Face expectancy cues differentially modulate conflict processing driven by emotional incongruence: An EEG study

Face expectancy cues differentially modulate conflict processing driven by emotional incongruence: An EEG study | 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 Face expectancy cues differentially modulate conflict processing driven by emotional incongruence: An EEG study Maria Coelho, Daniel Agostinho, Teresa Sousa, Gabriel Pires, Miguel Castelo-Branco This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7440652/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Adaptive behavior in social interactions requires the effective processing of conflicting emotional information. The impact of expectancy on conflict processing remains a relevant research question. Here we investigated the influence of primed expectancy on conflict processing. To achieve this goal, we used the Emotional Stroop paradigm and variants where expectancy was introduced using facial expression or emotional letter labels. Neurophysiological and behavioral data were collected from 20 healthy participants who completed these three conditions (in the presence or absence of prior expectancy cues). We first replicated previous findings by showing higher amplitudes of N400 and Conflict Slow Potential for the incongruent trials during the classical Emotional Stroop condition. When expectancy was introduced, we found a significant effect on conflict processing, with a striking difference between face and letter emotion cues. Parietal alpha and beta power decreases occurred specifically for face expectancy cues, which were attenuated by conflict processing. These findings suggest that attentional resources are differently prioritized by face versus letter emotion expectancy cues, with an impact on performance, with face-driven expectancy generating distinctive neurophysiological patterns and facilitating subsequent conflict resolution. Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology conflict processing emotional processing event-related potentials expectancy. Word count: 4044 words excluding figure legends and references Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Expectancy effect of Emotional Conflict Processing Conflict processing refers to cognitive mechanisms involved in detecting and resolving inconsistent information [ 1 ]. Given its role in guiding adaptive learning and goal-directed behavior [ 2 ], incongruence processing is a critical facet of everyday conflict handling [ 3 ], [ 4 ]. While previous research has addressed the impact of affective and emotional processing on incongruence processing [ 3 ], [ 5 ], [ 6 ], the role of expectation, which is typically present in socioemotional interactions [ 7 ] remains to be understood. Investigating how expectancy cueing can modulate incongruence processing offers a new window into improved understanding of conflict processing itself. Here, we thus seek to investigate the neural mechanisms underlying the interplay between these processes. Neural Correlates of Emotional Conflict Processing Previous event-related potential (ERP) studies have addressed the distinct neurophysiological underpinnings of conflict processing in emotional contexts, such as the centroparietal N400 [ 8 ] (also often referred to as the N450 [ 9 ]), where more negative amplitudes are evident in incongruent stimuli than in congruent stimuli, and the conflict slow potential (CSP) [ 9 ] (also referred to as the Late Positive Component [ 10 ], or Sustained Potential [ 11 ]) shown from 500 ms onwards after stimulus onset, showing a divergence in amplitude between congruent and incongruent stimuli in centroparietal channels and linked to conscious processing. Whilst ERPs are often studied in this context, oscillatory markers have not been as much of a focus of study. Previous research has associated increased parietal alpha power with the suppression of task-irrelevant information, therefore optimizing attentional focus and aiding in conflict resolution [ 12 ]. Parietal beta power modulations have frequently been linked to top-down attentional control processes, with decreases in beta power reflecting the allocation of attentional resources during visual processing [ 13 ], [ 14 ]. Previous findings have also reported parietal beta power decreases during post-cue periods [ 15 ]. Van Wijk et al. (2009) found that beta power decreased significantly less when a cue contained no useful information about the subsequent action [ 16 ], suggesting that these modulations may also contribute to stimulus anticipation and expectancy creation. Expectancy can be introduced in an experimental design using stimulus onset asynchrony paradigms [ 17 ]. By manipulating stimulus anticipation over an extended period, it is possible to create an expectancy effect which modulates perceptual and attentive stimulus processing. Study Overview and Hypotheses We hypothesized that primed expectations, particularly face-driven expectations, have a differential impact on conflict resolution, and this was investigated by a variation of the Emotional Stroop task at both behavioral and neurophysiological levels. Accordingly, to investigate how expectations affect conflict processing in emotion recognition we assessed the effects of two distinct primed expectations - face-driven and letter label-driven – on conflict resolution, using an Emotional Stroop design. Emotional Stroop Paradigms offer a unique approach for studying how emotions may influence conflict resolution [ 3 ]. By employing facial expressions to elicit emotional recognition responses, relevant insights were provided on how emotions are processed in congruent and incongruent contexts [ 18 ]. We analyzed ERP components linked to conflict processing and resolution, namely the N400 and CSP. In addition, we investigated how expectancy influenced oscillatory activity, focusing on parietal beta and alpha modulations. These measures were used in the current study to index changes in perceptual mechanisms induced by expectancy and the integration of top-down attentional processes, respectively. We hypothesized that parietal beta activity would reflect changes in top-down attentional control, potentially facilitating conflict processing through enhanced anticipation. Conversely, parietal alpha activity might index shifts in visual processing mechanisms, modulating the allocation of attentional resources to optimize the perceptual processing of expected stimuli. By examining these neurophysiological patterns alongside behavioral components, we aim to provide a deeper understanding of how expectancy modulates conflict processing in socioemotional contexts involving face processing. 2. Methods 2.1. Participants Twenty healthy participants (9 females, 11 males) with a mean age of 24 years (standard deviation (SD) = 2.92) were recruited using snowball sampling. Participants were Portuguese adults, 18 years old or older, with normal or corrected vision. Exclusion criteria included individuals with a history of neurological, psychiatric, or neurodevelopmental disorders as well as those scoring below the cut-off normal standard deviation (within 1 SD of the mean) on the matrix reasoning (M = 23.3 ± 1.9) and vocabulary (M = 48.5 ± 7.1) subtests of the Portuguese version of the Wechsler Adult Intelligence Scale-III (WAIS-III) [ 19 ]. All participants provided written informed consent, and the study was approved by the Ethics Committee of the Faculty of Medicine of the University of Coimbra (reference number 001-CE-2021). This study followed the ethical guidelines of the Declaration of Helsinki to protect the rights and well-being of all participants. 2.2. Experimental design The experimental task employed a face-word Emotional Stroop paradigm implemented in MATLAB [ 20 ] using the Psychophysics Toolbox Version 3 (PTB-3) [ 21 ]. Our task involved the presentation of 6 facial expressions (3 male, 3 female) retrieved from the Radbound Faces Database [ 22 ] representing happiness or sadness (with visual angles of approximately 9.46° in width and 14.74° in height), with superimposed text labels (either "T" for "triste" or "F" for "feliz", meaning sad and happy, respectively, with visual angles of approximately 0.95° in width and 1.91° in height), positioned centrally between the eyes, that were congruent or incongruent with the expressed facial expression (Figs. 1 and 2 ) in a 24-inch screen (1920 x 1080 pixels, refresh rate = 60 Hz). The proportions of congruent and incongruent stimuli were balanced. Three conditions were tested to investigate the influence of the stimulus-primed expectancy. In the classical condition (CL), face and emotion labels appeared simultaneously. For the label-first condition (LF), the letter label appeared first, followed by the face, with the label overlapping the face. In the face-first condition (FF), the face appeared first, followed by face and label overlapping. Participants were instructed to identify whether a trial was congruent or incongruent by pressing the corresponding key (letter C or I on the keyboard). A short practice session was conducted before the main experiment to ensure that the participants understood the task completely. In the CL condition, each trial lasted 3 s, while in the LF and FF conditions, it was extended to 4 s to allow for the expectancy period. Regardless of the condition, every trial commenced with a red fixation cross (with visual angles of approximately 1.91° in width and in height) in a black background, lasting 1 s, to enhance participants’ attentional focus. The fixation cross was followed by the presentation of the congruent or incongruent conditions lasting for 1 s, which was preceded in LF and FF trials by expectancy creation (1-second long). Following the stimulus onset, a black screen appeared with a question indicating the key press option: "Congruent? "C"; Incongruent? "I". Participants were instructed to respond only after the question appeared to prevent motor artifacts from affecting the neurophysiological conflict-related signals. The experimental implementation was divided into eight runs, each lasting approximately 6 minutes, and consisted of 96 trials equally distributed across conditions. The total duration was approximately 2 hours, including cognitive assessment (20 min), EEG preparation (30 min), data acquisition (60 min). All participants performed the task in a standardized, quiet, and distraction-free environment to minimize potential confounding factors that could influence their results. The full task implementation can be found at ( https://github.com/Daniel-Agostinho/ESP ). 2.3. Data acquisition Data were collected at the Institute for Nuclear Sciences Applied to Health (ICNAS) in Coimbra. Participants were administered the WAIS-III [ 19 ] vocabulary and matrix subtests as inclusion criteria. Electroencephalographic (EEG) activity was recorded using an actiCHamp amplifier (Brain Products GmbH, Gilching, Germany). A 64-channel EEG cap was used, with Ag/AgCl active electrodes placed on the scalp (ActiCHamp Plus, Brain Products GmbH, Gilching, Germany). EEG electrodes were positioned according to the 10–20 international system, standardizing the electrode placement for scalp recording. Data were collected at a sampling rate of 1000 Hz. The reference electrode was placed at the left mastoid, while the vertical and horizontal electrooculogram (EOG) electrodes were placed above and below the left eye, as well as to the left of the left eye and to the right of the right eye. The EOG signal was recorded to identify visual artifacts and facilitate their removal. Impedances were kept below 10 kΩ to ensure adequate signal quality. Data were recorded using BrainVision recorder software [ 23 ]. 2.4. Behavioral data processing analyzes When a participant failed to respond, the response was recorded as missing and subsequently imputed using the mean of the participant's responses within the corresponding run. Hit rates were subsequently calculated per participant based on the percentage of congruent and incongruent correct responses. The percentages of correct responses for each of the three tested conditions (classical, face-first, and label-first conditions) were extracted and compared across conditions. 2.5. Neurophysiological processing and analyzes EEG signal preprocessing and analyses were performed using the EEGLAB (version 2023.0) toolbox [ 24 ] in MATLAB [ 20 ]. For offline preprocessing of EEG data, a pipeline was created with the necessary steps according to Makoto’s preprocessing guidelines [ 25 ]. First, the data were downsampled to a frequency of 500 Hz. A high-pass filter was then applied at 0.1 Hz and a low-pass filter was applied at 40 Hz. After these steps, noisy channels (channels with electrical interference or a very low signal-to-noise ratio) were identified by visual inspection and interpolated based on data from neighboring channels, and the data were re-referenced to their average to provide a clearer representation of the brain's electrical activity. Following this step, independent component analysis (ICA) was performed to remove eye and motor artifacts, electrode drift, or any abnormal pattern identified [ 24 ]. Finally, the data were segmented into epochs of interest, from − 2000 ms to 1000 ms for six conditions (the three main conditions divided by congruent and incongruent events), locked to the moment where the face and the label overlapped for every condition. 2.5.1. Event-Related Potentials – N400 and CSP All epochs were normalized by subtracting the common baseline moment, referring to the last 500 ms of the fixation cross (-500 ms to 0 ms for CL, and − 1500 ms to -1000 ms for LF and FF). At least 90 trials resulted per condition. The maximum peak amplitude was extracted per participant between 330 and 440 ms for the N400 analysis on a central channel cluster (C1, C2, Cz) [ 9 ], whereas the mean amplitude between 400 ms and 700 ms was extracted for CSP on the central channel cluster [ 26 ] and a parietal channel cluster (P1, P2, Pz) [ 11 ]. 2.5.2. Event-Related Spectral Perturbation Event-related Spectral Perturbation (ERSP) analysis was conducted in EEGLAB [ 24 ] to investigate neural oscillatory dynamics during the formation of primed expectancy and subsequent conflict processing. Frequency power variations over time were calculated using wavelet decomposition as the default spectral decomposition method. EEG data were analyzed for parietal channels from primed expectancy creation (-1000 ms to 0 ms) and for conflict resolution (from 0 ms to 700 ms), within a frequency range from 4 Hz to 40 Hz. Further frequency analyses focused on alpha and beta oscillations, given their role in the interplay between attentional and monitoring processes [ 27 ], [ 28 ]. The basal period for time-frequency analysis was defined as 500 ms after the fixation cross. To assess frequency power oscillations, the average power of alpha and beta was extracted for both primed expectancy creation and conflict processing periods. The topographic distribution of alpha at 10 Hz (± 1 Hz) and low beta at 14 Hz (± 1 Hz) were estimated for two key time windows: -600 ms to -400 ms (primed expectation creation) and 400–600 ms (conflict processing). 2.5.3. Source localization analyzes For source localization analysis, we utilized standardized low-resolution brain electromagnetic tomography (sLORETA) [ 29 ], [ 30 ]. In the sLORETA, the brain’s intracerebral volume was divided into 6239 voxels, each with a spatial resolution of 5 mm. The standardized current density for each voxel was then computed based on a realistic head model using the MNI152-T1 template. Supporting evidence from EEG/fMRI studies confirms the accuracy of source estimation using sLORETA [ 31 ], as well as studies providing reliable results without localization bias [ 32 ]. To compare voxel-based sLORETA images across experimental conditions, voxel-wise randomization tests with 5000 permutations were conducted using the built-in sLORETA statistical nonparametric mapping approach. Significant voxel differences ( p < 0.05), corrected for multiple comparisons (through permutation-based correction) between conditions were mapped onto the MNI brain. 2.6. Statistical analysis Descriptive analyses were performed to characterize the participants by sex, age, laterality index, and education. The effects experimental cueing conditions (CL, LF, and FF) and conflict (congruency and incongruence) and the possible interaction between them on the hit rate were analyzed through a two-way Repeated Measures ANOVA. Greenhouse-Geisser correction was applied to adjust the degrees of freedom in the repeated-measures ANOVA. Effect sizes were measured using partial eta squared. Subsequently, a trend analysis was performed through a linear regression to explore any systematic patterns across the levels of the independent variables, particularly in relation to how the hit rate changed across the conditions. N400 and CSP components identified in the central channel cluster for the conditions CL, LF, and FF were analyzed regarding their amplitude point-to-point difference between congruent and incongruent trials using paired samples t-tests. Effect sizes were measured using Cohen’s d. For further analyses, two-way repeated measures ANOVA was performed to explore the effect of expectancy conditions (LF and FF) and conflict (congruency and incongruence), as well as the interaction between them, on the amplitude of N400 and CSP. Effect sizes were measured with partial eta squared. The grand average amplitude peak of the CL for N400 (average peak evident at 414 ms) was extracted by participant and subsequently compared between congruent and incongruent trials For the statistical analysis of source-localized activity, voxel-wise comparisons were performed using sLORETA's built-in nonparametric randomization tests. Statistical significance was evaluated using a log of the F-ratio (lnF) for each voxel, comparing current density estimates between the experimental conditions. To control for multiple comparisons, the significance threshold was set at p < 0.05 and corrected using a permutation-based method. A total of 5000 permutations were performed to assess the differences between conditions. Significant voxels were mapped onto the 3D MNI152 template and the corresponding Brodmann areas were identified. 3. Results 3.1. Behavioral data Descriptive statistics for behavioral performance in each condition are presented in Table S1 in the supplementary material. No significant differences were found in the hit rate between conditions ( F (2) = 2.844, p = 0.0741, ηp² = 0.105), nor did the presence of conflict significantly influence the hit rates ( F (1) = 0.458, p = 0.507, ηp² = 0.024). Moreover, no interaction was found between the type of condition and congruence ( F (2) = 0.906, p = 0.413, ηp² = 0.046). Nevertheless, further trend analysis revealed a significant main condition-related effect. Specifically, the FF condition showed significantly higher hit rates (M = 97.30, SD = 3.25) than both the LF (M = 96.40, SD = 3.71) and CL conditions (M = 95.60, SD = 4.00) ( F (1) = 5.885, p = 0.017), with a moderate effect size (R² = 0.048) (Fig. 3 ). 3.2. Event-related potentials related to conflict processing We first asked the question whether the conflict-related evoked responses were present in the conditions where expectancy was introduced (LF and FF) in addition to the classical Emotional Stroop (CL). 3.2.1. N400 and CSP modulation by conflict resolution . Paired samples t-test results indicated significant differences in the Classical Condition, with a more negative amplitude for incongruent trials (-0.486 ± 1.339 µV) than for congruent trials (-0.272 ± 1.284 µV) ( t (19) = 2.638, p = 0.016, CI = [0.044, 0.383], d = 0.590). Concerning the CSP component, the mean amplitude of congruent trials was significantly higher than the mean amplitude of incongruent trials (0.530 ± 1.179 µV and 0.283 ± 1.299 µV, respectively) ( t (19) = 2.327, p = 0.031, CI = [0.025, 0.469], d = 0.520) (Fig. 4 ). Regarding the conditions where expectancy was inserted, no significant differences were found between congruent and incongruent trials for either the N400 or CSP component. 3.3. Primed expectancy effect: Attentional Mechanisms related to conflict processing Further analyses were conducted to understand how primed expectancy was processed and subsequently influenced conflict-processing resolution at parietal channels, given this region’s importance in top-down control in anticipation [ 33 ] and conflict resolution [ 13 ]. A Two-way Repeated Measures ANOVA was performed to analyze the effect of expectancy and congruency on the signal amplitude for both N400 and CSP. 3.3.1. N400 and CSP modulation by the interaction between expectancy and conflict resolution at parietal channels We found a significant impact of expectancy type on the CSP amplitude ( F (1, 19) = 10.418, p = 0.004, ηp² = 0.354). Moreover, we found a significant interaction between expectancy creation and congruency ( F (1, 19) = 6.287, p = 0.021, ηp² = 0.249). Post hoc comparisons based on paired t -test analysis revealed that in the LF condition, the congruent trials (4.190 µV) showed a higher CSP amplitude than the incongruent trials (3.929 µV) ( t (19) = 1.637, p = 0.059, CI = [-0.073, 0.595], d = 0.366), while the opposite was observed in the FF condition, where incongruent trials (3.562 µV) had a higher CSP amplitude than congruent trials (3.292 µV) ( t (19) = -1.72, p = 0.046, CI = [-0.590, 0.049], d = -0.396) (Fig. 5 ). 3.3.2. Parietal Alpha and Beta Modulations During Expectancy and Conflict Resolution Distinct patterns of neural oscillations were revealed during primed expectancy formation and conflict processing for conditions in which expectancy was manipulated, LF, and FF. Two periods were analyzed separately: primed expectancy formation from − 600 to -400 ms and conflict resolution from 400 to 600 ms. The power difference between the expectancy generation period and the conflict adaptation period was calculated for each condition using a paired sample t-test. Significant differences were found between the LF and FF conditions ( t (19) = -3.777, p < 0.001) (Fig. 6 ). Specifically, in the FF condition, an alpha and beta average power decrease was observed during the expectancy period (-1.817 dB) and conflict adaptation (-1.655 dB), leading to an overall power difference of -0.161 dB between the expectancy and conflict resolution periods. In contrast, in the LF condition, no alpha and beta power decreases were observed during the expectancy period (-0.906 dB), while a decrease in alpha and beta power was observed during the conflict processing period (-2.407 dB), leading to a power difference of -1.502 dB. Topographical maps separately illustrating the alpha and beta average power distributions during the expectation creation and conflict resolution periods further support these findings. During the conflict resolution period, significantly stronger alpha and beta power decreases were observed in the LF condition, when compared to the FF condition (Fig. 7 ). 3.3.3. Alpha and Low Beta Source localization Significant differences in conflict processing (400–600 ms after stimulus onset) were found between the FF and LF conditions in the low-beta frequency range (12–15 Hz), with significantly stronger decreases in low-beta power observed in the LF condition compared to the FF condition. These differences were localized to Brodmann area 7, specifically in the precuneus, within the Parietal Lobe. The threshold for the log of the F-ratio was − 0.671, with a significance level of p < 0.05. The MNI coordinates for this activation difference were X = -5, Y = -80, Z = 50 (Fig. 8 ). No significant differences in alpha and beta modulations were found between LF and FF in the expectancy period. 4. Discussion This study investigated the question whether the type of stimulus driven expectancy, using face versus non face cues, differentially influences conflict processing, in the context of emotion recognition. We hypothesized that expectancy would modulate conflict resolution, especially for face stimuli, owing to their unique processing priority in the brain [ 28 ], [ 34 ], [ 35 ]. Our findings provide evidence that primed expectancy differentially affects conflict-processing dynamics in a cue dependent manner, highlighting its role in modulating cognitive processes in tasks that involve emotional stimuli. We first aimed to replicate previously described conflict-related components, such as the N400[ 8 ], [ 9 ] and CSP[ 9 ] using an Emotional Stroop task [ 36 ], aligned with conflict monitoring theory [ 1 ]. We observed that when primed expectancy was introduced, this abolished both N400 and CSP in the central channels, showing that expectancy changes typical Stroop conflict patterns. Instead, we observed significant differences at the ERP in the parietal channels, a region often associated with attentional resources [ 37 ], and expectancy [ 28 ], [ 38 ]. Notably, early neural responses did not show significant differences, indicating that the initial stages of conflict detection may remain unaffected by expectancy, as proposed in theories suggesting that early conflict detection mechanisms are automatic and less susceptible to top-down modulation [ 39 ]. However, the significant effect of distinct forms of expectancy cues (faces versus letters) differently impacted the later parietal CSP component (400–700 ms), showing an expectancy effect on conflict processing linked to top-down attentional mechanisms and active conscious processing [ 9 ], [ 37 ], [ 40 ]. Time-frequency analysis further corroborated these findings by showing that parietal alpha and beta powers differed significantly based on the type of emotional expectancy cue created. In the face-first condition, a decrease in alpha and beta powers, linked to the active visual processing and recruitment of attentional resources, was observed during the expectancy generation period, followed by a relative power increase during the conflict resolution period, suggesting less attentional allocation during conflict resolution. Contrarily, in the label-first condition, no significant decrease in alpha and beta power was found in expectancy creation, while an accentuated power decrease was clear in conflict resolution, suggesting a heightened engagement of attentional resources mostly during conflict processing, possibly due to the less salient nature of label expectancy compared to facial expectancy. The changed demands on attentional allocation signals during conflict processing, especially in the FF condition, suggests that expectancy primes involving more salient stimuli, such as faces, may reduce attentional and cognitive load during conflict processing [ 28 ], [ 37 ]. This result is further supported by behavioral data, which showed an increasing trend in hit rates from the classical to the label-first and then to the face-first condition, indicating improved performance with expectancy manipulation. Our results also corroborate Leocani et al. (2001) findings, whose results suggest that beta power modulations are possibly related to early attentional visual integration and consequently facilitate subsequent processing during the conflict period [ 41 ]. This finding aligns with prior evidence showing that beta and alpha power reduction is more pronounced in situations requiring greater attentional recruitments- as faces do- particularly during processes involving the segregation of visual elements, as described by Costa et al. (2024). Further differences in localized beta sources between the face-first and the label-first conditions reached significance during conflict processing, revealing activation differences in the precuneus (Broadmann area 7), which has been linked to high-level processing tasks including attentional deployment [ 43 ]. Regarding study limitations, although the use of a controlled laboratory task allowed for the precise investigation of specific cognitive mechanisms, it may limit the ecological validity of the findings, as real-world situations often involve more complex and dynamic environments. Future studies using multimodal imaging techniques, such as EEG combined with fMRI, could provide more detailed spatial and temporal insights into these processes. Additionally, the sLORETA source localization method used in this study has known limitations in spatial resolution. Higher-resolution neuroimaging methods could help validate and extend our source-level findings. Future work should examine expectancy-related conflict processing in clinical populations, such as individuals with anxiety or depression, who often exhibit expectancy biases [ 44 ], and conflict processing alterations. Incorporating more ecologically valid paradigms that better approximate real-life cognitive demands could also enhance the generalizability of the results. 5. Conclusion In summary, our findings provide novel evidence that expectancy, particularly face-driven expectancy, facilitates conflict resolution during Emotional Stroop tasks. Behaviorally, expectancy increased hit rates under expectancy conditions, especially when expectations were based on facial cues. This suggests that face-driven expectancy enhances conflict resolution by leveraging the brain’s prioritization of facial information. Neurophysiologically, we observed significant differential in both ERP outcomes (CSP) and in alpha and low beta activity in parietal channels, which are linked to attentional allocation and cognitive control. This indicates that expectancy modulates conflict processing by affecting later stages of cognitive processing and bypassing typical conflict-related ERP components due to enhanced facilitation. Our findings highlight the importance of expectancy in shaping cognitive processing, showing that face-driven expectations show a distinct deployment of attentional mechanisms and enhance performance during emotional recognition. Further research should explore this phenomenon in real-life settings and clinical populations, offering valuable insights into socioemotional conflict resolution and intervention strategies. Declarations Conflicts of interest The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript. Ethics approval The study was approved (or granted exemption) by the Ethics committee (including the name of the ethics committee of the Faculty of Medicine of the University of Coimbra in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki. Consent to participate All participants consented to participate and signed the informed consent approved by the Ethics Committee. Consent for publication Not applicable. Open Practices Statement Data or materials for the experiments reported here are available upon reasonable request. None of the experiments was preregistered. Competing interests The authors have no competing interests as defined by Nature Research, or other interests that might be perceived to influence the results and/or discussion reported in this paper. Funding The work was supported by grants UI/BD/154279/2022 ( https://doi.org/10.54499/UI/BD/154279/2022 ), UID/04950B/2020 & 2025, UID/04950P/2020 & 2025 and 2021.01469.CEECIND ( https://doi.org/10.54499/2021.01469.CEECIND/CP1656/CT0017 ) from the Foundation of Science and Technology. Author Contribution All authors contributed to the design of the research and reviewed the manuscript. DA and GP developed the code for implementation. MC and TS implemented the experimental task. Maria Coelho carried out the analysis of the results and wrote the original draft of the manuscript. MCB conceived the original framework and supervised the project. Data Availability Availability of data and materials (data transparency)Data or materials for the experiments reported here are available upon reasonable request.Code availability Research metadata and code supporting this publication are available at https://github.com/Daniel-Agostinho/ESP. Miguel Castelo-Branco and/or Daniel Agostinho should be contacted for any requested. References Botvinick, M. M., Carter, C. S., Braver, T. S., Barch, D. M. & Cohen, J. D. Conflict monitoring and cognitive control. Psychol. Rev. 108 (3). 10.1037/0033-295X.108.3.624 (2001). Menon, V. & D’Esposito, M. ‘The role of PFC networks in cognitive control and executive function’, 2022. 10.1038/s41386-021-01152-w Ma, J., Liu, C. & Chen, X. Emotional Modulation of Conflict Processing in the Affective Domain: Evidence from Event-related Potentials and Event-related Spectral Perturbation Analysis. Sci. Rep. 6 10.1038/srep31278 (2016). Overmeyer, R. et al. The Error-Related Negativity Predicts Self-Control Failures in Daily Life. Front. Hum. Neurosci. 14 10.3389/fnhum.2020.614979 (2021). Dignath, D., Eder, A. B., Steinhauser, M. & Kiesel, A. ‘Conflict monitoring and the affective-signaling hypothesis—An integrative review’, 2020. 10.3758/s13423-019-01668-9 Straub, E. R. et al. Limitations of cognitive control on emotional distraction – Congruency in the Color Stroop task does not modulate the Emotional Stroop effect. Cogn. Affect. Behav. Neurosci. 22 (1). 10.3758/s13415-021-00935-4 (2022). Bubic, A., Yves, D., von Cramon & Schubotz, R. I. ‘Prediction, cognition and the brain’, 2010. 10.3389/fnhum.2010.00025 Zhu, J. et al. Neural Basis of the Emotional Conflict Processing in Major Depression: ERPs and Source Localization Analysis on the N450 and P300 Components. Front. Hum. Neurosci. 12 10.3389/fnhum.2018.00214 (2018). Imbir, K. K., Spustek, T., Duda, J., Bernatowicz, G. & Zygierewicz, J. ‘N450 and LPC event-related potential correlates of an Emotional Stroop Task with words differing in valence and emotional origin’, Front Psychol , vol. 8, no. MAY, (2017). 10.3389/fpsyg.2017.00880 Fischer-Jbali, L. R., Montoro, C. I., Montoya, P., Halder, W. & Duschek, S. Central nervous activity during an emotional Stroop task in fibromyalgia syndrome. Int. J. Psychophysiol. 177 10.1016/j.ijpsycho.2022.05.009 (2022). Sullivan, S. K. & Strauss, G. P. Electrophysiological evidence for detrimental impact of a reappraisal emotion regulation strategy on subsequent cognitive control in schizophrenia. J. Abnorm. Psychol. 126 (5). 10.1037/abn0000285 (2017). Lobier, M., Palva, J. M. & Palva, S. ‘High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention’, Neuroimage , vol. 165, pp. 222–237, Jan. (2018). 10.1016/J.NEUROIMAGE.2017.10.044 Borra, D., Fantozzi, S., Bisi, M. C. & Magosso, E. ‘Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements’, Sensors , vol. 23, no. 7, p. 3530, Apr. (2023). 10.3390/S23073530/S1 Roehe, M. A. et al. Early alpha/beta oscillations reflect the formation of face-related expectations in the brain. PLoS One . 16 , e0255116. 10.1371/JOURNAL.PONE.0255116 (Jul. 2021). no. 7. Kilavik, B. E., Zaepffel, M., Brovelli, A., MacKay, W. A. & Riehle, A. ‘The ups and downs of beta oscillations in sensorimotor cortex’, 2013. 10.1016/j.expneurol.2012.09.014 Van Wijk, B. C. M., Daffertshofer, A., Roach, N. & Praamstra, P. A role of beta oscillatory synchrony in biasing response competition? Cereb. Cortex . 19 (6). 10.1093/cercor/bhn174 (2009). Harrison, N. R. & Ziessler, M. ‘Effect anticipation affects perceptual, cognitive, and motor phases of response preparation: Evidence from an event-related potential (ERP) study’, Front Hum Neurosci , vol. 10, no. JAN 2016, (2016). 10.3389/fnhum.2016.00005 Fan, L. et al. ‘Neural correlates of task-irrelevant first and second language emotion words - Evidence from the emotional face-word stroop task’, Front Psychol , vol. 7, no. NOV, (2016). 10.3389/fpsyg.2016.01672 Wechsler, D. ‘Wechsler Adult Intelligence Scale-Third Edition’, (1997). MathWorks, M. A. T. L. A. B. The MathWorks Inc, Natick, Massachusetts : R2022a. (2022). Brainard, D. ‘The psychophysics toolbox’, (1997). Langner, O. et al. ‘Presentation and validation of the radboud faces database’, Cogn Emot , vol. 24, no. 8, (2010). 10.1080/02699930903485076 Brain Products GmbH. ‘BrainVision Recorder ’, Gilching, Germany : Vers. 1.23.0001. (2020). Makeig, S., Debener, S., Onton, J. & Delorme, A. Mining event-related brain dynamics. Trends Cogn. Sci. 8 (5). 10.1016/j.tics.2004.03.008 (2004). Miyakoshi, M. ‘Makoto’s preprocessing pipeline - SCCN’, Swartz Center for Computational Neuroscience Wiki site. Chen, T. et al. Dissociable early attentional control mechanisms underlying cognitive and affective conflicts. Sci. Rep. 6 10.1038/srep37633 (2016). Borra, D., Fantozzi, S., Bisi, M. C. & Magosso, E. Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements. Sensors 23 (7). 10.3390/s23073530 (2023). Roehe, M. A. et al. July,., ‘Early alpha/beta oscillations reflect the formation of face-related expectations in the brain’, PLoS One , vol. 16, no. 7 (2021). 10.1371/journal.pone.0255116 Marco-Pallarés, J., Grau, C. & Ruffini, G. ‘Combined ICA-LORETA analysis of mismatch negativity’, Neuroimage , vol. 25, no. 2, (2005). 10.1016/j.neuroimage.2004.11.028 Pascual-Marqui, R. D. ‘Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details’, in Methods and Findings in Experimental and Clinical Pharmacology , (2002). Hoffmann, S., Labrenz, F., Themann, M., Wascher, E. & Beste, C. Crosslinking EEG time-frequency decomposition and fMRI in error monitoring. Brain Struct. Funct. 219 (2). 10.1007/s00429-013-0521-y (2014). Sekihara, K., Sahani, M. & Nagarajan, S. S. ‘Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction’, Neuroimage , vol. 25, no. 4, (2005). 10.1016/j.neuroimage.2004.11.051 Kilavik, B. E., Zaepffel, M., Brovelli, A., MacKay, W. A. & Riehle, A. The ups and downs of beta oscillations in sensorimotor cortex. Exp. Neurol. 245 , 15–26. 10.1016/J.EXPNEUROL.2012.09.014 (Jul. 2013). Bandura, A. ‘Social cognitive theory: An agentic perspective’, (2001). 10.1146/annurev.psych.52.1.1 Bourbon-Teles, J., Jorge, L., Canário, N. & Castelo-Branco, M. ‘Structural impairments in hippocampal and occipitotemporal networks specifically contribute to decline in place and face category processing but not to other visual object categories in healthy aging’, Brain Behav , vol. 11, no. 8, (2021). 10.1002/brb3.2127 Larson, M. J., Clayson, P. E. & Clawson, A. ‘Making sense of all the conflict: A theoretical review and critique of conflict-related ERPs’, 2014. 10.1016/j.ijpsycho.2014.06.007 Williams, C. C., Ferguson, T. D., Hassall, C. D., Wright, B. & Krigolson, O. E. ‘Dissociated neural signals of conflict and surprise in effortful decision Making: Theta activity reflects surprise while alpha and beta activity reflect conflict’, Neuropsychologia , vol. 155, (2021). 10.1016/j.neuropsychologia.2021.107793 Soutschek, A., Stelzel, C., Paschke, L., Walter, H. & Schubert, T. Dissociable effects of motivation and expectancy on conflict processing: An fMRI study. J. Cogn. Neurosci. 27 (2). 10.1162/jocn_a_00712 (2014). Van Veen, V. & Carter, C. S. The anterior cingulate as a conflict monitor: FMRI and ERP studies. Physiol. Behav. 77 , 4–5. 10.1016/S0031-9384(02)00930-7 (2002). Martinez-Alvarez, A., Sanz-Torrent, M., Pons, F. & de Diego-Balaguer, R. Rethinking attention in time: Expectancy violations reconcile contradictory developmental evidence. J. Exp. Child. Psychol. 206 10.1016/j.jecp.2020.105070 (2021). Leocani, L., Toro, C., Zhuang, P., Gerloff, C. & Hallett, M. ‘Event-related desynchronization in reaction time paradigms: A comparison with event-related potentials and corticospinal excitability’, Clinical Neurophysiology , vol. 112, no. 5, (2001). 10.1016/S1388-2457(01)00530-2 Costa, G. N. et al. Distinct oscillatory patterns differentiate between segregation and integration processes in perceptual grouping. Hum. Brain Mapp. 45 (12). 10.1002/HBM.26779 (Aug. 2024). Cavanna, A. E. & Trimble, M. R. ‘The precuneus: A review of its functional anatomy and behavioural correlates’, 2006. 10.1093/brain/awl004 Eysenck, M. W., Derakshan, N., Santos, R. & Calvo, M. G. ‘Anxiety and cognitive performance: Attentional control theory’, Emotion , vol. 7, no. 2, pp. 336–353, May (2007). 10.1037/1528-3542.7.2.336 . Additional Declarations No competing interests reported. Supplementary Files supmaterialreadyforsubm.docx Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 16 Oct, 2025 Reviews received at journal 15 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviewers agreed at journal 27 Sep, 2025 Reviews received at journal 26 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers invited by journal 22 Sep, 2025 Editor assigned by journal 22 Sep, 2025 Editor invited by journal 29 Aug, 2025 Submission checks completed at journal 26 Aug, 2025 First submitted to journal 26 Aug, 2025 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7440652","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":524871891,"identity":"8867ed11-692b-4bb9-ab82-90b4cf3367cc","order_by":0,"name":"Maria Coelho","email":"","orcid":"","institution":"University of Coimbra","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Coelho","suffix":""},{"id":524871892,"identity":"0468e4b2-4319-453c-961d-ea8aa474ba43","order_by":1,"name":"Daniel Agostinho","email":"","orcid":"","institution":"University of Coimbra","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Agostinho","suffix":""},{"id":524871893,"identity":"b432256b-e6d8-4b7f-880d-2b7706b48e61","order_by":2,"name":"Teresa Sousa","email":"","orcid":"","institution":"University of Coimbra","correspondingAuthor":false,"prefix":"","firstName":"Teresa","middleName":"","lastName":"Sousa","suffix":""},{"id":524871894,"identity":"6a68f449-8847-4c34-8558-d2d85fc5ee7c","order_by":3,"name":"Gabriel Pires","email":"","orcid":"","institution":"University of Coimbra","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"","lastName":"Pires","suffix":""},{"id":524871895,"identity":"fde06008-4d3f-4c53-923e-1760c1690e58","order_by":4,"name":"Miguel Castelo-Branco","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYFACHgjFz3wAziZSi2RbAozNTKQWg2PEatFtP3vsw88ddnLGx7gTH7xhOCzPIN1/AK8WszN5yTN7zyQbmx3j3Ww4h+GwYYPMYfy2mN3gMWbgbTuQuO1+7zZpHobDCQwSyYS1MP4Fatncxrv9N9FamEG2bGDj3cZMnBagX5hl25KNJYB+kZxjkG7YJnPYAL+W42cPM75ts5Pjb+Pd+OFNhbU8v3TjA/zWoAKg+WwSpGiAADK0jIJRMApGwfAGANYIP9jmCOGTAAAAAElFTkSuQmCC","orcid":"","institution":"University of Coimbra","correspondingAuthor":true,"prefix":"","firstName":"Miguel","middleName":"","lastName":"Castelo-Branco","suffix":""}],"badges":[],"createdAt":"2025-08-23 10:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7440652/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7440652/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-34447-9","type":"published","date":"2026-01-10T15:59:23+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93074757,"identity":"c0118efc-876c-44cd-bb92-45f85bed441b","added_by":"auto","created_at":"2025-10-08 18:41:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2042325,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript1postrevmcbreadyforsubm.docx","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/041119ced140a90f96381fef.docx"},{"id":93074622,"identity":"83153b2e-1f41-484b-a4a7-fbb013fadaba","added_by":"auto","created_at":"2025-10-08 18:41:23","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6771,"visible":true,"origin":"","legend":"","description":"","filename":"b6bb3ca00a024e4bb425dd423359360e.json","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/bd14a67b90152bd41c018b20.json"},{"id":93074729,"identity":"c71413e1-a4e4-4f80-851c-536e47e574af","added_by":"auto","created_at":"2025-10-08 18:41:30","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15821,"visible":true,"origin":"","legend":"","description":"","filename":"supmaterialreadyforsubm.docx","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/f06737cc82ce3b2ed8aa880d.docx"},{"id":93074718,"identity":"fa3a08da-5390-464f-b071-980705280100","added_by":"auto","created_at":"2025-10-08 18:41:26","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":113219,"visible":true,"origin":"","legend":"","description":"","filename":"b6bb3ca00a024e4bb425dd423359360e1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/a261216d906ddf9f0443a971.xml"},{"id":93074651,"identity":"b5c94d5d-3e3c-4862-a865-44b0f43e00a4","added_by":"auto","created_at":"2025-10-08 18:41:23","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":140155,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/e7c5c5db32523c20161f9f91.png"},{"id":93075082,"identity":"cb7f8cca-ae45-4cc3-91a7-7c4fd8c8f27d","added_by":"auto","created_at":"2025-10-08 19:01:40","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":160708,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/b2df27bb2e5b5814e96f1724.png"},{"id":93074606,"identity":"25094854-4167-4484-82c4-461ba661b940","added_by":"auto","created_at":"2025-10-08 18:41:19","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":157663,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/33d36025abbe6b5fe4cfe1e6.jpeg"},{"id":93074620,"identity":"1f960818-e23d-4d25-8071-20536ffc2acf","added_by":"auto","created_at":"2025-10-08 18:41:22","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141522,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/949f2187cca45044f3b3d796.png"},{"id":93074727,"identity":"75ffb018-9f60-48f8-93c2-9e20574f6a05","added_by":"auto","created_at":"2025-10-08 18:41:29","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":72785,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/f2b97a59314d0628d3b45649.png"},{"id":93074617,"identity":"d1c74dae-ed4d-4038-9271-d0b1a032b663","added_by":"auto","created_at":"2025-10-08 18:41:22","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":293527,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/c43f6a95eabc49dfa6bd2f0f.png"},{"id":93074686,"identity":"66988592-d56d-402c-b6bc-626ac5847166","added_by":"auto","created_at":"2025-10-08 18:41:24","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":494576,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/a1646c74420c9b130aca05ad.png"},{"id":93074608,"identity":"1be0550d-37f4-4800-8a48-0355a06ab138","added_by":"auto","created_at":"2025-10-08 18:41:20","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":402068,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/dceee1c5f36bbb769ac25a4d.png"},{"id":93074624,"identity":"000c216a-c6c2-40e5-ab28-ee8d516888f5","added_by":"auto","created_at":"2025-10-08 18:41:23","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32981,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/df3be13e658ea4c76a91990c.png"},{"id":93074607,"identity":"c613c78a-4e60-4581-83bc-87890dff2558","added_by":"auto","created_at":"2025-10-08 18:41:19","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":31087,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/2f16bae574e4539775ae9884.png"},{"id":93074732,"identity":"91a58900-f1a0-47ab-b1d4-9d939f060d6d","added_by":"auto","created_at":"2025-10-08 18:41:31","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34458,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/ab9b90a49be34be12a56a997.png"},{"id":93074609,"identity":"29e71b1a-d94a-447b-9f15-cefa66c698c9","added_by":"auto","created_at":"2025-10-08 18:41:21","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":31462,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/dd2246f2f146d1b7cd391f78.png"},{"id":93074616,"identity":"9304543f-bfc5-45c8-b606-9031e06f2d1d","added_by":"auto","created_at":"2025-10-08 18:41:22","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":18349,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/4785a7b9c096fcd4375ed79d.png"},{"id":93074612,"identity":"94b8e516-0b0e-4760-aaf6-4228f2a098cb","added_by":"auto","created_at":"2025-10-08 18:41:21","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32274,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/ac75b2749146780991ef5dad.png"},{"id":93074723,"identity":"d4daa597-52dd-4811-8bda-cebe5f1badee","added_by":"auto","created_at":"2025-10-08 18:41:27","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":52310,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/51c67549bb6dcbadda7fba55.png"},{"id":93074610,"identity":"796e8c4d-6ec0-4404-9c0d-347e5b8e88b1","added_by":"auto","created_at":"2025-10-08 18:41:21","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37261,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/03bd3e9d165a403d061c869d.png"},{"id":93074730,"identity":"5d8959ff-5a4b-44ab-b0b4-71a23486f1da","added_by":"auto","created_at":"2025-10-08 18:41:30","extension":"xml","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110956,"visible":true,"origin":"","legend":"","description":"","filename":"b6bb3ca00a024e4bb425dd423359360e1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/1f7828313c012e28c0cfa43b.xml"},{"id":93074681,"identity":"d0ae5dd6-c25f-4537-adb5-1d215838e901","added_by":"auto","created_at":"2025-10-08 18:41:24","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126212,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/7cbb387ba7dda368b93e45a0.html"},{"id":93074731,"identity":"8711cebf-60a7-4dbb-908c-f0b165ec2f5c","added_by":"auto","created_at":"2025-10-08 18:41:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":140155,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEXPERIMENTAL TASK. \u003c/strong\u003eA VARIATION OF THE FACE-WORD EMOTIONAL STROOP TASK IS PRESENTED. IN THE CLASSICAL CONDITION (CL), THE FACE AND THE LABEL APPEAR SIMULTANEOUSLY. IN THE LABEL-FIRST CONDITION (LF), THE LABEL APPEARS FIRST, FOLLOWED BY THE FACE AND THE LABEL OVERLAPPED. FINALLY, IN THE FACE-FIRST CONDITION (FF) THE FACE APPEARED FIRST, FOLLOWED BY THE FACE AND THE LABEL OVERLAPPING. IN BOTH THE LF AND THE FF CONDITIONS, EXPECTANCY IS GENERATED THROUGH STIMULUS ANTICIPATION. ALL FACES WERE RETRIEVED FROM THE OPEN-ACCESS RADBOUD FACES DATABASE (LANGNER ET AL., 2010).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/e8bae2747dd160139353fb4a.png"},{"id":93074738,"identity":"343778a3-4259-4527-851f-e73d9a8052bd","added_by":"auto","created_at":"2025-10-08 18:41:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":160708,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCONGRUENT AND INCONGRUENT EXAMPLES\u003c/strong\u003e. ON THE LEFT SIDE, CONGRUENT STIMULI ARE PRESENTED, WITH A HAPPY FACE AND A HAPPY LABEL (TOP) AND A SAD FACE WITH A SAD LABEL (BOTTOM). ON THE RIGHT PANEL,INCONGRUENT STIMULI ARE SHOWN. A HAPPY FACE WITH A SAD LABEL IS PRESENTED IN THE TOP CORNER, AND A SAD FACE WITH A HAPPY LABEL IS PRESENTED IN THE BOTTOM CORNER.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/9fe7aaec28ed2040e09df78f.png"},{"id":93074611,"identity":"8e6d316a-c21b-441d-979e-9ab2a29d6f14","added_by":"auto","created_at":"2025-10-08 18:41:21","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":92758,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTREND ANALYSIS FOR HIT-RATE.\u003c/strong\u003e A SIGNIFICANT CONDITION-RELATED MAIN EFFECT WAS FOUND. SPECIFICALLY, THE FACE-FIRST CONDITION SHOWED SIGNIFICANTLY HIGHER HIT RATES (M = 97.30, SD = 3.25) COMPARED TO BOTH THE LABEL-FIRST CONDITION (M = 96.40, SD = 3.71) AND THE CLASSIC EMOTIONAL STROOP CONDITION (M = 95.60, SD = 4.00).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/dc94e88cf311a3db15a88461.jpeg"},{"id":93074714,"identity":"b3d247e0-25f2-426a-8141-807b917a9385","added_by":"auto","created_at":"2025-10-08 18:41:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":141522,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTIME-LOCKED ERP COMPONENTS. \u003c/strong\u003eTHE N400-RELATED COMPONENT IS SHOWN AT 414 MS AND THE CSP-RELATED COMPONENT in THE [600MS, 700MS] TIMEFRAME ON THE CENTRAL CLUSTER (C1, C2, CZ) FOR THE CLASSICAL, THE LABEL-FIRST AND THE FACE-FIRST CONDITIONS, RESPECTIVELY. FOR ALL THE CONDITIONS THE 0 MS REPRESENTS THE MOMENT WHERE THE FACE AND THE LABEL APPEAR SIMULTANEOUSLY (CONFLICT MOMENT). THE BLUE TRACE REPRESENTS THE RESPONSE TO THE CONGRUENT TRIALS, THE RED TRACE REPRESENTS THE RESPONSE TO INCONGRUENT TRIALS, AND THE DASHED LINE ILLUSTRATES THE RESPONSE DIFFERENCE BETWEEN INCONGRUENT AND CONGRUENT TRIALS. THE SHADED GREY AREAS INDICATE TIME INTERVALS WHERE SIGNIFICANT DIFFERENCES BETWEEN THE CONGRUENT AND INCONGRUENT NEURONAL RESPONSES WERE FOUND, AS OBTAINED BY THE PAIRED SAMPLE T-TEST PER TIME POINT FOR EACH CONDITION.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/d928947b80a1ac191910472a.png"},{"id":93074621,"identity":"a26e348b-a36b-43d2-8975-bc1726707c32","added_by":"auto","created_at":"2025-10-08 18:41:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":72785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTIME-LOCKED ERP COMPONENTS\u003c/strong\u003e. THE CSP-RELATED COMPONENT IS SHOWN ON THE [450 MS, 700 MS] INTERVAL ON THE PARIETAL CLUSTER (P1, P2, PZ) FOR THE LABEL-FIRST AND THE FACE-FIRST CONDITIONS, RESPECTIVELY. THE 0 MS REPRESENTS THE MOMENT WHERE THE FACE AND THE LABEL APPEAR SIMULTANEOUSLY. THE BLUE TRACE REPRESENTS THE RESPONSE TO CONGRUENT TRIALS AND THE RED TRACE REPRESENTS THE RESPONSE TO INCONGRUENT TRIALS. THE SHADED GREY AREAS INDICATE TIME POINTS WHERE SIGNIFICANT DIFFERENCES BETWEEN THE CONGRUENT AND INCONGRUENT SIGNALS WERE FOUND AS FOUND BY THE PAIRED SAMPLE T-TEST PER TIME POINT FOR EACH CONDITION.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/a1376e1a0336f43842314c2d.png"},{"id":93074602,"identity":"46f7f161-c641-4bfc-aa09-340012413144","added_by":"auto","created_at":"2025-10-08 18:41:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":293527,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEVENT-RELATED SPECTRAL PERTURBATION (ERSP) ANALYSIS FOR PRIMED EXPECTANCY CONDITIONS, IN A PARIETAL CHANNELS CLUSTER (P1, P2, PZ).\u003c/strong\u003e AT -1000 THE STIMULUS FOR EXPECTANCY CREATION, THE LABEL (LEFT PANEL) OR THE FACE (RIGHT PANEL) APPEAR. AT 0 MS THE OVERLAP BETWEEN THE FACE AND THE LABEL APPEARS CREATING A CONFLICT RESOLUTION MOMENT. THE COLOR SCALE INDICATES THE POWER DESCRIBED IN DB.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/f242d2a70ae5d0ff24568d33.png"},{"id":93074623,"identity":"74f1d35f-264f-4ad6-982f-27bb9fb0bbf2","added_by":"auto","created_at":"2025-10-08 18:41:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":494576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTOPOGRAPHICAL MAPS OF ALPHA AND BETA ERSP DISTRIBUTION DURING PRIMED EXPECTANCY AND CONFLICT PROCESSING\u003c/strong\u003e. THE AVERAGED POWER DISTRIBUTION FOR BOTH PRIMED EXPECTANCY PERIOD (LEFT PANEL) AND CONFLICT RESOLUTION (RIGHT PANEL) ARE SHOWN. FOR\u003cem\u003e \u003c/em\u003eBOTH ALPHA (10 ± 1 HZ) AND LOW BETA (14 ± 1 HZ) FREQUENCIES SIGNIFICANT POWER DIFFERENCES BETWEEN CONDITIONS FOR BOTH ALPHA AND LOW BETA FREQUENCIES, IDENTIFIED USING PAIRED SAMPLE T-TESTS AND CORRECTED WITH THE LTD METHOD, ARE HIGHLIGHTED IN RED IN THE \u003cem\u003eP\u003c/em\u003e-VALUE TOPOGRAPHICAL MAP.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/8c8b2fd26cadbf1aaf8cc6d2.png"},{"id":93074741,"identity":"947c68c8-9b22-45b4-86a9-eb2a703f4558","added_by":"auto","created_at":"2025-10-08 18:41:35","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":402068,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSLORETA SOURCE LOCALIZATION RESULTS. \u003c/strong\u003eSIGNIFICANT DIFFERENCES IN LOW BETA POWER (12-15 HZ) ARE SHOWN, BETWEEN THE FACE-BASED AND THE LABEL-BASED EXPECTANCY CONDITIONS IN THE TIME WINDOW OF 400-600 MS POST-STIMULUS WHERE CONFLICT USUALLY OCCURS. THE SIGNIFICANT DIFFERENCES WERE ESTIMATED TO OCCUR IN THE BRODMANN AREA 7, SPECIFICALLY IN THE PRECUNEUS REGION OF THE PARIETAL LOBE (MNI COORDINATES: \u003cem\u003eX\u003c/em\u003e = -5, \u003cem\u003eY\u003c/em\u003e = -80, \u003cem\u003eZ \u003c/em\u003e= 50) WITH A LOG OF THE F-RATIO THRESHOLD OF -0.671 AND A SIGNIFICANCE LEVEL OF \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/a8db5bba1a3be95afe1d4dd4.png"},{"id":100070169,"identity":"9514d367-5305-458c-adc3-6e8b50521a24","added_by":"auto","created_at":"2026-01-12 16:16:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2717132,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/0a821ad0-5e30-454e-9d71-8e247b460646.pdf"},{"id":93074641,"identity":"0d1e9374-5c21-4ffd-bdaa-1002fb6b94e2","added_by":"auto","created_at":"2025-10-08 18:41:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15821,"visible":true,"origin":"","legend":"","description":"","filename":"supmaterialreadyforsubm.docx","url":"https://assets-eu.researchsquare.com/files/rs-7440652/v1/1cb4ab95c846993064a9fcc0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Face expectancy cues differentially modulate conflict processing driven by emotional incongruence: An EEG study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cb\u003eExpectancy effect of Emotional Conflict Processing\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflict\u003c/strong\u003e\u003cp\u003eprocessing refers to cognitive mechanisms involved in detecting and resolving inconsistent information [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Given its role in guiding adaptive learning and goal-directed behavior [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], incongruence processing is a critical facet of everyday conflict handling [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While previous research has addressed the impact of affective and emotional processing on incongruence processing [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], the role of expectation, which is typically present in socioemotional interactions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] remains to be understood. Investigating how expectancy cueing can modulate incongruence processing offers a new window into improved understanding of conflict processing itself. Here, we thus seek to investigate the neural mechanisms underlying the interplay between these processes.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNeural Correlates of Emotional Conflict Processing\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrevious event-related potential (ERP) studies have addressed the distinct neurophysiological underpinnings of conflict processing in emotional contexts, such as the centroparietal N400 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] (also often referred to as the N450 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]), where more negative amplitudes are evident in incongruent stimuli than in congruent stimuli, and the conflict slow potential (CSP) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] (also referred to as the Late Positive Component [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], or Sustained Potential [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]) shown from 500 ms onwards after stimulus onset, showing a divergence in amplitude between congruent and incongruent stimuli in centroparietal channels and linked to conscious processing. Whilst ERPs are often studied in this context, oscillatory markers have not been as much of a focus of study. Previous research has associated increased parietal alpha power with the suppression of task-irrelevant information, therefore optimizing attentional focus and aiding in conflict resolution [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Parietal beta power modulations have frequently been linked to top-down attentional control processes, with decreases in beta power reflecting the allocation of attentional resources during visual processing [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous findings have also reported parietal beta power decreases during post-cue periods [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Van Wijk et al. (2009) found that beta power decreased significantly less when a cue contained no useful information about the subsequent action [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], suggesting that these modulations may also contribute to stimulus anticipation and expectancy creation. Expectancy can be introduced in an experimental design using stimulus onset asynchrony paradigms [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. By manipulating stimulus anticipation over an extended period, it is possible to create an expectancy effect which modulates perceptual and attentive stimulus processing.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Overview and Hypotheses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe hypothesized that primed expectations, particularly face-driven expectations, have a differential impact on conflict resolution, and this was investigated by a variation of the Emotional Stroop task at both behavioral and neurophysiological levels.\u003c/p\u003e\u003cp\u003e Accordingly, to investigate how expectations affect conflict processing in emotion recognition we assessed the effects of two distinct primed expectations - face-driven and letter label-driven \u0026ndash; on conflict resolution, using an Emotional Stroop design. Emotional Stroop Paradigms offer a unique approach for studying how emotions may influence conflict resolution [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. By employing facial expressions to elicit emotional recognition responses, relevant insights were provided on how emotions are processed in congruent and incongruent contexts [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWe analyzed ERP components linked to conflict processing and resolution, namely the N400 and CSP. In addition, we investigated how expectancy influenced oscillatory activity, focusing on parietal beta and alpha modulations. These measures were used in the current study to index changes in perceptual mechanisms induced by expectancy and the integration of top-down attentional processes, respectively.\u003c/p\u003e\u003cp\u003eWe hypothesized that parietal beta activity would reflect changes in top-down attentional control, potentially facilitating conflict processing through enhanced anticipation. Conversely, parietal alpha activity might index shifts in visual processing mechanisms, modulating the allocation of attentional resources to optimize the perceptual processing of expected stimuli. By examining these neurophysiological patterns alongside behavioral components, we aim to provide a deeper understanding of how expectancy modulates conflict processing in socioemotional contexts involving face processing.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Participants\u003c/h2\u003e\u003cp\u003eTwenty healthy participants (9 females, 11 males) with a mean age of 24 years (standard deviation (SD)\u0026thinsp;=\u0026thinsp;2.92) were recruited using snowball sampling. Participants were Portuguese adults, 18 years old or older, with normal or corrected vision. Exclusion criteria included individuals with a history of neurological, psychiatric, or neurodevelopmental disorders as well as those scoring below the cut-off normal standard deviation (within 1 SD of the mean) on the matrix reasoning (M\u0026thinsp;=\u0026thinsp;23.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9) and vocabulary (M\u0026thinsp;=\u0026thinsp;48.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1) subtests of the Portuguese version of the Wechsler Adult Intelligence Scale-III (WAIS-III) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. All participants provided written informed consent, and the study was approved by the Ethics Committee of the Faculty of Medicine of the University of Coimbra (reference number 001-CE-2021). This study followed the ethical guidelines of the Declaration of Helsinki to protect the rights and well-being of all participants.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Experimental design\u003c/h2\u003e\u003cp\u003eThe experimental task employed a face-word Emotional Stroop paradigm implemented in MATLAB [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] using the Psychophysics Toolbox Version 3 (PTB-3) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our task involved the presentation of 6 facial expressions (3 male, 3 female) retrieved from the Radbound Faces Database [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] representing happiness or sadness (with visual angles of approximately 9.46\u0026deg; in width and 14.74\u0026deg; in height), with superimposed text labels (either \"T\" for \"triste\" or \"F\" for \"feliz\", meaning sad and happy, respectively, with visual angles of approximately 0.95\u0026deg; in width and 1.91\u0026deg; in height), positioned centrally between the eyes, that were congruent or incongruent with the expressed facial expression (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) in a 24-inch screen (1920 x 1080 pixels, refresh rate\u0026thinsp;=\u0026thinsp;60 Hz). The proportions of congruent and incongruent stimuli were balanced. Three conditions were tested to investigate the influence of the stimulus-primed expectancy. In the classical condition (CL), face and emotion labels appeared simultaneously. For the label-first condition (LF), the letter label appeared first, followed by the face, with the label overlapping the face. In the face-first condition (FF), the face appeared first, followed by face and label overlapping.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e Participants were instructed to identify whether a trial was congruent or incongruent by pressing the corresponding key (letter C or I on the keyboard). A short practice session was conducted before the main experiment to ensure that the participants understood the task completely. In the CL condition, each trial lasted 3 s, while in the LF and FF conditions, it was extended to 4 s to allow for the expectancy period. Regardless of the condition, every trial commenced with a red fixation cross (with visual angles of approximately 1.91\u0026deg; in width and in height) in a black background, lasting 1 s, to enhance participants\u0026rsquo; attentional focus. The fixation cross was followed by the presentation of the congruent or incongruent conditions lasting for 1 s, which was preceded in LF and FF trials by expectancy creation (1-second long). Following the stimulus onset, a black screen appeared with a question indicating the key press option: \"Congruent? \"C\"; Incongruent? \"I\". Participants were instructed to respond only after the question appeared to prevent motor artifacts from affecting the neurophysiological conflict-related signals.\u003c/p\u003e\u003cp\u003eThe experimental implementation was divided into eight runs, each lasting approximately 6 minutes, and consisted of 96 trials equally distributed across conditions. The total duration was approximately 2 hours, including cognitive assessment (20 min), EEG preparation (30 min), data acquisition (60 min). All participants performed the task in a standardized, quiet, and distraction-free environment to minimize potential confounding factors that could influence their results. The full task implementation can be found at (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/Daniel-Agostinho/ESP\u003c/span\u003e\u003cspan address=\"https://github.com/Daniel-Agostinho/ESP\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Data acquisition\u003c/h2\u003e\u003cp\u003eData were collected at the Institute for Nuclear Sciences Applied to Health (ICNAS) in Coimbra. Participants were administered the WAIS-III [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] vocabulary and matrix subtests as inclusion criteria. Electroencephalographic (EEG) activity was recorded using an actiCHamp amplifier (Brain Products GmbH, Gilching, Germany). A 64-channel EEG cap was used, with Ag/AgCl active electrodes placed on the scalp (ActiCHamp Plus, Brain Products GmbH, Gilching, Germany). EEG electrodes were positioned according to the 10\u0026ndash;20 international system, standardizing the electrode placement for scalp recording. Data were collected at a sampling rate of 1000 Hz. The reference electrode was placed at the left mastoid, while the vertical and horizontal electrooculogram (EOG) electrodes were placed above and below the left eye, as well as to the left of the left eye and to the right of the right eye. The EOG signal was recorded to identify visual artifacts and facilitate their removal. Impedances were kept below 10 kΩ to ensure adequate signal quality. Data were recorded using BrainVision recorder software [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Behavioral data processing analyzes\u003c/h2\u003e\u003cp\u003e When a participant failed to respond, the response was recorded as missing and subsequently imputed using the mean of the participant's responses within the corresponding run. Hit rates were subsequently calculated per participant based on the percentage of congruent and incongruent correct responses. The percentages of correct responses for each of the three tested conditions (classical, face-first, and label-first conditions) were extracted and compared across conditions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Neurophysiological processing and analyzes\u003c/h2\u003e\u003cp\u003eEEG signal preprocessing and analyses were performed using the EEGLAB (version 2023.0) toolbox [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] in MATLAB [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. For offline preprocessing of EEG data, a pipeline was created with the necessary steps according to Makoto\u0026rsquo;s preprocessing guidelines [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFirst, the data were downsampled to a frequency of 500 Hz. A high-pass filter was then applied at 0.1 Hz and a low-pass filter was applied at 40 Hz. After these steps, noisy channels (channels with electrical interference or a very low signal-to-noise ratio) were identified by visual inspection and interpolated based on data from neighboring channels, and the data were re-referenced to their average to provide a clearer representation of the brain's electrical activity. Following this step, independent component analysis (ICA) was performed to remove eye and motor artifacts, electrode drift, or any abnormal pattern identified [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Finally, the data were segmented into epochs of interest, from \u0026minus;\u0026thinsp;2000 ms to 1000 ms for six conditions (the three main conditions divided by congruent and incongruent events), locked to the moment where the face and the label overlapped for every condition.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1. Event-Related Potentials \u0026ndash; N400 and CSP\u003c/h2\u003e\u003cp\u003eAll epochs were normalized by subtracting the common baseline moment, referring to the last 500 ms of the fixation cross (-500 ms to 0 ms for CL, and \u0026minus;\u0026thinsp;1500 ms to -1000 ms for LF and FF). At least 90 trials resulted per condition. The maximum peak amplitude was extracted per participant between 330 and 440 ms for the N400 analysis on a central channel cluster (C1, C2, Cz) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], whereas the mean amplitude between 400 ms and 700 ms was extracted for CSP on the central channel cluster [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and a parietal channel cluster (P1, P2, Pz) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.5.2. Event-Related Spectral Perturbation\u003c/h2\u003e\u003cp\u003eEvent-related Spectral Perturbation (ERSP) analysis was conducted in EEGLAB [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] to investigate neural oscillatory dynamics during the formation of primed expectancy and subsequent conflict processing. Frequency power variations over time were calculated using wavelet decomposition as the default spectral decomposition method. EEG data were analyzed for parietal channels from primed expectancy creation (-1000 ms to 0 ms) and for conflict resolution (from 0 ms to 700 ms), within a frequency range from 4 Hz to 40 Hz. Further frequency analyses focused on alpha and beta oscillations, given their role in the interplay between attentional and monitoring processes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The basal period for time-frequency analysis was defined as 500 ms after the fixation cross.\u003c/p\u003e\u003cp\u003eTo assess frequency power oscillations, the average power of alpha and beta was extracted for both primed expectancy creation and conflict processing periods. The topographic distribution of alpha at 10 Hz (\u0026plusmn;\u0026thinsp;1 Hz) and low beta at 14 Hz (\u0026plusmn;\u0026thinsp;1 Hz) were estimated for two key time windows: -600 ms to -400 ms (primed expectation creation) and 400\u0026ndash;600 ms (conflict processing).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.5.3. Source localization analyzes\u003c/h2\u003e\u003cp\u003eFor source localization analysis, we utilized standardized low-resolution brain electromagnetic tomography (sLORETA) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In the sLORETA, the brain\u0026rsquo;s intracerebral volume was divided into 6239 voxels, each with a spatial resolution of 5 mm. The standardized current density for each voxel was then computed based on a realistic head model using the MNI152-T1 template. Supporting evidence from EEG/fMRI studies confirms the accuracy of source estimation using sLORETA [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], as well as studies providing reliable results without localization bias [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. To compare voxel-based sLORETA images across experimental conditions, voxel-wise randomization tests with 5000 permutations were conducted using the built-in sLORETA statistical nonparametric mapping approach. Significant voxel differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), corrected for multiple comparisons (through permutation-based correction) between conditions were mapped onto the MNI brain.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Statistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive analyses were performed to characterize the participants by sex, age, laterality index, and education. The effects experimental cueing conditions (CL, LF, and FF) and conflict (congruency and incongruence) and the possible interaction between them on the hit rate were analyzed through a two-way Repeated Measures ANOVA. Greenhouse-Geisser correction was applied to adjust the degrees of freedom in the repeated-measures ANOVA. Effect sizes were measured using partial eta squared. Subsequently, a trend analysis was performed through a linear regression to explore any systematic patterns across the levels of the independent variables, particularly in relation to how the hit rate changed across the conditions.\u003c/p\u003e\u003cp\u003eN400 and CSP components identified in the central channel cluster for the conditions CL, LF, and FF were analyzed regarding their amplitude point-to-point difference between congruent and incongruent trials using paired samples t-tests. Effect sizes were measured using Cohen\u0026rsquo;s d. For further analyses, two-way repeated measures ANOVA was performed to explore the effect of expectancy conditions (LF and FF) and conflict (congruency and incongruence), as well as the interaction between them, on the amplitude of N400 and CSP. Effect sizes were measured with partial eta squared. The grand average amplitude peak of the CL for N400 (average peak evident at 414 ms) was extracted by participant and subsequently compared between congruent and incongruent trials\u003c/p\u003e\u003cp\u003eFor the statistical analysis of source-localized activity, voxel-wise comparisons were performed using sLORETA's built-in nonparametric randomization tests. Statistical significance was evaluated using a log of the F-ratio (lnF) for each voxel, comparing current density estimates between the experimental conditions. To control for multiple comparisons, the significance threshold was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and corrected using a permutation-based method. A total of 5000 permutations were performed to assess the differences between conditions. Significant voxels were mapped onto the 3D MNI152 template and the corresponding Brodmann areas were identified.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Behavioral data\u003c/h2\u003e\u003cp\u003eDescriptive statistics for behavioral performance in each condition are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e in the supplementary material. No significant differences were found in the hit rate between conditions (\u003cem\u003eF\u003c/em\u003e(2)\u0026thinsp;=\u0026thinsp;2.844, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0741, \u003cem\u003eηp\u0026sup2;\u003c/em\u003e = 0.105), nor did the presence of conflict significantly influence the hit rates (\u003cem\u003eF\u003c/em\u003e(1)\u0026thinsp;=\u0026thinsp;0.458, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.507, \u003cem\u003eηp\u0026sup2;\u003c/em\u003e = 0.024). Moreover, no interaction was found between the type of condition and congruence (\u003cem\u003eF\u003c/em\u003e(2)\u0026thinsp;=\u0026thinsp;0.906, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.413, \u003cem\u003eηp\u0026sup2;\u003c/em\u003e = 0.046).\u003c/p\u003e\u003cp\u003eNevertheless, further trend analysis revealed a significant main condition-related effect. Specifically, the FF condition showed significantly higher hit rates (M\u0026thinsp;=\u0026thinsp;97.30, SD\u0026thinsp;=\u0026thinsp;3.25) than both the LF (M\u0026thinsp;=\u0026thinsp;96.40, SD\u0026thinsp;=\u0026thinsp;3.71) and CL conditions (M\u0026thinsp;=\u0026thinsp;95.60, SD\u0026thinsp;=\u0026thinsp;4.00) (\u003cem\u003eF\u003c/em\u003e(1)\u0026thinsp;=\u0026thinsp;5.885, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), with a moderate effect size (R\u0026sup2; = 0.048) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Event-related potentials related to conflict processing\u003c/h2\u003e\u003cp\u003eWe first asked the question whether the conflict-related evoked responses were present in the conditions where expectancy was introduced (LF and FF) in addition to the classical Emotional Stroop (CL).\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1. N400 and CSP modulation by conflict resolution\u003c/h2\u003e\u003cp\u003e. Paired samples t-test results indicated significant differences in the Classical Condition, with a more negative amplitude for incongruent trials (-0.486\u0026thinsp;\u0026plusmn;\u0026thinsp;1.339 \u0026micro;V) than for congruent trials (-0.272\u0026thinsp;\u0026plusmn;\u0026thinsp;1.284 \u0026micro;V) (\u003cem\u003et\u003c/em\u003e(19)\u0026thinsp;=\u0026thinsp;2.638, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016, CI = [0.044, 0.383], \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.590). Concerning the CSP component, the mean amplitude of congruent trials was significantly higher than the mean amplitude of incongruent trials (0.530\u0026thinsp;\u0026plusmn;\u0026thinsp;1.179 \u0026micro;V and 0.283\u0026thinsp;\u0026plusmn;\u0026thinsp;1.299 \u0026micro;V, respectively) (\u003cem\u003et\u003c/em\u003e(19)\u0026thinsp;=\u0026thinsp;2.327, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031, CI = [0.025, 0.469], \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.520) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Regarding the conditions where expectancy was inserted, no significant differences were found between congruent and incongruent trials for either the N400 or CSP component.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Primed expectancy effect: Attentional Mechanisms related to conflict processing\u003c/h2\u003e\u003cp\u003eFurther analyses were conducted to understand how primed expectancy was processed and subsequently influenced conflict-processing resolution at parietal channels, given this region\u0026rsquo;s importance in top-down control in anticipation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and conflict resolution [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A Two-way Repeated Measures ANOVA was performed to analyze the effect of expectancy and congruency on the signal amplitude for both N400 and CSP.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1. N400 and CSP modulation by the interaction between expectancy and conflict resolution at parietal channels\u003c/h2\u003e\u003cp\u003eWe found a significant impact of expectancy type on the CSP amplitude (\u003cem\u003eF\u003c/em\u003e(1, 19)\u0026thinsp;=\u0026thinsp;10.418, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004, \u003cem\u003eηp\u0026sup2;\u003c/em\u003e = 0.354). Moreover, we found a significant interaction between expectancy creation and congruency (\u003cem\u003eF\u003c/em\u003e(1, 19)\u0026thinsp;=\u0026thinsp;6.287, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021, \u003cem\u003eηp\u0026sup2;\u003c/em\u003e = 0.249). Post hoc comparisons based on paired \u003cem\u003et\u003c/em\u003e-test analysis revealed that in the LF condition, the congruent trials (4.190 \u0026micro;V) showed a higher CSP amplitude than the incongruent trials (3.929 \u0026micro;V) (\u003cem\u003et\u003c/em\u003e(19)\u0026thinsp;=\u0026thinsp;1.637, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.059, CI = [-0.073, 0.595], \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.366), while the opposite was observed in the FF condition, where incongruent trials (3.562 \u0026micro;V) had a higher CSP amplitude than congruent trials (3.292 \u0026micro;V) (\u003cem\u003et\u003c/em\u003e(19) = -1.72, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.046, CI = [-0.590, 0.049], \u003cem\u003ed\u003c/em\u003e = -0.396) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2. Parietal Alpha and Beta Modulations During Expectancy and Conflict Resolution\u003c/h2\u003e\u003cp\u003eDistinct patterns of neural oscillations were revealed during primed expectancy formation and conflict processing for conditions in which expectancy was manipulated, LF, and FF. Two periods were analyzed separately: primed expectancy formation from \u0026minus;\u0026thinsp;600 to -400 ms and conflict resolution from 400 to 600 ms. The power difference between the expectancy generation period and the conflict adaptation period was calculated for each condition using a paired sample t-test. Significant differences were found between the LF and FF conditions (\u003cem\u003et\u003c/em\u003e(19) = -3.777, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Specifically, in the FF condition, an alpha and beta average power decrease was observed during the expectancy period (-1.817 dB) and conflict adaptation (-1.655 dB), leading to an overall power difference of -0.161 dB between the expectancy and conflict resolution periods. In contrast, in the LF condition, no alpha and beta power decreases were observed during the expectancy period (-0.906 dB), while a decrease in alpha and beta power was observed during the conflict processing period (-2.407 dB), leading to a power difference of -1.502 dB.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTopographical maps separately illustrating the alpha and beta average power distributions during the expectation creation and conflict resolution periods further support these findings. During the conflict resolution period, significantly stronger alpha and beta power decreases were observed in the LF condition, when compared to the FF condition (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3. Alpha and Low Beta Source localization\u003c/h2\u003e\u003cp\u003eSignificant differences in conflict processing (400\u0026ndash;600 ms after stimulus onset) were found between the FF and LF conditions in the low-beta frequency range (12\u0026ndash;15 Hz), with significantly stronger decreases in low-beta power observed in the LF condition compared to the FF condition. These differences were localized to Brodmann area 7, specifically in the precuneus, within the Parietal Lobe. The threshold for the log of the F-ratio was \u0026minus;\u0026thinsp;0.671, with a significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The MNI coordinates for this activation difference were X = -5, Y = -80, Z\u0026thinsp;=\u0026thinsp;50 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). No significant differences in alpha and beta modulations were found between LF and FF in the expectancy period.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study investigated the question whether the type of stimulus driven expectancy, using face versus non face cues, differentially influences conflict processing, in the context of emotion recognition. We hypothesized that expectancy would modulate conflict resolution, especially for face stimuli, owing to their unique processing priority in the brain [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Our findings provide evidence that primed expectancy differentially affects conflict-processing dynamics in a cue dependent manner, highlighting its role in modulating cognitive processes in tasks that involve emotional stimuli.\u003c/p\u003e\u003cp\u003eWe first aimed to replicate previously described conflict-related components, such as the N400[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and CSP[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] using an Emotional Stroop task [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], aligned with conflict monitoring theory [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. We observed that when primed expectancy was introduced, this abolished both N400 and CSP in the central channels, showing that expectancy changes typical Stroop conflict patterns. Instead, we observed significant differences at the ERP in the parietal channels, a region often associated with attentional resources [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and expectancy [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Notably, early neural responses did not show significant differences, indicating that the initial stages of conflict detection may remain unaffected by expectancy, as proposed in theories suggesting that early conflict detection mechanisms are automatic and less susceptible to top-down modulation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. However, the significant effect of distinct forms of expectancy cues (faces versus letters) differently impacted the later parietal CSP component (400\u0026ndash;700 ms), showing an expectancy effect on conflict processing linked to top-down attentional mechanisms and active conscious processing [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTime-frequency analysis further corroborated these findings by showing that parietal alpha and beta powers differed significantly based on the type of emotional expectancy cue created. In the face-first condition, a decrease in alpha and beta powers, linked to the active visual processing and recruitment of attentional resources, was observed during the expectancy generation period, followed by a relative power increase during the conflict resolution period, suggesting less attentional allocation during conflict resolution. Contrarily, in the label-first condition, no significant decrease in alpha and beta power was found in expectancy creation, while an accentuated power decrease was clear in conflict resolution, suggesting a heightened engagement of attentional resources mostly during conflict processing, possibly due to the less salient nature of label expectancy compared to facial expectancy. The changed demands on attentional allocation signals during conflict processing, especially in the FF condition, suggests that expectancy primes involving more salient stimuli, such as faces, may reduce attentional and cognitive load during conflict processing [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This result is further supported by behavioral data, which showed an increasing trend in hit rates from the classical to the label-first and then to the face-first condition, indicating improved performance with expectancy manipulation.\u003c/p\u003e\u003cp\u003eOur results also corroborate Leocani et al. (2001) findings, whose results suggest that beta power modulations are possibly related to early attentional visual integration and consequently facilitate subsequent processing during the conflict period [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This finding aligns with prior evidence showing that beta and alpha power reduction is more pronounced in situations requiring greater attentional recruitments- as faces do- particularly during processes involving the segregation of visual elements, as described by Costa et al. (2024). Further differences in localized beta sources between the face-first and the label-first conditions reached significance during conflict processing, revealing activation differences in the precuneus (Broadmann area 7), which has been linked to high-level processing tasks including attentional deployment [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRegarding study limitations, although the use of a controlled laboratory task allowed for the precise investigation of specific cognitive mechanisms, it may limit the ecological validity of the findings, as real-world situations often involve more complex and dynamic environments. Future studies using multimodal imaging techniques, such as EEG combined with fMRI, could provide more detailed spatial and temporal insights into these processes.\u003c/p\u003e\u003cp\u003eAdditionally, the sLORETA source localization method used in this study has known limitations in spatial resolution. Higher-resolution neuroimaging methods could help validate and extend our source-level findings.\u003c/p\u003e\u003cp\u003eFuture work should examine expectancy-related conflict processing in clinical populations, such as individuals with anxiety or depression, who often exhibit expectancy biases [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and conflict processing alterations. Incorporating more ecologically valid paradigms that better approximate real-life cognitive demands could also enhance the generalizability of the results.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn summary, our findings provide novel evidence that expectancy, particularly face-driven expectancy, facilitates conflict resolution during Emotional Stroop tasks. Behaviorally, expectancy increased hit rates under expectancy conditions, especially when expectations were based on facial cues. This suggests that face-driven expectancy enhances conflict resolution by leveraging the brain\u0026rsquo;s prioritization of facial information. Neurophysiologically, we observed significant differential in both ERP outcomes (CSP) and in alpha and low beta activity in parietal channels, which are linked to attentional allocation and cognitive control. This indicates that expectancy modulates conflict processing by affecting later stages of cognitive processing and bypassing typical conflict-related ERP components due to enhanced facilitation.\u003c/p\u003e\u003cp\u003eOur findings highlight the importance of expectancy in shaping cognitive processing, showing that face-driven expectations show a distinct deployment of attentional mechanisms and enhance performance during emotional recognition. Further research should explore this phenomenon in real-life settings and clinical populations, offering valuable insights into socioemotional conflict resolution and intervention strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cp\u003e The study was approved (or granted exemption) by the Ethics committee (including the name of the ethics committee of the Faculty of Medicine of the University of Coimbra in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003cp\u003e All participants consented to participate and signed the informed consent approved by the Ethics Committee.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eOpen Practices Statement\u003c/h2\u003e\u003cp\u003eData or materials for the experiments reported here are available upon reasonable request. None of the experiments was preregistered.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors have no competing interests as defined by Nature Research, or other interests that might be perceived to influence the results and/or discussion reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe work was supported by grants UI/BD/154279/2022 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/UI/BD/154279/2022\u003c/span\u003e\u003cspan address=\"10.54499/UI/BD/154279/2022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), UID/04950B/2020 \u0026amp; 2025, UID/04950P/2020 \u0026amp; 2025 and 2021.01469.CEECIND (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/2021.01469.CEECIND/CP1656/CT0017\u003c/span\u003e\u003cspan address=\"10.54499/2021.01469.CEECIND/CP1656/CT0017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) from the Foundation of Science and Technology.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the design of the research and reviewed the manuscript. DA and GP developed the code for implementation. MC and TS implemented the experimental task. Maria Coelho carried out the analysis of the results and wrote the original draft of the manuscript. MCB conceived the original framework and supervised the project.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAvailability of data and materials (data transparency)Data or materials for the experiments reported here are available upon reasonable request.Code availability Research metadata and code supporting this publication are available at https://github.com/Daniel-Agostinho/ESP. Miguel Castelo-Branco and/or Daniel Agostinho should be contacted for any requested.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBotvinick, M. M., Carter, C. S., Braver, T. S., Barch, D. M. \u0026amp; Cohen, J. D. Conflict monitoring and cognitive control. \u003cem\u003ePsychol. Rev.\u003c/em\u003e \u003cb\u003e108\u003c/b\u003e (3). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/0033-295X.108.3.624\u003c/span\u003e\u003cspan address=\"10.1037/0033-295X.108.3.624\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMenon, V. \u0026amp; D\u0026rsquo;Esposito, M. \u0026lsquo;The role of PFC networks in cognitive control and executive function\u0026rsquo;, 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41386-021-01152-w\u003c/span\u003e\u003cspan address=\"10.1038/s41386-021-01152-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa, J., Liu, C. \u0026amp; Chen, X. Emotional Modulation of Conflict Processing in the Affective Domain: Evidence from Event-related Potentials and Event-related Spectral Perturbation Analysis. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/srep31278\u003c/span\u003e\u003cspan address=\"10.1038/srep31278\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOvermeyer, R. et al. The Error-Related Negativity Predicts Self-Control Failures in Daily Life. \u003cem\u003eFront. Hum. Neurosci.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnhum.2020.614979\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2020.614979\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDignath, D., Eder, A. B., Steinhauser, M. \u0026amp; Kiesel, A. \u0026lsquo;Conflict monitoring and the affective-signaling hypothesis\u0026mdash;An integrative review\u0026rsquo;, 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3758/s13423-019-01668-9\u003c/span\u003e\u003cspan address=\"10.3758/s13423-019-01668-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStraub, E. R. et al. Limitations of cognitive control on emotional distraction \u0026ndash; Congruency in the Color Stroop task does not modulate the Emotional Stroop effect. \u003cem\u003eCogn. Affect. Behav. Neurosci.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3758/s13415-021-00935-4\u003c/span\u003e\u003cspan address=\"10.3758/s13415-021-00935-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBubic, A., Yves, D., von Cramon \u0026amp; Schubotz, R. I. \u0026lsquo;Prediction, cognition and the brain\u0026rsquo;, 2010. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnhum.2010.00025\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2010.00025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, J. et al. Neural Basis of the Emotional Conflict Processing in Major Depression: ERPs and Source Localization Analysis on the N450 and P300 Components. \u003cem\u003eFront. Hum. Neurosci.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnhum.2018.00214\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2018.00214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eImbir, K. K., Spustek, T., Duda, J., Bernatowicz, G. \u0026amp; Zygierewicz, J. \u0026lsquo;N450 and LPC event-related potential correlates of an Emotional Stroop Task with words differing in valence and emotional origin\u0026rsquo;, \u003cem\u003eFront Psychol\u003c/em\u003e, vol. 8, no. MAY, (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyg.2017.00880\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2017.00880\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFischer-Jbali, L. R., Montoro, C. I., Montoya, P., Halder, W. \u0026amp; Duschek, S. Central nervous activity during an emotional Stroop task in fibromyalgia syndrome. \u003cem\u003eInt. J. Psychophysiol.\u003c/em\u003e \u003cb\u003e177\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijpsycho.2022.05.009\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpsycho.2022.05.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSullivan, S. K. \u0026amp; Strauss, G. P. Electrophysiological evidence for detrimental impact of a reappraisal emotion regulation strategy on subsequent cognitive control in schizophrenia. \u003cem\u003eJ. Abnorm. Psychol.\u003c/em\u003e \u003cb\u003e126\u003c/b\u003e (5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/abn0000285\u003c/span\u003e\u003cspan address=\"10.1037/abn0000285\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLobier, M., Palva, J. M. \u0026amp; Palva, S. \u0026lsquo;High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention\u0026rsquo;, \u003cem\u003eNeuroimage\u003c/em\u003e, vol. 165, pp. 222\u0026ndash;237, Jan. (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/J.NEUROIMAGE.2017.10.044\u003c/span\u003e\u003cspan address=\"10.1016/J.NEUROIMAGE.2017.10.044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBorra, D., Fantozzi, S., Bisi, M. C. \u0026amp; Magosso, E. \u0026lsquo;Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements\u0026rsquo;, \u003cem\u003eSensors\u003c/em\u003e, vol. 23, no. 7, p. 3530, Apr. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/S23073530/S1\u003c/span\u003e\u003cspan address=\"10.3390/S23073530/S1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoehe, M. A. et al. Early alpha/beta oscillations reflect the formation of face-related expectations in the brain. \u003cem\u003ePLoS One\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e, e0255116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/JOURNAL.PONE.0255116\u003c/span\u003e\u003cspan address=\"10.1371/JOURNAL.PONE.0255116\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Jul. 2021). no. 7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKilavik, B. E., Zaepffel, M., Brovelli, A., MacKay, W. A. \u0026amp; Riehle, A. \u0026lsquo;The ups and downs of beta oscillations in sensorimotor cortex\u0026rsquo;, 2013. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.expneurol.2012.09.014\u003c/span\u003e\u003cspan address=\"10.1016/j.expneurol.2012.09.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Wijk, B. C. M., Daffertshofer, A., Roach, N. \u0026amp; Praamstra, P. A role of beta oscillatory synchrony in biasing response competition? \u003cem\u003eCereb. Cortex\u003c/em\u003e. \u003cb\u003e19\u003c/b\u003e (6). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/cercor/bhn174\u003c/span\u003e\u003cspan address=\"10.1093/cercor/bhn174\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarrison, N. R. \u0026amp; Ziessler, M. \u0026lsquo;Effect anticipation affects perceptual, cognitive, and motor phases of response preparation: Evidence from an event-related potential (ERP) study\u0026rsquo;, \u003cem\u003eFront Hum Neurosci\u003c/em\u003e, vol. 10, no. JAN 2016, (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnhum.2016.00005\u003c/span\u003e\u003cspan address=\"10.3389/fnhum.2016.00005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFan, L. et al. \u0026lsquo;Neural correlates of task-irrelevant first and second language emotion words - Evidence from the emotional face-word stroop task\u0026rsquo;, \u003cem\u003eFront Psychol\u003c/em\u003e, vol. 7, no. NOV, (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyg.2016.01672\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2016.01672\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWechsler, D. \u0026lsquo;Wechsler Adult Intelligence Scale-Third Edition\u0026rsquo;, (1997).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMathWorks, M. A. T. L. A. B. \u003cem\u003eThe MathWorks Inc, Natick, Massachusetts\u003c/em\u003e: R2022a. (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrainard, D. \u0026lsquo;The psychophysics toolbox\u0026rsquo;, (1997).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangner, O. et al. \u0026lsquo;Presentation and validation of the radboud faces database\u0026rsquo;, \u003cem\u003eCogn Emot\u003c/em\u003e, vol. 24, no. 8, (2010). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/02699930903485076\u003c/span\u003e\u003cspan address=\"10.1080/02699930903485076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrain Products GmbH. \u0026lsquo;BrainVision Recorder \u0026rsquo;, \u003cem\u003eGilching, Germany\u003c/em\u003e: Vers. 1.23.0001. (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMakeig, S., Debener, S., Onton, J. \u0026amp; Delorme, A. Mining event-related brain dynamics. \u003cem\u003eTrends Cogn. Sci.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e (5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tics.2004.03.008\u003c/span\u003e\u003cspan address=\"10.1016/j.tics.2004.03.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2004).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiyakoshi, M. \u0026lsquo;Makoto\u0026rsquo;s preprocessing pipeline - SCCN\u0026rsquo;, Swartz Center for Computational Neuroscience Wiki site.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen, T. et al. Dissociable early attentional control mechanisms underlying cognitive and affective conflicts. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/srep37633\u003c/span\u003e\u003cspan address=\"10.1038/srep37633\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBorra, D., Fantozzi, S., Bisi, M. C. \u0026amp; Magosso, E. Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements. \u003cem\u003eSensors\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/s23073530\u003c/span\u003e\u003cspan address=\"10.3390/s23073530\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoehe, M. A. et al. July,., \u0026lsquo;Early alpha/beta oscillations reflect the formation of face-related expectations in the brain\u0026rsquo;, \u003cem\u003ePLoS One\u003c/em\u003e, vol. 16, no. 7 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0255116\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0255116\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarco-Pallar\u0026eacute;s, J., Grau, C. \u0026amp; Ruffini, G. \u0026lsquo;Combined ICA-LORETA analysis of mismatch negativity\u0026rsquo;, \u003cem\u003eNeuroimage\u003c/em\u003e, vol. 25, no. 2, (2005). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuroimage.2004.11.028\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2004.11.028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePascual-Marqui, R. D. \u0026lsquo;Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details\u0026rsquo;, in \u003cem\u003eMethods and Findings in Experimental and Clinical Pharmacology\u003c/em\u003e, (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoffmann, S., Labrenz, F., Themann, M., Wascher, E. \u0026amp; Beste, C. Crosslinking EEG time-frequency decomposition and fMRI in error monitoring. \u003cem\u003eBrain Struct. Funct.\u003c/em\u003e \u003cb\u003e219\u003c/b\u003e (2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00429-013-0521-y\u003c/span\u003e\u003cspan address=\"10.1007/s00429-013-0521-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSekihara, K., Sahani, M. \u0026amp; Nagarajan, S. S. \u0026lsquo;Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction\u0026rsquo;, \u003cem\u003eNeuroimage\u003c/em\u003e, vol. 25, no. 4, (2005). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuroimage.2004.11.051\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2004.11.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKilavik, B. E., Zaepffel, M., Brovelli, A., MacKay, W. A. \u0026amp; Riehle, A. The ups and downs of beta oscillations in sensorimotor cortex. \u003cem\u003eExp. Neurol.\u003c/em\u003e \u003cb\u003e245\u003c/b\u003e, 15\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/J.EXPNEUROL.2012.09.014\u003c/span\u003e\u003cspan address=\"10.1016/J.EXPNEUROL.2012.09.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Jul. 2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBandura, A. \u0026lsquo;Social cognitive theory: An agentic perspective\u0026rsquo;, (2001). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1146/annurev.psych.52.1.1\u003c/span\u003e\u003cspan address=\"10.1146/annurev.psych.52.1.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBourbon-Teles, J., Jorge, L., Can\u0026aacute;rio, N. \u0026amp; Castelo-Branco, M. \u0026lsquo;Structural impairments in hippocampal and occipitotemporal networks specifically contribute to decline in place and face category processing but not to other visual object categories in healthy aging\u0026rsquo;, \u003cem\u003eBrain Behav\u003c/em\u003e, vol. 11, no. 8, (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/brb3.2127\u003c/span\u003e\u003cspan address=\"10.1002/brb3.2127\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLarson, M. J., Clayson, P. E. \u0026amp; Clawson, A. \u0026lsquo;Making sense of all the conflict: A theoretical review and critique of conflict-related ERPs\u0026rsquo;, 2014. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijpsycho.2014.06.007\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpsycho.2014.06.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilliams, C. C., Ferguson, T. D., Hassall, C. D., Wright, B. \u0026amp; Krigolson, O. E. \u0026lsquo;Dissociated neural signals of conflict and surprise in effortful decision Making: Theta activity reflects surprise while alpha and beta activity reflect conflict\u0026rsquo;, \u003cem\u003eNeuropsychologia\u003c/em\u003e, vol. 155, (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuropsychologia.2021.107793\u003c/span\u003e\u003cspan address=\"10.1016/j.neuropsychologia.2021.107793\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSoutschek, A., Stelzel, C., Paschke, L., Walter, H. \u0026amp; Schubert, T. Dissociable effects of motivation and expectancy on conflict processing: An fMRI study. \u003cem\u003eJ. Cogn. Neurosci.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1162/jocn_a_00712\u003c/span\u003e\u003cspan address=\"10.1162/jocn_a_00712\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Veen, V. \u0026amp; Carter, C. S. The anterior cingulate as a conflict monitor: FMRI and ERP studies. \u003cem\u003ePhysiol. Behav.\u003c/em\u003e \u003cb\u003e77\u003c/b\u003e, 4\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0031-9384(02)00930-7\u003c/span\u003e\u003cspan address=\"10.1016/S0031-9384(02)00930-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartinez-Alvarez, A., Sanz-Torrent, M., Pons, F. \u0026amp; de Diego-Balaguer, R. Rethinking attention in time: Expectancy violations reconcile contradictory developmental evidence. \u003cem\u003eJ. Exp. Child. Psychol.\u003c/em\u003e \u003cb\u003e206\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jecp.2020.105070\u003c/span\u003e\u003cspan address=\"10.1016/j.jecp.2020.105070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeocani, L., Toro, C., Zhuang, P., Gerloff, C. \u0026amp; Hallett, M. \u0026lsquo;Event-related desynchronization in reaction time paradigms: A comparison with event-related potentials and corticospinal excitability\u0026rsquo;, \u003cem\u003eClinical Neurophysiology\u003c/em\u003e, vol. 112, no. 5, (2001). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S1388-2457(01)00530-2\u003c/span\u003e\u003cspan address=\"10.1016/S1388-2457(01)00530-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCosta, G. N. et al. Distinct oscillatory patterns differentiate between segregation and integration processes in perceptual grouping. \u003cem\u003eHum. Brain Mapp.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (12). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/HBM.26779\u003c/span\u003e\u003cspan address=\"10.1002/HBM.26779\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Aug. 2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCavanna, A. E. \u0026amp; Trimble, M. R. \u0026lsquo;The precuneus: A review of its functional anatomy and behavioural correlates\u0026rsquo;, 2006. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/brain/awl004\u003c/span\u003e\u003cspan address=\"10.1093/brain/awl004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEysenck, M. W., Derakshan, N., Santos, R. \u0026amp; Calvo, M. G. \u0026lsquo;Anxiety and cognitive performance: Attentional control theory\u0026rsquo;, \u003cem\u003eEmotion\u003c/em\u003e, vol. 7, no. 2, pp. 336\u0026ndash;353, May (2007). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/1528-3542.7.2.336\u003c/span\u003e\u003cspan address=\"10.1037/1528-3542.7.2.336\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":true,"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":"conflict processing, emotional processing, event-related potentials, expectancy. Word count: 4044 words, excluding figure legends and references","lastPublishedDoi":"10.21203/rs.3.rs-7440652/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7440652/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdaptive behavior in social interactions requires the effective processing of conflicting emotional information. The impact of expectancy on conflict processing remains a relevant research question. Here we investigated the influence of primed expectancy on conflict processing. To achieve this goal, we used the Emotional Stroop paradigm and variants where expectancy was introduced using facial expression or emotional letter labels. Neurophysiological and behavioral data were collected from 20 healthy participants who completed these three conditions (in the presence or absence of prior expectancy cues). We first replicated previous findings by showing higher amplitudes of N400 and Conflict Slow Potential for the incongruent trials during the classical Emotional Stroop condition. When expectancy was introduced, we found a significant effect on conflict processing, with a striking difference between face and letter emotion cues. Parietal alpha and beta power decreases occurred specifically for face expectancy cues, which were attenuated by conflict processing. These findings suggest that attentional resources are differently prioritized by face versus letter emotion expectancy cues, with an impact on performance, with face-driven expectancy generating distinctive neurophysiological patterns and facilitating subsequent conflict resolution.\u003c/p\u003e","manuscriptTitle":"Face expectancy cues differentially modulate conflict processing driven by emotional incongruence: An EEG study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 18:38:29","doi":"10.21203/rs.3.rs-7440652/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-16T05:18:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-15T16:36:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-10T02:07:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"311009581185229562003732258826178826845","date":"2025-09-27T13:57:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-26T08:07:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269748928358958346365045267021490132810","date":"2025-09-25T12:15:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274344061328132614553640954543546144039","date":"2025-09-23T05:48:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-22T17:49:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-22T15:13:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-29T04:14:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-26T21:15:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-26T21:12:09+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":"dad37f99-88df-4496-a920-169eeb66879f","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":55785419,"name":"Biological sciences/Neuroscience"},{"id":55785420,"name":"Biological sciences/Psychology"},{"id":55785421,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-01-12T16:10:34+00:00","versionOfRecord":{"articleIdentity":"rs-7440652","link":"https://doi.org/10.1038/s41598-025-34447-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-10 15:59:23","publishedOnDateReadable":"January 10th, 2026"},"versionCreatedAt":"2025-10-08 18:38:29","video":"","vorDoi":"10.1038/s41598-025-34447-9","vorDoiUrl":"https://doi.org/10.1038/s41598-025-34447-9","workflowStages":[]},"version":"v1","identity":"rs-7440652","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7440652","identity":"rs-7440652","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}