ML directions for both target-aligned and response-aligned times series. As will be reported below the effect of cognitive task was never significant and also did not interact with congruency and time bin, therefore, Individual analyses of balance performance for each of the two cognitive tasks can be found in the supplementary materials.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTarget-Aligned And Response-Aligned Time Series Analyses Of Congruency Effects In Both Cognitive Tasks\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e list the descriptive statistics of the target-aligned and response-aligned force moment variability for both cognitive tasks as well as the Simon task and the Spatial Stroop task and each congruency condition and time bin. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e contains the test statistics of the ANOVAs of the congruency effect for the target-aligned and response-aligned moment variability for both cognitive tasks combined and the individual tasks. The main effects of the two cognitive tasks, congruency and the progression across the time bins were assessed as within-subject factors of a repeated-measures analyses of variance (ANOVA).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the mediolateral force moment variability for both cognitive tasks as a function of congruency and time bin. M: mean, S: standard deviation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"20\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003etarget-aligned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCognitive conflict task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime bin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e-150 to -75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e-75 ms to target onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003etarget onset to 75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e75 to 150 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c18\" namest=\"c16\"\u003e \u003cp\u003e150 to 225 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e225 to 300 ms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBoth tasks included\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003eresponse-aligned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCognitive conflict task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime bin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-300 to -225 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e-225 to -150 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e-150 to -75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003e-75 ms to response onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c17\" namest=\"c15\"\u003e \u003cp\u003eresponse onset to 75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c20\" namest=\"c18\"\u003e \u003cp\u003e75 to 150 ms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBoth tasks included\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCongruency effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e-0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTest statistics of ANOVAs of the congruency effect for the moment variability in each temporal bin (target-aligned and response-aligned) for the both cognitive tasks in both directions of body sway. Significant effects or interactions are indicated in bold.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c9\" namest=\"c4\"\u003e \u003cp\u003eF, p, partial eta^2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTemporal bin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-150 to -75 ms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-75 ms to target onset\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003etarget onset to 75 ms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75 to 150 ms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e150 to 225 ms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e225 to 300 ms\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eTarget-aligned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBoth cognitive tasks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnteroposterior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89) = 0.50, p = .48, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89) = 0.29, p = .59, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89) = 0.32, p = .57, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89) = 0.14, p = .71, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89) = 0.05, p = .82, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89) = 0.48, p = .49, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMediolateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89) = 0.69, p = .41, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 5.24, p = .02, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 5.47, p = .02, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89) = 0.17, p = .679, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89) = 0.20, p = .656, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89) = 0.62, p = .435, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnteroposterior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 0.51, p=.48, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89)= 0.08, p=.77, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89)= 0.26, p=.61, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 0.46, p=.50, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 0.12, p=.73, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.58, p=.45, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMediolateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 1.21, p=.27, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 5.31, p=.02, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 7.68, p=.007, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 0.06, p=.81, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 0.05, p=.82, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.44, p=.51, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnteroposterior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 2.98, p=.09, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89)= 1.00, p=.32, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89)= 0.07, p=.79, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 1.45, p=.23, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 0.44, p=.51, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.03, p=.87, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMediolateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 0.05, p=.83, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89)= 1.01, p=.32, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89)= 0.17, p=.68, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 0.99, p=.32, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 0.09, p=.76, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.12, p=.73, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTemporal bin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-300 to -225 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-225 to -150 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-150 to -75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-75 ms to response onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eresponse onset to 75 ms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e75 to 150 ms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eResponse-aligned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBoth cognitive tasks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnteroposterior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 6.28, p = .01, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89) = 2.72, p = .10, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e = .03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89) = 0.46, p = .50, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 5.54, p = .021, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 7.04, p = .009, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89) = 0.73, p = .395, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u0026lt; .01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMediolateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 7.72, p = .007, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 10.85, p = .001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 14.68, p \u0026lt; .001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89) = 14.30, p \u0026lt; .001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= .14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89) = 3.12, p = .08, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89) = 1.63, p = .20, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e = .02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSimon task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnteroposterior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 2.60, p=.11, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89)= 1.57, p=.21, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89)= 0.08, p=.79, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 2.39, p=.13, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 6.91, p=.01, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.07 *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 2.90, p=.09, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMediolateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 2.42, p=.12, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 6.28, p=.014, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 9.96, p=.002, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 5.00, p=.03, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 1.65, p=.20, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.80, p=.37, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpatial Stroop task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnteroposterior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF(1, 89)= 2.50, p=.12, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF(1, 89)= 0.82, p=.37, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF(1, 89)= 0.54, p=.46, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(1, 89)= 3.86, p=.05, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 0.88, p=.35, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.56, p=.46, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMediolateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 7.14, p=.009, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 4.72, p=.03, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)= 6.93, p=.01, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eF(1, 89)\u0026thinsp;=\u0026thinsp;11.97, p\u0026lt;.001, ƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e=.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF(1, 89)= 1.77, p=.19, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e=.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF(1, 89)= 0.80, p=.37, \u003cb\u003eƞ\u003c/b\u003e\u003csub\u003e\u003cb\u003ep\u003c/b\u003e\u003c/sub\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u0026lt;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor the target-aligned AP force moment time series, a change across the six time bins was observed (F(2.94, 261.79)\u0026thinsp;=\u0026thinsp;71.42, MSE\u0026thinsp;=\u0026thinsp;0.0067, p \u0026lt; .001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .45, BF\u0026thinsp;=\u0026thinsp;1.56 \u0026times; 10\u003csup\u003e51\u003c/sup\u003e \u0026plusmn;0.59%; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) only. This was caused by a general reduction in moment variability, independent of congruency, that became observable in the time bin from 150 ms to 225 ms after target onset (M\u003csub\u003e1\u003c/sub\u003e = -2.33, SD\u003csub\u003e1\u003c/sub\u003e 0.51; M\u003csub\u003e2\u003c/sub\u003e =-2.32, SD\u003csub\u003e2\u003c/sub\u003e 0.52; M\u003csub\u003e3\u003c/sub\u003e = -2.32, SD\u003csub\u003e3\u003c/sub\u003e 0.52; M\u003csub\u003e4\u003c/sub\u003e = -2.33, SD\u003csub\u003e4\u003c/sub\u003e 0.52; M\u003csub\u003e5\u003c/sub\u003e = -2.35, SD\u003csub\u003e5\u003c/sub\u003e 0.52; M\u003csub\u003e6\u003c/sub\u003e =-2.39, SD\u003csub\u003e6\u003c/sub\u003e 0.51). A similar change across time bins was also seen in the ML direction (F(2.85, 254.02)\u0026thinsp;=\u0026thinsp;98.61, MSE\u0026thinsp;=\u0026thinsp;0.0085, p \u0026lt; .001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .53, BF\u0026thinsp;=\u0026thinsp;1.17 \u0026times; 10\u003csup\u003e66\u003c/sup\u003e \u0026plusmn;1.85%) but with an earlier start of reduction observable at the time bin from target onset to 75 ms after (M\u003csub\u003e1\u003c/sub\u003e= -2.59, SD\u003csub\u003e1\u003c/sub\u003e 0.52; M\u003csub\u003e2\u003c/sub\u003e= -2.59, SD\u003csub\u003e2\u003c/sub\u003e 0.54; M\u003csub\u003e3\u003c/sub\u003e=-2.61, SD\u003csub\u003e3\u003c/sub\u003e 0.53; M\u003csub\u003e4\u003c/sub\u003e= -2.62, SD\u003csub\u003e4\u003c/sub\u003e 0.53; M\u003csub\u003e5\u003c/sub\u003e= -2.65, SD\u003csub\u003e5\u003c/sub\u003e 0.53; M\u003csub\u003e6\u003c/sub\u003e= -2.68, SD\u003csub\u003e6\u003c/sub\u003e 0.50). In addition, an interaction between change across time bins and the congruency condition occurred (F(3.47, 308.88)\u0026thinsp;=\u0026thinsp;2.58, MSE\u0026thinsp;=\u0026thinsp;0.0044, p = .045, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .03). Although the frequentist ANOVA suggested a significant interaction, the Bayes Factor analysis provided extreme evidence in favour of the main-effects-only model excluding the interaction (BF\u0026thinsp;=\u0026thinsp;0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95%). The time bins from 75 ms before to target onset (F(1, 89)\u0026thinsp;=\u0026thinsp;5.24, MSE\u0026thinsp;=\u0026thinsp;0.0035, p = .024, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .06, BF\u0026thinsp;=\u0026thinsp;1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93%) and from target onset to 75 ms after target onset (F(1, 89)\u0026thinsp;=\u0026thinsp;5.47, MSE\u0026thinsp;=\u0026thinsp;0.0035, p = .022, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .06; BF\u0026thinsp;=\u0026thinsp;1.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78%) demonstrated reduced moment variability in incongruent trials (M\u003csub\u003e2\u003c/sub\u003e=-2.60, SD\u003csub\u003e2\u003c/sub\u003e 0.53; M\u003csub\u003e3\u003c/sub\u003e=-2.62, SD\u003csub\u003e3\u003c/sub\u003e 0.53) compared to congruent trials (M\u003csub\u003e2\u003c/sub\u003e=-2.58, SD\u003csub\u003e2\u003c/sub\u003e 0.54; M\u003csub\u003e3\u003c/sub\u003e=-2.60, SD\u003csub\u003e3\u003c/sub\u003e 0.54; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The reason for this observation lies in an effect pattern demonstrated by the Simon task alone and is presented in more detail in the supplementary materials.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the response-aligned force moment time series, AP moment variability demonstrated significant main effects for congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;6.07, MSE\u0026thinsp;=\u0026thinsp;0.0149, p = .016, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .06, BF\u0026thinsp;=\u0026thinsp;2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.43%) and change across time bins (F(2.31, 205.65)\u0026thinsp;=\u0026thinsp;11.85, MSE\u0026thinsp;=\u0026thinsp;0.0148, p \u0026lt; .001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .12, BF\u0026thinsp;=\u0026thinsp;87431211\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39%; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) only, but no interaction between both factors. Moment variability was lower in incongruent trials (M= -2.38, SD 0.49) than congruent trials (M=-2.37, SD 0.50). Across the time bins, moment variability reduced until the time bin from 75 ms to response onset and then began to rise again (M\u003csub\u003e1\u003c/sub\u003e=-2.37, SD\u003csub\u003e1\u003c/sub\u003e 0.51; M\u003csub\u003e2\u003c/sub\u003e=-2.37, SD\u003csub\u003e2\u003c/sub\u003e 0.51; M\u003csub\u003e3\u003c/sub\u003e=-2.39, SD\u003csub\u003e3\u003c/sub\u003e 0.50; M\u003csub\u003e4\u003c/sub\u003e=-2.39, SD\u003csub\u003e4\u003c/sub\u003e 0.49; M\u003csub\u003e5\u003c/sub\u003e=-2.36, SD\u003csub\u003e5\u003c/sub\u003e 0.49; M\u003csub\u003e6\u003c/sub\u003e=-2.36, SD\u003csub\u003e6\u003c/sub\u003e 0.49). The cognitive task had no specific influence on moment variability or its time course.\u003c/p\u003e \u003cp\u003eFor the ML moment variability when aligned to response-onset, significant main effects were observed for congruency (F(1, 89)\u0026thinsp;=\u0026thinsp;11.98, MSE\u0026thinsp;=\u0026thinsp;0.0280, p \u0026lt; .001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .12, BF\u0026thinsp;=\u0026thinsp;30.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54%) and time bins (F(2.22, 197.56)\u0026thinsp;=\u0026thinsp;14.47, MSE\u0026thinsp;=\u0026thinsp;0.0164, p \u0026lt; .001, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .14, BF\u0026thinsp;=\u0026thinsp;17664113019\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46%), in addition to an interaction between both factors (F(3.63, 322.98)\u0026thinsp;=\u0026thinsp;2.63, MSE\u0026thinsp;=\u0026thinsp;0.0042, p = .040, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e = .03; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Bayes Factor analysis, however, did not calculate a statistical model that includes the interaction as more likely than a model with both main effects only (BF\u0026thinsp;=\u0026thinsp;0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.33%). Moment variability was lower in incongruent trials (M=-2.70, SD 0.49) than congruent trials (M=-2.67, SD 0.50). Across the time bins, moment variability reduced until the time bin from 75 ms to response onset and then began to rise again (M\u003csub\u003e1\u003c/sub\u003e=-2.66, SD\u003csub\u003e1\u003c/sub\u003e 0.504; M\u003csub\u003e2\u003c/sub\u003e=-2.68, SD\u003csub\u003e2\u003c/sub\u003e 0.513; M\u003csub\u003e3\u003c/sub\u003e=-2.71, SD\u003csub\u003e3\u003c/sub\u003e 0.50; M\u003csub\u003e4\u003c/sub\u003e=-2.71, SD\u003csub\u003e4\u003c/sub\u003e 0.490; M\u003csub\u003e5\u003c/sub\u003e=-2.69, SD\u003csub\u003e5\u003c/sub\u003e 0.492; M\u003csub\u003e6\u003c/sub\u003e=-2.68, SD\u003csub\u003e6\u003c/sub\u003e 0.466). The interaction between congruency and time bins resulted from only the four time bins before response-onset showing reduced moment variability in incongruent trials (M\u003csub\u003e1\u003c/sub\u003e= -2.68, SD\u003csub\u003e1\u003c/sub\u003e 0.499; M\u003csub\u003e2\u003c/sub\u003e= -2.69, SD\u003csub\u003e2\u003c/sub\u003e 0.506; M\u003csub\u003e3\u003c/sub\u003e=-2.73, SD\u003csub\u003e3\u003c/sub\u003e 0.498; M\u003csub\u003e4\u003c/sub\u003e= -2.72, SD\u003csub\u003e4\u003c/sub\u003e 0.480) compared to congruent trials (M\u003csub\u003e1\u003c/sub\u003e= -2.65, SD\u003csub\u003e1\u003c/sub\u003e 0.510; M\u003csub\u003e2\u003c/sub\u003e= -2.66, SD\u003csub\u003e2\u003c/sub\u003e 0.521; M\u003csub\u003e3\u003c/sub\u003e=-2.69, SD\u003csub\u003e3\u003c/sub\u003e 0.514; M\u003csub\u003e4\u003c/sub\u003e= -2.69, SD\u003csub\u003e4\u003c/sub\u003e 0.499; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). The cognitive task had no specific influence on moment variability or its time course as a three-way interaction between cognitive task, congruency and time bin was not observed (F(3.84, 341.76)\u0026thinsp;=\u0026thinsp;0.29, MSE\u0026thinsp;=\u0026thinsp;0.0033, p=.878, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026lt;.01, BF\u0026thinsp;=\u0026thinsp;4.18 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e \u0026plusmn;3.33%). Likewise, a comparison between both cognitive tasks regarding their maximum reduction of force moment variability during incongruent trials did not demonstrate a difference in their maximum congruency effect sizes (F(1, 89)\u0026thinsp;=\u0026thinsp;0.02, MSE\u0026thinsp;=\u0026thinsp;0.0101, p=.899, ƞ\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026lt;.01, BF\u0026thinsp;=\u0026thinsp;0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99%).\u003c/p\u003e \u003cp\u003e--- Insert Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e about here ---\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo elucidate the mechanisms behind interference between cognitive processes and the control of body balance, we pursued a novel event-related methodology, which indicated that engagement of cognitive control for the resolution of response selection conflict impacts on the concurrent control of body balance [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]. In the present study, we aimed to extend our previous observations regarding the permeation of response selection conflict in a cognitive task into the balance control domain. In a Simon task and a Spatial Stroop task, we found strong cognitive congruency effects in both tasks in combination with reduction in mediolateral force moment variability in incongruent compared to congruent trials. The time range in which congruency influenced moment variability before response onset (e.g. in terms of an earlier onset of a difference between congruent and incongruent trials in the Spatial Stroop task) did not differ qualitatively between the two cognitive tasks (no three-way interaction between cognitive task, congruency, and temporal bin).\u003c/p\u003e \u003cp\u003eThe Simon task analysis revealed strong sequential conflict adaptation effects, where the typical Simon effect was modulated noticeably by the previous trial's congruency. After congruent trials, participants showed the standard Simon effects (better performance in congruent compared to incongruent trials), but after incongruent trials, these effects disappeared and even reversed. This pattern demonstrates that experiencing response selection conflict on one trial improves performance and eliminates (and even slightly reverses) the typical impact of incongruency [for similar findings see e.g. 10] on the subsequent trial. The Spatial Stroop task showed sequential conflict adaptation effects like the Simon task. After congruent trials, participants displayed the typical Spatial Stroop effects, and after incongruent trials, these congruency effects were eliminated [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]. This demonstrates that both tasks show conflict adaptation whereby previously incongruent trials improved subsequent performance. Different mechanisms [e.g. cognitive control, 48, cognitive control and mulit-level learning, 49, affect regulation, 50, feature integration, 51, 52] have been discussed to account for this sequential modulation, yet a discussion on these mechanisms is beyond the scope of this study.\u003c/p\u003e \u003cp\u003eIn our previous study [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e] comparing incongruent and congruent Simon trials, we observed a reduced mediolateral force moment variability within a single time bin of 150 ms width before response onset in the response-aligned time series data. The previous experiment did not include a jittered duration between trials, so that it was possible that the effects we observed were influenced by the periodic predictability of the trial cycle. In the present study, we aimed to improve our temporal resolution by halving the width of the time bins to 75 ms, we increased the entire range of time bins from 300 ms before to 150 ms after response onset, and by including temporal jitter between trials we ensured that the onset of consecutive trials was very hard to predict. The strongest effect of congruency on moment variability, that is the greatest relative reduction in force moment variability in incongruent trials, was detected in the temporal range from 150 ms to 75 ms before response onset. This finding confirms our observations in the previous study and implies that shortly before response onset some critical cognitive process may interfere with balance control. It seems, however, that the relative timing of this interference phenomenon is subject to some variability as less strong effects occurred in the two neighbouring time bins too. Furthermore, it is conceivable that the cognitive process, which causes the interference, is active across this entire period of 3 consecutive time bins from 225 ms before response onset until the onset of a response, when moment variability was reduced in incongruent trials in the Simon task. Provided that balance control is subject to neuromuscular delays and the body’s inertia, the impact of any critical cognitive process may precede any effects observable in the force plate data.\u003c/p\u003e \u003cp\u003eBased on Kornblum’s taxonomy [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e], we expected an impact of congruency on response-aligned force moment variability for both the Simon and the Spatial Stroop task. Like in the Simon task, the Spatial Stroop task demonstrated no congruency effects for anteroposterior force moment variability. Also like in the Simon task, the response-aligned data revealed an impact of congruency with reduced mediolateral force moment variability but apparently for a slightly extended time period from 300 ms before response onset to response onset. Nevertheless, these observations indicate that despite the additional stimulus-stimulus conflict in the Spatial Stroop compared to the Simon task, the different dimensional overlap structure did not induce additional interference with balance control.\u003c/p\u003e \u003cp\u003eDescriptively, balance appears to vary with the type of cognitive task and, by extension, the nature or strength of cognitive conflict. As these differences are not statistically significant, however, any interpretation remains speculative and primarily serves to highlight avenues for more targeted investigation in future research. Similarly, an impact on target-aligned force moment variability was not observed in the Spatial Stroop task, which contrasts with the observations made in the Simon task discussed above. Based on these qualitative observations the possibility cannot be entirely excluded that the Spatial Stroop task may have induced a slight difference in the temporally structured modulation of balance control interference compared to the Simon task. As we did not find a three-way interaction between cognitive task, current trial congruency and time bin for the response-aligned analysis of mediolateral force moment variability, we can interpret any cognitive task-specific effects with caution only. It might be interesting to follow-up these indications with future research, also to corroborate our current conclusion that S-S conflict resolution does not permeate balance control.\u003c/p\u003e \u003cp\u003e Both Simon and Spatial Stroop tasks demonstrated systematic modulation of force moment variability across the entire trial duration with a reduction in moment variability gradually emerging around target onset and the achievement of a relative minimum during response selection before onset of a response. This general dynamic might indicate tighter balance control when specific cognitive processing was required or at least expected. Koger et al. [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e] demonstrated similar general dynamics of moment variability across much longer trial periods in a setup comprising a cognitive dual-task. We believe that the global reduction of moment variability during a trial compared to the leading (and following) intertrial interval is an expression of strategically timed, proactive balance control in anticipation of impending cognitive demands. Thus, in the present study, we can hypothesize that two distinct components modulate moment variability. A global reduction during a cognitive trial irrespective of the congruency condition, and a local reduction during response selection, when conflict resolution is necessary for a correct response.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGeneral Role Of Inhibition In Balance Control\u003c/h2\u003e \u003cp\u003eBalance control requires the selection of appropriate sensory cues (e.g. vestibular, visual, somatosensory, or proprioceptive) and down-weighting or suppressing of misleading inputs. These processes might mirror the role of cognitive control in dealing with task-irrelevant or conflicting information. The fusion of multisensory feedback into an integrated state estimate of self-motion is the prerequisite of stable body balance [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e]. Cognitive control processes play an important role in maintaining balance under challenging sensory conditions [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. When sensory feedback becomes unreliable or when sensory conflict occurs, for example in situations in which visual feedback and/or proprioception do provide accurate information about the state orientation, the stabilization of balance seems to involve cognitive processes for the selection of relevant, still informative sensory cues (e.g. vestibular sensation) and the suppression of those noninformative, misleading sensory cues [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. An association between performance in a Spatial Stroop task and body sway also suggested that the ability to resolve cognitive conflict underlies more effective sensory disambiguation [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGawthrop et al. [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e] advanced current balance control theory further and suggested that continuously updated state estimates alone are insufficient for explaining the dynamics of body balance. According to their model, human balance control resembles an event-driven intermittent predictive control system, in which short-term predictive control is extended by a mechanism that corrects prediction errors through threshold-based state resets. When a predicted hold-state, which is a body balance state estimate kept active in memory, diverges from an observed-state based on multisensory fusion beyond a defined threshold, then the system triggers a reset that re-initializes the generalized hold-state. This process combines continuous open-loop prediction with intermittent error monitoring and closed-loop state updating [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eJohannsen et al. [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e] surmised that the local reduction in force moment variability within 150 ms before response onset was potentially caused by inhibitory suppression or delay of individual balance adjustments that occurred close in time to the resolution of cognitive conflict in the respective cognitive task. It may be the case that the resolution of conflict between a target’s stimulus-response mappings and the currently active task representation activates processes that are involved in the detection of conflicts between observed and hold-state and its updating. As an explanation of the observed reduction in moment variability, we suggested the existence of a “micro-bottleneck” similar to the central bottleneck model [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]: cognitive processes for response selection or conflict monitoring and resolution [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e] cannot be deployed simultaneously to processes of balance control. At least when they are engaged in disambiguation of intersensory conflict or the resolution of conflict between state estimates. In this sense, our point of view is compatible with the adaptive multiple resource time-sharing theory [\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e], which assumes that adjusting the time scale for balance adjustments directly affects the time available for a cognitive task and vice versa.\u003c/p\u003e \u003cp\u003eThe notion that cognitive control engagement may inhibit, suppress, or delay activity of balance control can also be explained through neurocognitive mechanisms, such as inhibition and gating [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e]. When cognitive control is strongly engaged by conflict monitoring or response inhibition [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e], the ongoing sensorimotor balance control loop may be actively suppressed or downregulated to prevent lower-level balance control activity from interfering or distracting higher level cognitive control. For instance, the transient reduction of the sensorimotor gain of corrective balance adjustments per se could have two parallel effects, such as reduced moment variability [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e] as well as less frequent bottom-up calls for high-level involvement. More specifically, when the balance system detects instability, sensorimotor networks may generate signals that demand attention. Over a short period of time, this strategy might not result in noticeable balance instability that would require high-level intervention like over longer durations. Therefore, central mechanisms may try to suppress the intrusion of these sensorimotor signals to shield a cognitive task [\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e]. Thus, when cognitive control is activated, the activation of competing sensorimotor representations may be downregulated or suppressed to facilitate the cognitive task set.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDirection-specificity of Interference Effects\u003c/h2\u003e \u003cp\u003eA noticeable observation in our previous [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e] and in our present study is that the effect of incongruency was far stronger in the mediolateral than the anteroposterior direction. Again, we observed a correspondence between the mediolateral direction in which manual response decisions had to be performed and the mediolateral direction of body balance control where the observed congruency effects predominated. Thus, the effect of cognitive interference on balance adjustments in multitasking situations may not only be sensitive to the involvement of any specific cognitive processes, such as the suppression of task-irrelevant target features, but may also be direction-specific based on a task-specific, egocentric frame of reference.\u003c/p\u003e \u003cp\u003eIt has been argued that the balance control system can independently adapt and respond to challenges in different directional planes through control mechanisms that decouple ML and AP balance control via direction-specific muscle synergies [\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e]. In addition to the evidence that body balance control in the mediolateral and anteroposterior planes can be dissociated, Scholz and Schöner [\u003cspan class=\"CitationRef\"\u003e69\u003c/span\u003e] suggested that the motor system strategically organizes movement variability into two subspaces due to motor system redundancy: it minimizes task-relevant variability that directly affects performance outcomes while it allows or even exploits task-redundant motor variability that does not compromise the task goal. This implies that the balance control system selectively channels variability by tightly constraining joint movements that could destabilize the CoM while permitting compensatory variations across joints that maintain balance [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e] so that structured flexibility and adaptability is enabled through redundant multisegmental joint configurations [\u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTransient suppression or reduction of variability in directions that threaten the stability of a task-relevant variable is selectively applied at critical task phases [\u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e]. Possible mechanisms for stricter balance control by means of the reduction of variance could involve increased muscle co-contractions to stiffen joints, alterations in neural feedback control gains, or damping of exploratory behaviour, that are only applied when boundary conditions are approached, constraints encountered, or critical events detected. The integrated control of body balance alongside a secondary task performed while standing, such as tracking moving targets, manipulating objects, reaching, or balancing items, introduce additional, ‘suprapostural’ cognitive performance demands that need to be coordinated with the fundamental requirement of maintaining stable posture. The interference observed between the cognitive task domain and balance control observed in these multitasking contexts has been debated as an indication of a facilitatory role of balance control or adaptive time-sharing of a central capacity [\u003cspan class=\"CitationRef\"\u003e73\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e]. In a multitasking situation, where some kind of precision behaviour in the suprapostural task is required, decomposition of joint variability into performance-relevant components and non-relevant components becomes more complex. The assumption is that adaptive motor solutions are produced by the reduction of variability that affects the motion performance across repetitions. To achieve this, the balance control system might exhibit flexible task prioritization by allowing increased (or unaltered) variability in postural degrees of freedom that do not compromise suprapostural performance, while variability on the critical orthogonal direction is reduced. In our present study, both cognitive tasks did not involve explicit precision demands, but minimized retinal slip at the time of target onset in the mediolateral direction might have been implicitly beneficial. In follow-up experiment, we are currently testing if the direction-selective reduction in moment variability is dependent on an egocentric frame of reference that is imposed by the demands of the cognitive task.\u003c/p\u003e \u003c/div\u003e "},{"header":"Summary And Conclusion","content":"\u003cp\u003eOur study investigated how cognitive conflict tasks interfere with balance control using an event-related methodology, successfully replicating and extending previous findings [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e] that response selection conflict systematically affects balance control. We examined two conflict paradigms, the Simon task and Spatial Stroop task, while participants maintained upright standing posture. Both tasks produced strong congruency effects alongside reduced mediolateral force moment variability during incongruent compared to congruent trials, confirming that balance adjustments are systematically affected by conflict resolution demands. Both tasks reduced mediolateral postural variability during incongruent trials.\u003c/p\u003e\u003cp\u003eTaken together, these findings demonstrate that cognitive conflict consistently permeates into the domain of balance control, manifesting as lower force moment variability during conflict resolution. The effects are temporally discrete and occur only during the very brief period of conflict resolution and can only be detected using a temporally high-resolution event-related analysis. This study provides robust evidence that different types of cognitive conflict engage balance control systems through partially different pathways, with the Spatial Stroop task producing more extensive, robust, and temporally structured interference compared to the Simon task's diffuse and transient patterns. This indicates that while conflict resolution transiently competes with balance control, the underlying cognitive-balance interactions are shaped by task-specific mechanisms.\u003c/p\u003e\u003cp\u003eFrom a theoretical perspective, the results align with predictive models of balance control and theories of intermittent, event-driven postural adjustment systems, which suggest that discrete corrective actions are triggered only when stability estimates fall below critical thresholds. The observed reduction in adjustment rates during conflict trials reflects a temporary suppression or postponement of balance adjustments while cognitive resources are recruited for conflict resolution. This supports the notion that shared cognitive-motor resources operate through temporally specific mechanisms and demonstrates that the interaction between cognition and balance control is intermittent and event-driven, with balance control being adaptively constrained during periods in which higher cognitive demand is present. This provides new insights into the dynamic interplay between cognitive control and the stability of body balance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll extracted data files are available from the figshare database (https://doi.org/10.6084/m9.figshare.31305772).\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe wish to thank Wiebke Janesch and Frida Schulz for their contributions to data collection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eL.J., A.K., I.K., H.M designed and planned the study. L.J. and E.S. supervised data collection. L.J. processed the data and performed the data analysis. L.J., An.Ko., E.S., D.N.S., A.K., I.K., H.M. prepared the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interest statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was supported by funding from the German Research Foundation (DFG; project number: 517439747).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWinter, D. A. Human balance and posture control during standing and walking. \u003cem\u003eGait Posture\u003c/em\u003e. \u003cb\u003e3\u003c/b\u003e (4), 193\u0026ndash;214 (1995).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNashner, L. M. 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Sci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (1), 1\u0026ndash;20 (2004).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"balance control, cognitive conflict resolution, cognitive-motor interference, Simon task, Spatial Stroop task","lastPublishedDoi":"10.21203/rs.3.rs-8884917/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8884917/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe scientific understanding of any interaction between cognition and balance control is advanced by methods that capture event-related effects of cognitive processes on balance with high temporal resolution and precision. We developed such an approach to examine how cognitive conflict interferes with the control of body balance during upright standing. Participants stood on a force plate while performing two cognitive conflict paradigms: a Simon task, which induces spatial stimulus\u0026ndash;response conflict during response selection, and a Spatial Stroop task, which elicits an additional stimulus\u0026ndash;stimulus conflict during stimulus encoding. By aligning force plate time series data to the onset events of target and response across all trials, we assessed the temporal dynamics of spatial congruency effects on force moment variability as a marker of balance control activity. Across both experimental cognitive tasks, incongruent trials produced strong congruency effects in cognitive task performance and systematically caused transient reductions in force moment variability along the mediolateral axis in balance control. These observations suggest that the recruitment of cognitive processes for conflict resolution temporarily inhibits, suppresses, or postpones balance adjustments. Importantly, regarding the impact of cognitive interference on body balance, we confirm our previous observations using improved methods and demonstrate that reduction in balance control activity during resolution of cognitive conflict generalizes to a task with multiple conflict loci (Spatial Stroop task). However, this extended range of conflict does not result in correspondingly stronger interference effects in balance control. These findings suggest that conflict-related demands in cognitive control robustly permeate into balance control. From a theoretical perspective, the results align with predictive models of postural regulation and intermittent, event-driven accounts of balance control.\u003c/p\u003e","manuscriptTitle":"Contrasting cognitive control in the Simon and spatial Stroop tasks regarding their interference with the control of standing balance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 16:58:04","doi":"10.21203/rs.3.rs-8884917/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-03T06:29:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-01T14:38:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T13:29:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314037043994259399240514527107502000043","date":"2026-03-10T10:57:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293926253060148021497515666311528662606","date":"2026-03-09T10:51:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122580754004928254944584273092772579276","date":"2026-03-04T07:54:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-02T12:27:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-21T02:51:38+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-19T20:41:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-17T10:11:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-17T10:06:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8dc46766-8f39-4178-b2aa-e43de6451d62","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63947715,"name":"Biological sciences/Neuroscience"},{"id":63947716,"name":"Biological sciences/Psychology"},{"id":63947717,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-05-13T08:15:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 16:58:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8884917","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8884917","identity":"rs-8884917","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}