The Linkage between Decision-making and Bodily States: An Investigation Using an Emotional Startle Reflex Paradigm and the Iowa Gambling Task

The Linkage between Decision-making and Bodily States: An Investigation Using an Emotional Startle Reflex Paradigm and the Iowa Gambling Task | 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 Research Article The Linkage between Decision-making and Bodily States: An Investigation Using an Emotional Startle Reflex Paradigm and the Iowa Gambling Task Azahara Miranda, Stefan Duschek, José Luis Mata This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5324668/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Apr, 2025 Read the published version in Psychological Research → Version 1 posted 9 You are reading this latest preprint version Abstract Theories such as the somatic marker hypothesis posit that emotions and feedback from bodily states support higher cognition and decision-making. This study investigated the connection between decision-making and activity of the startle reflex, a defense reflex that is sensitive to emotional states. Decision-making was assessed using the Iowa Gambling Task (IGT), which simulates real-life decision-making with respect to complexity and uncertainty. The startle reflex was quantified, via electromyography, as the eyeblink following intense noise stimulation during the viewing of pleasant, neutral, and unpleasant emotional pictures. Forty-two healthy participants were classified according to their performance on the IGT using the median-split method. In the entire sample, the startle response amplitude progressively increased from pleasant to unpleasant picture exposure. Participants with high IGT performance exhibited smaller response amplitudes than those with low IGT performance, independent of picture valence. Furthermore, inverse linear associations were seen between IGT performance and response amplitudes. The association between decision-making and startle reflex activity may be mediated by individual differences in emotional state. According to previous studies, a positive emotional state, as opposed to a negative emotional state, relates to smaller startle amplitudes and a preference for decision-making strategies based on intuition and body-related information (i.e., somatic markers), which are beneficial in situations involving complex and uncertain decisions. Moreover, an impact of individual differences in prefrontal cortex function on decision-making and startle reflex activity is feasible. The startle paradigm may be a useful tool to investigate the interaction between bodily states and higher-order cognitive processing in future research. startle reflex decision-making emotional state Iowa Gambling Task somatic marker hypothesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction As a crucial ability in daily life, decision-making refers to a set of cognitive processes enabling selection of an advantageous response from among an array of available options (Fellows, 2004 ; Gold & Shadlen, 2007 ). Psychological research suggested strong involvement of emotional experience in these processes (see Angie et al., 2011 for an overview). Positive or negative emotions, as well as emotional regulation abilities, may influence appraisal of the potential consequences of a decision and their respective likelihoods (Werner et al., 2009a ). For example, anxiety modulates the tolerance for risk in experimental decision-making tasks, where highly anxious individuals tend to choose safer options than low-anxiety individuals (Maner et al., 2006 ; Miu et al. 2008 ). In further studies, positive affect was related to higher, and negative affect to lower, success levels in decision-making tasks (Buelow & Suhr, 2012 ; de Vries et al., 2008 ; Suhr & Tsanadis, 2006 ). Current theories emphasize the role of interactions between the brain and body in emotionally guided decision-making (Damasio, 1994 ; Thayer et al., 2009 ). The somatic marker hypothesis may be most influential in this field (Bechara & Damasio, 2004 ). The theory posits that neural representations of physiological conditions (somatic markers) evoke feeling states that in turn support cognition, decision-making and behavioral adjustment. During decision situations, somatic markers (e.g., changes in heart activity or muscular tension) are generated together with emotional responses and connected to specific behavioral options. They are stored in memory and reactivated when similar situations occur, together with the corresponding options and likely outcomes. As such, somatic markers support decision-making via the endorsement of advantageous and rejection of disadvantageous choices. According to the theory, somatic markers are represented and regulated in central nervous emotion circuits, especially in the ventromedial prefrontal cortex (VMPFC). In decision situations, they can be evoked in two different ways. Within the “body loop”, a particular somatic state is elicited and projected to the cortex by somatosensory afferents; and in the “as-if body loop”, the representation of the somatic state is activated in somatosensory brain areas without generating an actual peripheral physiological change. These processes may occur with or without conscious awareness. Somatic markers are believed to be particularly helpful in situations characterized by high uncertainty and complexity, where they enable rapid experience-driven decision-making (Bechara & Damasio, 2004 ). The Iowa Gambling Task (IGT) is a well established decision-making paradigm developed in the context of the somatic marker hypothesis (Bechara, 2007 ). It resembles real-life decision situations in terms of the uncertainty of outcomes and variable positive or negative consequences. The IGT requires the selection of cards from four decks (A, B, C, D), where each move can be associated with monetary gain or loss. Two decks (A, B) provide high gains and high losses. However, if these decks are selected continuously, a net loss results, such that they are disadvantageous in the long run. The two other decks (C, D) are associated with small gains and small losses but a gain results if they are chosen continuously, making them advantageous. Commonly, subjects acquire the optimal strategy to maximize total gain (i.e., choosing decks C and D and avoiding decks A and B) during execution of the task. Patients with damage to the VMPFC, where somatic markers are believed to be processed, showed impaired decision-making as they continuously chose cards from the disadvantageous decks instead of increasing the number of selections from the advantageous ones (Bechara et al., 1994 , 1999 , 2000 ). Moreover, these patients generated smaller skin conductance responses (SCRs) than healthy individuals, especially in the period preceding card selection (anticipatory SCRs), which was interpreted as suggestive of impaired development of somatic markers. In consideration of the relevance of emotional and somatic processes to decision-making, this study investigated the implications of individual differences in the startle reflex for behavior on the IGT. This defense reflex is typically assessed as the eyeblink that occurs after sudden and intense noise stimulation (Lang et al., 1990 ). Its properties can be quantified via electromyography at the orbicularis oculi muscle and according to the affective state (Bradley & Lang, 2016 ; Oskarsson et al., 2021 ). Numerous studies using emotional pictures demonstrated that the startle reflex response progressively increases during the presentation of pleasant, neutral and unpleasant pictures (e.g., Aluja et al., 2018 ; Bradley et al., 2001 , 2006 ; Larson et al., 2000 ). The same changes can be induced using emotional stimuli like movie scenes, sounds or odors differing in pleasantness (Ehrlichman et al., 1995 ; Jansen & Frijda, 1994 ; Bradley & Lang, 2000 ). Due to its sensitivity to affective valence, the startle reflex is regarded as a reliable physiological marker of emotional state (Lang et al., 1990 ; Grillon & Baas, 2003 ). While other psychophysiological parameters like skin conductance, heart rate or muscle tension merely reflect emotional arousal, the startle reflex is unique in indexing the valence dimension of emotion (Grillon & Baas, 2003 ). The variation in the startle response according to affective valence makes it suitable for investigating the impact of emotion on decision-making. Several studies have investigated the connection between affective state and IGT performance. Building on reports of associations between negative mood and riskier judgements and behaviors (Arkes et al., 1988 ; Nygren, 1998 ), Suhr and Tsanidis (2006) demonstrated that high negative affect, quantified with the Positive and Negative Affect Schedule (PANAS, Watson et al., 1988 ), was related to poor IGT performance independent of personality characteristics. Similarly, Buelow and Suhr ( 2012 ) reported that individuals scoring high for negative affect on the PANAS scale made more disadvantageous and less advantageous decisions. De Vries et al. ( 2008 ) investigated the effects of naturally occurring differences in emotional state, and experimental manipulations thereof, on behavior in the IGT. Both approaches yielded evidence of better performance during a positive than negative emotional state. The association between emotional state and decision-making was explained based on the somatic marker hypothesis; it was argued that a negative affective state results in a tendency toward careful analysis of available information, whereas during a positive affective state individuals tend to rely on intuition and “gut feelings” (Bolte et al., 2003 ; de Vries et al., 2008 ; Wagar & Dixon, 2006 ). In this study, IGT performance was related to the startle response magnitude in healthy individuals. The startle paradigm involved eyeblink responses to noise stimuli during the viewing of pleasant, neutral and unpleasant affective pictures. The main hypothesis pertains to a smaller reflex response in individuals with high IGT performance than in those with low performance. This prediction is informed by the described dependence of startle amplitude on the affective state and the findings of lower decision-making performance during a negative than positive affective state (Buelow & Suhr, 2012 ; de Vries et al., 2008 ; Grillon & Baas, 2003 ). Methods Participants In total, 42 students from the University of Granada (Spain) participated in the study. They were assigned to two groups according to their performance on the IGT (high IGT performance vs. low IGT performance). Therefore, the group was split based on the median IGT score (n = 21 per group; see the Iowa Gambling Task section for computation of the IGT score). The group demographics were as follows: high performance group, 14 men, 7 women; age, M = 20.57 years, SD = 3.30 years; IGT score, M = 29.90, SD = 25.40; low performance group, 16 men, 5 women; age, M = 20.24 years, SD = 4.26 years; IGT score, M = -19.43, SD = 17.86. Participants were only included if they did not suffer from any relevant physical or mental disorders and did not use any psychoactive drugs. Iowa Gambling Task The standard version of the IGT described by Bechara ( 2007 ) was used in the study (see Fig. 1 for task scheme). It was presented on a 22-inch monitor using E-Prime 2.0 software (Pinker, 2015 ). At the beginning of each trial, four virtual card decks (decks A, B, C, D) were concurrently displayed on the screen. Participants selected a card from one deck using the left mouse button. After the selection, the decks disappeared, and two numbers were sequentially displayed for 2 s each. The first number provided information about monetary gain (e.g., + 100 €), and the second one information about loss (e.g., − 300 €), in the respective trial. Each trial was associated with either overall gain (e.g., gain + 300 €, loss – 200 €) or overall loss (e.g., gain + 100 €, loss – 200 €). In total, 100 trials were performed; the task was presented in blocks of 20 trials each with short breaks between them. The intertrial intervals ranged between 1 and 5 s. Decks A and B provided large gains but also large losses. If chosen continuously, these decks led to a net loss (disadvantageous decks). Decks C and D provided modest gains and modest losses, and the choice thereof resulted in long-term net profit (advantageous decks). The current monetary balance was continuously shown on the screen. Participants started the task with a 2,000 € credit of play money. All instructions were given in oral and written form and corresponded to those described by Bechara ( 2007 ). Individual task performance was indexed by the IGT score, computed according to the formula (C + D) – (A + B) (Bechara, 2007 ). The computation of the score was based on all 100 task trials. Preliminary data analysis performed separately for each of the five blocks did not reveal differential connections with the startle reflex; therefore, the final data analysis was only conducted for the 100 trials in their entirety (see Results section for learning curves across the five blocks). Startle reflex paradigm The startle paradigm was also controlled using E-Prime 2.0 software (Pinker, 2015 ); stimulus markers were recorded by a Biopac MP 100 system (Biopac Systems Inc., Goleta, CA). The startle response was triggered by 105 dB white noise stimuli of 50 ms duration, recorded in a wav file, amplified with an IMG Stage Line 2000 amplifier (Monacor, Bremen, Germany) and presented through AKG K240 headphones (Harman, Inc., Garching, Germany; see Fig. 2 for stimuli and timing). A total of 27 noise stimuli were delivered while participants were viewing affective pictures. Therefore, 45 pictures were selected from the International Affective Picture System (IAPS; Moltó et al., 1999 ). Each picture (size 640 × 480 pixels) was displayed for 6 s on a 22-inch monitor at a viewing distance of 50 cm. They depicted persons either in pleasant (e.g., erotica), neutral (e.g., formal interactions) or unpleasant (e.g., mutilations) situations. Per affective category, 15 pictures were chosen with the following codes: pleasant, 4607, 4608, 4651, 4652, 4658, 4659, 4664, 4670, 4680, 4687, 4800, 4810, 4687, 4800, 4810; neutral, 2190, 2214, 2230, 2372, 2383, 2440, 2480, 2485, 2495, 2514, 2840, 7550, 2514, 2840, 7550; unpleasant, 3000, 3010, 3030, 3051, 3053. 3071, 3100, 3110, 3150, 3168, 3170, 3400, 3168, 3170, 3400. The mean normative valence and arousal ratings were as follows; pleasant: valence = 7.08, arousal = 5.73; neutral: valence = 5.28, arousal = 2.84; unpleasant: valence = 1.91, arousal = 6.03. Pictures from the three categories were equivalent in brightness and contrast. During the presentation of 9 of the 15 pictures in each category (random assignment), noise stimuli were delivered 3 s, 3.5 s, 4 s, 4.5 s, 5 s or 5.5 s after picture onset. Intertrial intervals ranged between 2.5 and 5 s. Pictures were presented in blocks according to their affective valence (pleasant, neutral, unpleasant). The presentation order of the three blocks was counterbalanced across participants. Participants were asked to continuously look at the pictures. EMG recording The EMG was recorded from two miniature Ag/AgCl electrodes filled with standard electrode gel and attached to the skin overlying the orbicularis oculi muscle of the left eye. One electrode was attached underneath the pupil and the second one 1 cm lateral to the outer cantus of the eye. The signal was amplified using an EMG100C amplifier (Biopac MP 100) with a gain of 500 and a band pass filter with a low cut-off of 10 Hz and a high cut-off of 500 Hz. Data were stored at a sampling rate of 1000 Hz using AcqKnowledge 3.9 software (Biopac Systems Inc.). The amplitude of the startle response to each of the 27 noise stimuli was quantified as the absolute difference (in µV) between the mean value of a 20 ms baseline starting at stimulus onset and the maximal value during the period from 20 to 150 ms after stimulus onset. The amplitudes were averaged across the nine trials of each affective category. Procedure After completing the informed consent form, participants performed the IGT in the form described above. Subsequently, the EMG electrodes were attached, and the startle paradigm was executed. Finally, participants evaluated the IAPS pictures on the valence and arousal dimensions of the Self-Assessment Manikin scale (Moltó et al., 1999 ). The study procedure complied with the APA ethical standards and the Declaration of Helsinki. All participants provided written informed consent. The Ethical Committee of the University of Granada approved the study protocol (IRB#2994/CEIH/2022). Data analysis For statistical analysis of the startle reflex amplitude, a mixed ANOVA was computed with the between-subjects factor of Group (high IGT performance, low IGT performance) and the within-subjects factor of Picture Category (pleasant, neutral, unpleasant). ANOVAs with the same factors were performed for the SAM ratings of valence and arousal. Only ratings on the pictures during which noises were delivered were included in this analysis. In the ANOVAs, Greenhouse–Geisser correction was applied where necessary. Post-hoc analyses were performed using repeated-measures F-tests. Partial η 2 was used as the measure of effect size. To evaluate linear associations between IGT performance and startle reflex amplitude for the three picture categories, Pearson correlations were computed. Alpha was set at .05 in all analyses. Statistical analyses were carried out using IBM SPSS Statistics (ver. 24; IBM Corp., Armonk, NY). Results IGT learning curves Figure 3 displays the learning curves for the IGT of the two study groups classified according to their task performance. The IGT score is displayed for the five blocks of the task, each comprising 20 trials (computed according to the formula (C + D) – (A + B)). While the score showed a strong increasing trend across the five blocks in the group with high performance, it remained virtually unchanged in the group with low performance. Startle reflex amplitude Figure 4 displays the startle reflex amplitude for both groups and the three affective picture categories. The ANOVA revealed a main effect of the Group factor ( F (1, 40) = 4.91, p = .032, η p 2 = .11); the amplitude was larger overall in the group with low IGT performance than in the group with high IGT performance. A main effect of Picture Category indicated that the amplitude differed according to the affective valence of the pictures in the entire sample ( F (2, 80) = 26.92, p < .001, η p 2 = .40). It was larger for unpleasant than pleasant ( F (1, 41) = 46.28, p < .001, η p 2 = .53) and neutral ( F (1, 41) = 7.94, p = .007, η p 2 = .16) pictures, and for neutral than pleasant ( F (1, 41) = 20.05, p < .001, η p 2 = .33) pictures. The Group × Picture Category interaction did not reach significance ( F (2, 80) = 2.87, p = .062, η p 2 = .067). In the entire sample, the IGT score correlated negatively with the startle reflex amplitude recorded during the presentation of unpleasant (r = − .37, p = .008), neutral (r = − .39, p = .006) and pleasant (r = − .31, p = .025) pictures. Self-Assessment Manikin (SAM) scale Table 1 includes the SAM ratings for the affective pictures (higher values denote more positive valence and greater arousal). The ANOVA for the valence ratings yielded main effects of Group ( F (1, 40) = 7.86, p = .008, η p 2 = .16) and Picture Category ( F (2, 80) = 266.59, p < .001, η p 2 = .87); the interaction effect was not significant ( F (1, 40) = 2.65, p = .085, η p 2 = .062). Valence ratings were most positive for pleasant pictures, followed by neutral and unpleasant pictures (p < .001 for all differences). The Group effect denotes more positive picture evaluations in participants with high IGT performance. The ANOVA for the arousal ratings revealed a main effect of Picture Category ( F (2, 80) = 50.14, p < .001, η p 2 = .56). The Group ( F (1, 40) = 0.04, p = .84, η p 2 = .001) and interaction ( F (1, 40) = 2.87, p = .062, η p 2 = .067) effects were not significant. Pleasant and unpleasant pictures were rated as more arousing than neutral pictures (pleasant vs. neutral: F (1, 41) = 86.90, p < .001, η p 2 = .68; unpleasant vs. neutral: F (1, 41) = 75.70, p < .001, η p 2 = .65); arousal ratings did not differ between pleasant and unpleasant pictures ( F (1, 41) = 0.56, p = .46, η p 2 = .013). Discussion This study investigated for the first time the possible implications of the activity of the startle reflex for decision-making. The eyeblink response to aversive noise stimulation was recorded during the viewing of pleasant, neutral and unpleasant affective pictures in healthy individuals classified according to their performance on the IGT. Participants with low IGT performance exhibited a larger startle response overall than those with high IGT performance. In the entire sample, the response amplitude increased from pleasant to unpleasant pictures. Furthermore, inverse linear associations were seen between IGT performance and the response amplitude during the viewing of pleasant, neutral and unpleasant pictures. The startle reflex involves an automatic response to sudden and intense stimulation that is associated with the mobilization of defensive systems and unpleasant subjective experience (Lang et al., 1990 ). It is regarded as a protective mechanism, facilitating coping with potential threats by interrupting current behaviors and focusing attention on the source of the threat (Oskarsson et al., 2021 ). Though the startle reflex affects the entire body, the eyeblink constitutes the fastest and most reliable component thereof and is therefore commonly assessed in psychophysiological research (Bradley & Lang, 2016 ). The affective modulation of the startle reflex amplitude observed in the present study is in accordance with the literature. A large database substantiates startle potentiation during negative affective states; despite its somewhat smaller extent, attrition of the reflex during positive affect is also widely acknowledged (see Bradley & Lang, 2016 and Grillon & Baas, 2003 for overview). According to the SAM ratings, pleasant and unpleasant pictures were perceived as more arousing than neutral pictures. Nevertheless, the startle response progressively increased across pleasant, neutral and unpleasant pictures. This supports the notion that the reflex changes as a function of emotional valence and is virtually unaffected by arousal (Bradley & Lang, 2016 ; Grillon & Baas, 2003 ). While the startle reflex is characterized as a brainstem reflex, neuroimaging studies in humans suggest a crucial role of the amygdala in its affective modulation (Anders at al., 2004; Kuhn et al., 2020 ). According to the motivational priming hypothesis, defensive mechanisms, such as the startle reflex, are automatically primed during aversive experience; by contrast, positive emotional experience is connected to the inhibition of defensive mechanisms and activation of appetitive motivation (Lang, 1995 ; Lang et al., 1990 ). As illustrated by the learning curves, the group with higher IGT scores showed a strong increase in advantageous, and decrease in disadvantageous, decisions across the five blocks of the task. In contrast, no learning was evident in the group with lower IGT scores. The described connection between the startle reflex and emotional and motivational states may be relevant to the association of the startle response with decision-making. There is evidence that positive and negative emotional states are associated with different cognitive processing modes and specific behaviors in decision situations (Angie et al., 2011 ; Bolte et al., 2003 ). According to the personality systems interaction theory, a negative emotional state supports an analytic processing mode, whereas positive emotional state relates to a holistic processing mode and more intuitive decision-making (Kuhl, 2000 ). In accordance with this reasoning, Bolte et al. ( 2003 ) reported that positive affect improved participants´ ability to make intuitive judgments about the semantic coherence of verbal stimuli; negative affect had the opposite effect. As mentioned previously, individuals also performed more poorly on the IGT during a negative, and better during a positive, emotional state (e.g., Buelow & Suhr, 2012 ; De Vries et al., 2008 ; Suhr & Tsanidis, 2006). With reference to the somatic marker hypothesis, it was claimed that under a positive emotional state, decisions are more likely to be made based on feelings and information arising from within the body (Bolte et al., 2003 ; de Vries et al., 2008 ; Wagar & Dixon, 2006 ). In complex and uncertain situations, such as that simulated by the IGT, unambiguous information enabling deduction of a rational strategy is unavailable; thus, affectively guided and intuitive strategies are more effective (Wagar & Dixon, 2006 ). This is illustrated by the observation that healthy individuals tend to decide advantageously on the task before being aware of the advantageous strategy (Bechara et al., 1997 ). Furthermore, somatic markers (represented by anticipatory SCRs) are developed at a relatively early stage of task execution, and their generation relates positively to performance (Bechara et al., 1996; Wagar & Dixon, 2006 ). In contrast, explicit conscious knowledge of the relative value of the four card desks is gained in later stages (Bechara et al., 1997 ; Maia & McClelland, 2004 ). Considering this, in the IGT, decisions driven by emotion and “gut feelings” (i.e., somatic markers), such as those related to a positive emotional state, may be superior to decisions based on analytic strategies, such as those related to a negative emotional state. As a defense mechanism, the startle reflex is closely associated with the processing of threat and anxiety; hence, individual differences in its magnitude reflect differences in threat-related physiological reactivity (Lang et al., 1990 ). It may be that individuals characterized by high threat-related reactivity also exhibit stronger bodily responses during the IGT, especially when considering risky decisions (decks A and B). In terms of the somatic marker hypothesis, highly reactive individuals would command a larger amount of somatic information, helping to avoid risky and thus disadvantageous decisions. Evidently, this was not the case in this study, as greater startle responses were associated with more frequent instead of less frequent disadvantageous decisions. It may be hypothesized that strong physiological activation does not necessarily imply improved emotional guidance in decision-making. To serve as somatic markers, physiological changes must be linked to behavioral options and, in addition, must be accessible to central nervous and mental processing. This is illustrated by a study concerning the role of interoceptive sensibility in decision-making (Werner et al., 2009b ). Performance on the IGT was compared between individuals with high and low interoceptive sensitivity, assessed via a heartbeat perception task (Schandry, 1981 ). While high interoceptive sensitivity was associated with better IGT performance, heart rate recorded during anticipation of decisions and feedback pertaining to gain and loss did not differ between individuals with high and low interoceptive sensitivity. This underlines that decision-making varies according to the accessibility of somatic feedback rather than its actual magnitude. The extent of affective modulation of the startle reflex was unrelated to IGT performance in this study. Alterations in affective modulation were mainly observed in clinical conditions. While individuals with specific phobias exhibited greater affective modulation than controls (Lang et al., 2005 ), the opposite was reported, for example, in depression and sociopathy (Kaviani et al., 2004 ; Oskarsson et al., 2021 ). This was discussed in terms of emotional and motivational dysregulations in the pathogenetic mechanisms (Grillon & Baas, 2003 ). Some studies also related individual differences in affective startle modulation to psychological features in healthy individuals (Cook et al., 1991 ; Grüsser et al., 2006 ; Vaidyanathan et al., 2008 ); however, according to the present study, individual differences in the response magnitude seem more relevant to decision-making than variations therein according to emotional stimuli. In addition to the impact of emotion on the use of emotional and somatic information during decision-making, top-down effects of high-order cognition on emotional processing should be taken into account in the connection between the startle reflex and decision-making. Decision-making involves weighing multiple alternatives and selecting an advantageous option while reflecting on potential positive and negative consequences; these abilities strongly depend on cognitive control (Fellows, 2004 ; Miller & Cohen, 2001 ). As a neural correlate of cognitive control, the prefrontal cortex plays a key role in decision-making (Miyake et al., 2000 ; Miller & Cohen, 2001 ). The neurovisceral integration model posits a close interaction between the prefrontal cortex and activity in limbic structures, especially in the amygdala (Thayer & Lane, 2008 ). In turn, the amygdala is crucial in the impact of affect on the startle reflex (Anders at al., 2004; Kuhn et al., 2020 ). The amygdala becomes active during conditions of uncertainty; in terms of negative bias, it preferentially responds to threatening information (Cunningham et al., 2008 ). Amygdala activation is regarded as part of a “default response” to uncertainty that corresponds to defense mechanisms like the startle reflex or the fight-and-flight response, protecting the organism and mobilizing energetic resources to ensure survival. Importantly, amygdala activity is inhibited most of the time via projections from the prefrontal cortex. However, inhibition strongly varies among individuals. Differences in prefrontal cortex function modulate top-down control of the amygdala, where poorer prefrontal function is accompanied by weaker inhibition and thus greater amygdala activity (Thayer & Lane, 2008 ). Considering this, larger startle response magnitudes may relate to amygdala disinhibition and greater threat processing due to poorer prefrontal function. According to the SAM scale of valence, the participants in this study with high IGT performance perceived the emotional pictures as more pleasant than those with low IGT performance. This suggests a tendency toward more positive emotional reactivity in these individuals, which does not conflict with the proposed interpretations. A relevant limitation of this study pertains to the lack of assessment of variables that would have facilitated interpretation of the results in terms of relevant psychophysiological mechanisms. Measurements of emotional state during the IGT and subjective responses to noise stimuli could have substantiated the hypothesized role of individual differences in emotional state in the detected associations. In addition, recording of a parameter of autonomic function like electrodermal activity or heart rate during the IGT would have been beneficial. In future research, the role of prefrontal cortex function in the linkage between decision-making and startle reflex activity could be investigated by recording vagally mediated heart rate variability (vmHRV). vmHRV constitutes an index of the integrity of prefrontal processing (Berntson et al., 2016 ; Thayer & Lane, 2008 ). Moreover, individual differences in vmHRV are associated with cognitive control and emotional regulation (Appelhans & Luecken, 2006 ; Bair et al., 2020 , 2022 ; Hansen et al., 2003 ). Another restriction is the relatively small sample size, which limited the power of the statistical tests and thus the possibility of detecting possible small effects. In sum, this study revealed evidence of a connection between startle reflex activity and decision-making in healthy individuals. This association may be explained by individual differences in emotional state, which affect the startle response and modulate cognitive processing modes and decision-making strategies. Moreover, top-down effects of prefrontal cortex function on decision-making, emotional processing and the startle reflex are feasible. The study adds to the research on the peculiarities of the startle reflex in mental disorders like post-traumatic stress disorder, obsessive compulsive disorder, psychopathy or substance abuse (Jurado-Barba et al., 2017 ; Kumari et al., 2001 ; Medina et al., 2001 ; Oskarsson et al., 2021 ), and its associations with personality characteristics like trait anxiety, aggressiveness and reward sensitivity (Aluja et al., 2014 ; Blanch et al, 2014 ; Sege et al., 2018 ; Vaidyanathan et al., 2008 ). The findings illustrate that the startle paradigm may be a useful tool to investigate the interaction between bodily states and higher-order cognitive processing in future psychophysiological research. Table 1 Mean (SD in parentheses) Self-Assessment Manikin (SAM) ratings of valence and arousal in both study groups; higher values denote more positive valence and greater arousal. The presented data are based only on the pictures during which noises were delivered. Pleasant Neutral Unpleasant SAM valence High IGT performance 7.80 (0.96) 5.26 (0.60) 1.96 (1.21) Low IGT performance 6.79 (1.48) 5.35 (0.88) 1.63 (0.76) SAM arousal High IGT performance 5.67 (2.48) 2.42 (1.28) 6.48 (2.10) Low IGT performance 5.87 (1.93) 3.29 (1.38) 5.66 (2.24) Declarations The authors declare that there are no conflicts of interests. The research data is available on request. Author Contribution All authors have contributed equally to research and manuscript preparation and have reviewed the final version of the manuscript. Data Availability The research data is available on request. References Aluja, A., Balada, F., Blanco, E., Lucas, I., & Blanch, A. (2018). Startle reflex modulation by affective face Emoji pictographs. Psychological Research Psychologische Forschung , 84 , 15–22. https://doi.org/10.1007/s00426-018-0991-x Aluja, A., Blanch, A., Blanco, E., & Balada, F. (2014). 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Psychological Review , 97 , 377–395. https://doi.org/10.1037/0033-295x.97.3.377 Lang, P. J., McTeague, L. M., & Cuthbert, B. N. (2005). Fearful imagery and the anxiety disorder spectrum. In B. O. Rothbaum (Ed.), Pathological anxiety: Emotional processing in etiology and treatment (pp. 56–77). Guilford Press. Larson, C. L., Ruffalo, D., Nietert, J. Y., & Davidson, R. J. (2000). Temporal stability of the emotion-modulated startle response. Psychophysiology , 37 , 92–101. https://doi.org/10.1017/s0048577200981344 Maia, T. V., & McClelland, J. L. (2004). A reexamination of the evidence for the somatic marker hypothesis: What participants really know in the Iowa Gambling Task. Proceedings of The National Academy of Sciences , 101 , 16075–16080. https://doi.org/10.1073/pnas.0406666101 Maner, J. K., Richey, J. A., Cromer, K., Mallott, M., Lejuez, C. W., Joiner, T. E., & Schmidt, N. B. (2006). Dispositional anxiety and risk-avoidant decision-making. 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E-Prime 2.0: A guide to clearer, more accurate thinking . Harp. Schandry, R. (1981). Heart beat perception and emotional experience. Psychophysiology , 18 , 483–488. https://doi.org/10.1111/j.1469-8986.1981.tb02486.x Sege, C. T., Bradley, M. M., & Lang, P. J. (2018). Avoidance and escape: Defensive reactivity and trait anxiety. Behaviour Research and Therapy , 104 , 62–68. https://doi.org/10.1016/j.brat.2018.03.002 Suhr, J. A., & Tsanadis, J. (2006). Affect and personality correlates of the Iowa Gambling Task. Personality and Individual Differences , 43 , 27–36. https://doi.org/10.1016/j.paid.2006.11.004 Thayer, J. F., & Lane, R. D. (2008). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews , 33 , 81–88. https://doi.org/10.1016/j.neubiorev.2008.08.004 Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, Adaptation, and Health. Annals of Behavioral Medicine , 37 , 141–153. https://doi.org/10.1007/s12160-009-9101-z Vaidyanathan, U., Patrick, C. J., & Bernat, E. M. (2008). Startle reflex potentiation during aversive picture viewing as an indicator of trait fear. Psychophysiology , 46 , 75–85. https://doi.org/10.1111/j.1469-8986.2008.00751.x Wagar, B. M., & Dixon, M. (2006). Affective guidance in the Iowa Gambling Task. Cognitive Affective & Behavioral Neuroscience , 6 , 277–290. https://doi.org/10.3758/cabn.6.4.277 Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology , 54 , 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 Werner, N. S., Duschek, S., & Schandry, R. (2009a). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5324668","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":370194715,"identity":"498adf4c-71ea-4d51-8879-9b3aba5d0dab","order_by":0,"name":"Azahara Miranda","email":"","orcid":"","institution":"University of Granada","correspondingAuthor":false,"prefix":"","firstName":"Azahara","middleName":"","lastName":"Miranda","suffix":""},{"id":370194716,"identity":"f5fc4a3b-0e1f-47df-a7c2-4640017cbe32","order_by":1,"name":"Stefan Duschek","email":"","orcid":"","institution":"UMIT Tirol - University of Health Sciences and Technology, Hall in Tirol","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Duschek","suffix":""},{"id":370194717,"identity":"a8adf6df-8fd3-46d3-94a8-54083b4dea88","order_by":2,"name":"José Luis Mata","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYBADOVIUM4NJY9K1JDYQrUG3/fzBTzdq7qVvOL/2AcOHP0RoMTuTzCydc6w4d8ON5waMM9uI0XIgmUE6hy0BqOUYAzMvMc4zO/+Y+XfOv4R0A5CWP0Q57EYym3RuW0KCwfk2YEiwEaXlsZl1bl+C4cwbbAwHe4nyy/nEx7dzviXI850/xvjgBzEOQwCJBIYDJGlgYOAnVcMoGAWjYBSMGAAAOXs5VcQb8X8AAAAASUVORK5CYII=","orcid":"","institution":"University of Granada","correspondingAuthor":true,"prefix":"","firstName":"José","middleName":"Luis","lastName":"Mata","suffix":""}],"badges":[],"createdAt":"2024-10-24 09:38:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5324668/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5324668/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00426-025-02114-3","type":"published","date":"2025-04-05T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68764641,"identity":"95f61baa-38de-4b5b-8deb-7bd09fa61ddf","added_by":"auto","created_at":"2024-11-11 19:44:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32157,"visible":true,"origin":"","legend":"\u003cp\u003eTask scheme of the IGT\u003c/p\u003e","description":"","filename":"Figure1741.png","url":"https://assets-eu.researchsquare.com/files/rs-5324668/v1/e6e0f087bfbf85c37a1447b1.png"},{"id":68764642,"identity":"551949fe-1c6e-448c-8bee-435aa13b58ae","added_by":"auto","created_at":"2024-11-11 19:44:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1277914,"visible":true,"origin":"","legend":"\u003cp\u003eStimuli and timing of the startle paradigm\u003c/p\u003e","description":"","filename":"Figure1742.png","url":"https://assets-eu.researchsquare.com/files/rs-5324668/v1/4d1fd54933e0286c3a42c349.png"},{"id":68764640,"identity":"d1b47292-c03a-465c-bbaf-1fa3319d49db","added_by":"auto","created_at":"2024-11-11 19:44:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":32885,"visible":true,"origin":"","legend":"\u003cp\u003eLearning curves on the IGT for participants with high and low task performance (bars represent standard errors of the mean)\u003c/p\u003e","description":"","filename":"Figure1743.png","url":"https://assets-eu.researchsquare.com/files/rs-5324668/v1/e2e07039869a374fda863294.png"},{"id":68764639,"identity":"efaa37cb-2ae6-427e-8d75-146b0c126678","added_by":"auto","created_at":"2024-11-11 19:44:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":34977,"visible":true,"origin":"","legend":"\u003cp\u003eStartle reflex amplitude for the three affective picture categories in participants with high and low IGT performance (bars represent standard errors of the mean)\u003c/p\u003e","description":"","filename":"Figure1744.png","url":"https://assets-eu.researchsquare.com/files/rs-5324668/v1/adbb250cc795bbcd454a4d4d.png"},{"id":80082667,"identity":"9ac1fe1b-54bd-40ca-8646-0d78cdefe205","added_by":"auto","created_at":"2025-04-07 16:09:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2047969,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5324668/v1/3be886a0-1179-4322-9c33-5aee152f0b77.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Linkage between Decision-making and Bodily States: An Investigation Using an Emotional Startle Reflex Paradigm and the Iowa Gambling Task","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs a crucial ability in daily life, decision-making refers to a set of cognitive processes enabling selection of an advantageous response from among an array of available options (Fellows, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Gold \u0026amp; Shadlen, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Psychological research suggested strong involvement of emotional experience in these processes (see Angie et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e for an overview). Positive or negative emotions, as well as emotional regulation abilities, may influence appraisal of the potential consequences of a decision and their respective likelihoods (Werner et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2009a\u003c/span\u003e). For example, anxiety modulates the tolerance for risk in experimental decision-making tasks, where highly anxious individuals tend to choose safer options than low-anxiety individuals (Maner et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Miu et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In further studies, positive affect was related to higher, and negative affect to lower, success levels in decision-making tasks (Buelow \u0026amp; Suhr, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; de Vries et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Suhr \u0026amp; Tsanadis, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrent theories emphasize the role of interactions between the brain and body in emotionally guided decision-making (Damasio, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Thayer et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The somatic marker hypothesis may be most influential in this field (Bechara \u0026amp; Damasio, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The theory posits that neural representations of physiological conditions (somatic markers) evoke feeling states that in turn support cognition, decision-making and behavioral adjustment. During decision situations, somatic markers (e.g., changes in heart activity or muscular tension) are generated together with emotional responses and connected to specific behavioral options. They are stored in memory and reactivated when similar situations occur, together with the corresponding options and likely outcomes. As such, somatic markers support decision-making via the endorsement of advantageous and rejection of disadvantageous choices. According to the theory, somatic markers are represented and regulated in central nervous emotion circuits, especially in the ventromedial prefrontal cortex (VMPFC). In decision situations, they can be evoked in two different ways. Within the \u0026ldquo;body loop\u0026rdquo;, a particular somatic state is elicited and projected to the cortex by somatosensory afferents; and in the \u0026ldquo;as-if body loop\u0026rdquo;, the representation of the somatic state is activated in somatosensory brain areas without generating an actual peripheral physiological change. These processes may occur with or without conscious awareness. Somatic markers are believed to be particularly helpful in situations characterized by high uncertainty and complexity, where they enable rapid experience-driven decision-making (Bechara \u0026amp; Damasio, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Iowa Gambling Task (IGT) is a well established decision-making paradigm developed in the context of the somatic marker hypothesis (Bechara, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). It resembles real-life decision situations in terms of the uncertainty of outcomes and variable positive or negative consequences. The IGT requires the selection of cards from four decks (A, B, C, D), where each move can be associated with monetary gain or loss. Two decks (A, B) provide high gains and high losses. However, if these decks are selected continuously, a net loss results, such that they are disadvantageous in the long run. The two other decks (C, D) are associated with small gains and small losses but a gain results if they are chosen continuously, making them advantageous. Commonly, subjects acquire the optimal strategy to maximize total gain (i.e., choosing decks C and D and avoiding decks A and B) during execution of the task. Patients with damage to the VMPFC, where somatic markers are believed to be processed, showed impaired decision-making as they continuously chose cards from the disadvantageous decks instead of increasing the number of selections from the advantageous ones (Bechara et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1999\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Moreover, these patients generated smaller skin conductance responses (SCRs) than healthy individuals, especially in the period preceding card selection (anticipatory SCRs), which was interpreted as suggestive of impaired development of somatic markers.\u003c/p\u003e \u003cp\u003eIn consideration of the relevance of emotional and somatic processes to decision-making, this study investigated the implications of individual differences in the startle reflex for behavior on the IGT. This defense reflex is typically assessed as the eyeblink that occurs after sudden and intense noise stimulation (Lang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Its properties can be quantified via electromyography at the orbicularis oculi muscle and according to the affective state (Bradley \u0026amp; Lang, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Oskarsson et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Numerous studies using emotional pictures demonstrated that the startle reflex response progressively increases during the presentation of pleasant, neutral and unpleasant pictures (e.g., Aluja et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bradley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Larson et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The same changes can be induced using emotional stimuli like movie scenes, sounds or odors differing in pleasantness (Ehrlichman et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Jansen \u0026amp; Frijda, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Bradley \u0026amp; Lang, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Due to its sensitivity to affective valence, the startle reflex is regarded as a reliable physiological marker of emotional state (Lang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Grillon \u0026amp; Baas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). While other psychophysiological parameters like skin conductance, heart rate or muscle tension merely reflect emotional arousal, the startle reflex is unique in indexing the valence dimension of emotion (Grillon \u0026amp; Baas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe variation in the startle response according to affective valence makes it suitable for investigating the impact of emotion on decision-making. Several studies have investigated the connection between affective state and IGT performance. Building on reports of associations between negative mood and riskier judgements and behaviors (Arkes et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Nygren, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), Suhr and Tsanidis (2006) demonstrated that high negative affect, quantified with the Positive and Negative Affect Schedule (PANAS, Watson et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), was related to poor IGT performance independent of personality characteristics. Similarly, Buelow and Suhr (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) reported that individuals scoring high for negative affect on the PANAS scale made more disadvantageous and less advantageous decisions. De Vries et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) investigated the effects of naturally occurring differences in emotional state, and experimental manipulations thereof, on behavior in the IGT. Both approaches yielded evidence of better performance during a positive than negative emotional state. The association between emotional state and decision-making was explained based on the somatic marker hypothesis; it was argued that a negative affective state results in a tendency toward careful analysis of available information, whereas during a positive affective state individuals tend to rely on intuition and \u0026ldquo;gut feelings\u0026rdquo; (Bolte et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; de Vries et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Wagar \u0026amp; Dixon, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, IGT performance was related to the startle response magnitude in healthy individuals. The startle paradigm involved eyeblink responses to noise stimuli during the viewing of pleasant, neutral and unpleasant affective pictures. The main hypothesis pertains to a smaller reflex response in individuals with high IGT performance than in those with low performance. This prediction is informed by the described dependence of startle amplitude on the affective state and the findings of lower decision-making performance during a negative than positive affective state (Buelow \u0026amp; Suhr, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; de Vries et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Grillon \u0026amp; Baas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003e In total, 42 students from the University of Granada (Spain) participated in the study. They were assigned to two groups according to their performance on the IGT (high IGT performance vs. low IGT performance). Therefore, the group was split based on the median IGT score (n\u0026thinsp;=\u0026thinsp;21 per group; see the \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003eIowa Gambling Task\u003c/span\u003e section for computation of the IGT score). The group demographics were as follows: high performance group, 14 men, 7 women; age, M\u0026thinsp;=\u0026thinsp;20.57 years, SD\u0026thinsp;=\u0026thinsp;3.30 years; IGT score, M\u0026thinsp;=\u0026thinsp;29.90, SD\u0026thinsp;=\u0026thinsp;25.40; low performance group, 16 men, 5 women; age, M\u0026thinsp;=\u0026thinsp;20.24 years, SD\u0026thinsp;=\u0026thinsp;4.26 years; IGT score, M = -19.43, SD\u0026thinsp;=\u0026thinsp;17.86. Participants were only included if they did not suffer from any relevant physical or mental disorders and did not use any psychoactive drugs.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIowa Gambling Task\u003c/h3\u003e\n\u003cp\u003eThe standard version of the IGT described by Bechara (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) was used in the study (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for task scheme). It was presented on a 22-inch monitor using E-Prime 2.0 software (Pinker, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). At the beginning of each trial, four virtual card decks (decks A, B, C, D) were concurrently displayed on the screen. Participants selected a card from one deck using the left mouse button. After the selection, the decks disappeared, and two numbers were sequentially displayed for 2 s each. The first number provided information about monetary gain (e.g., + 100 \u0026euro;), and the second one information about loss (e.g., \u0026minus; 300 \u0026euro;), in the respective trial. Each trial was associated with either overall gain (e.g., gain\u0026thinsp;+\u0026thinsp;300 \u0026euro;, loss \u0026ndash; 200 \u0026euro;) or overall loss (e.g., gain\u0026thinsp;+\u0026thinsp;100 \u0026euro;, loss \u0026ndash; 200 \u0026euro;). In total, 100 trials were performed; the task was presented in blocks of 20 trials each with short breaks between them. The intertrial intervals ranged between 1 and 5 s. Decks A and B provided large gains but also large losses. If chosen continuously, these decks led to a net loss (disadvantageous decks). Decks C and D provided modest gains and modest losses, and the choice thereof resulted in long-term net profit (advantageous decks). The current monetary balance was continuously shown on the screen. Participants started the task with a 2,000 \u0026euro; credit of play money. All instructions were given in oral and written form and corresponded to those described by Bechara (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Individual task performance was indexed by the IGT score, computed according to the formula (C\u0026thinsp;+\u0026thinsp;D) \u0026ndash; (A\u0026thinsp;+\u0026thinsp;B) (Bechara, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The computation of the score was based on all 100 task trials. Preliminary data analysis performed separately for each of the five blocks did not reveal differential connections with the startle reflex; therefore, the final data analysis was only conducted for the 100 trials in their entirety (see \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003eResults\u003c/span\u003e section for learning curves across the five blocks).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eStartle reflex paradigm\u003c/h3\u003e\n\u003cp\u003eThe startle paradigm was also controlled using E-Prime 2.0 software (Pinker, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); stimulus markers were recorded by a Biopac MP 100 system (Biopac Systems Inc., Goleta, CA). The startle response was triggered by 105 dB white noise stimuli of 50 ms duration, recorded in a wav file, amplified with an IMG Stage Line 2000 amplifier (Monacor, Bremen, Germany) and presented through AKG K240 headphones (Harman, Inc., Garching, Germany; see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e for stimuli and timing). A total of 27 noise stimuli were delivered while participants were viewing affective pictures.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTherefore, 45 pictures were selected from the International Affective Picture System (IAPS; Molt\u0026oacute; et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Each picture (size 640 \u0026times; 480 pixels) was displayed for 6 s on a 22-inch monitor at a viewing distance of 50 cm. They depicted persons either in pleasant (e.g., erotica), neutral (e.g., formal interactions) or unpleasant (e.g., mutilations) situations. Per affective category, 15 pictures were chosen with the following codes: pleasant, 4607, 4608, 4651, 4652, 4658, 4659, 4664, 4670, 4680, 4687, 4800, 4810, 4687, 4800, 4810; neutral, 2190, 2214, 2230, 2372, 2383, 2440, 2480, 2485, 2495, 2514, 2840, 7550, 2514, 2840, 7550; unpleasant, 3000, 3010, 3030, 3051, 3053. 3071, 3100, 3110, 3150, 3168, 3170, 3400, 3168, 3170, 3400. The mean normative valence and arousal ratings were as follows; pleasant: valence\u0026thinsp;=\u0026thinsp;7.08, arousal\u0026thinsp;=\u0026thinsp;5.73; neutral: valence\u0026thinsp;=\u0026thinsp;5.28, arousal\u0026thinsp;=\u0026thinsp;2.84; unpleasant: valence\u0026thinsp;=\u0026thinsp;1.91, arousal\u0026thinsp;=\u0026thinsp;6.03. Pictures from the three categories were equivalent in brightness and contrast. During the presentation of 9 of the 15 pictures in each category (random assignment), noise stimuli were delivered 3 s, 3.5 s, 4 s, 4.5 s, 5 s or 5.5 s after picture onset. Intertrial intervals ranged between 2.5 and 5 s. Pictures were presented in blocks according to their affective valence (pleasant, neutral, unpleasant). The presentation order of the three blocks was counterbalanced across participants. Participants were asked to continuously look at the pictures.\u003c/p\u003e\n\u003ch3\u003eEMG recording\u003c/h3\u003e\n\u003cp\u003eThe EMG was recorded from two miniature Ag/AgCl electrodes filled with standard electrode gel and attached to the skin overlying the orbicularis oculi muscle of the left eye. One electrode was attached underneath the pupil and the second one 1 cm lateral to the outer cantus of the eye. The signal was amplified using an EMG100C amplifier (Biopac MP 100) with a gain of 500 and a band pass filter with a low cut-off of 10 Hz and a high cut-off of 500 Hz. Data were stored at a sampling rate of 1000 Hz using AcqKnowledge 3.9 software (Biopac Systems Inc.).\u003c/p\u003e \u003cp\u003eThe amplitude of the startle response to each of the 27 noise stimuli was quantified as the absolute difference (in \u0026micro;V) between the mean value of a 20 ms baseline starting at stimulus onset and the maximal value during the period from 20 to 150 ms after stimulus onset. The amplitudes were averaged across the nine trials of each affective category.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003e After completing the informed consent form, participants performed the IGT in the form described above. Subsequently, the EMG electrodes were attached, and the startle paradigm was executed. Finally, participants evaluated the IAPS pictures on the valence and arousal dimensions of the Self-Assessment Manikin scale (Molt\u0026oacute; et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The study procedure complied with the APA ethical standards and the Declaration of Helsinki. All participants provided written informed consent. The Ethical Committee of the University of Granada approved the study protocol (IRB#2994/CEIH/2022).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eFor statistical analysis of the startle reflex amplitude, a mixed ANOVA was computed with the between-subjects factor of Group (high IGT performance, low IGT performance) and the within-subjects factor of Picture Category (pleasant, neutral, unpleasant). ANOVAs with the same factors were performed for the SAM ratings of valence and arousal. Only ratings on the pictures during which noises were delivered were included in this analysis. In the ANOVAs, Greenhouse\u0026ndash;Geisser correction was applied where necessary. Post-hoc analyses were performed using repeated-measures F-tests. Partial η\u003csup\u003e2\u003c/sup\u003e was used as the measure of effect size. To evaluate linear associations between IGT performance and startle reflex amplitude for the three picture categories, Pearson correlations were computed. Alpha was set at .05 in all analyses. Statistical analyses were carried out using IBM SPSS Statistics (ver. 24; IBM Corp., Armonk, NY).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eIGT learning curves\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the learning curves for the IGT of the two study groups classified according to their task performance. The IGT score is displayed for the five blocks of the task, each comprising 20 trials (computed according to the formula (C\u0026thinsp;+\u0026thinsp;D) \u0026ndash; (A\u0026thinsp;+\u0026thinsp;B)). While the score showed a strong increasing trend across the five blocks in the group with high performance, it remained virtually unchanged in the group with low performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStartle reflex amplitude\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displays the startle reflex amplitude for both groups and the three affective picture categories. The ANOVA revealed a main effect of the Group factor (\u003cem\u003eF\u003c/em\u003e(1, 40)\u0026thinsp;=\u0026thinsp;4.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.032, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.11); the amplitude was larger overall in the group with low IGT performance than in the group with high IGT performance. A main effect of Picture Category indicated that the amplitude differed according to the affective valence of the pictures in the entire sample (\u003cem\u003eF\u003c/em\u003e(2, 80)\u0026thinsp;=\u0026thinsp;26.92, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.40). It was larger for unpleasant than pleasant (\u003cem\u003eF\u003c/em\u003e(1, 41)\u0026thinsp;=\u0026thinsp;46.28, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.53) and neutral (\u003cem\u003eF\u003c/em\u003e(1, 41)\u0026thinsp;=\u0026thinsp;7.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.007, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.16) pictures, and for neutral than pleasant (\u003cem\u003eF\u003c/em\u003e(1, 41)\u0026thinsp;=\u0026thinsp;20.05, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.33) pictures. The Group \u0026times; Picture Category interaction did not reach significance (\u003cem\u003eF\u003c/em\u003e (2, 80)\u0026thinsp;=\u0026thinsp;2.87, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.062, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.067).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the entire sample, the IGT score correlated negatively with the startle reflex amplitude recorded during the presentation of unpleasant (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.37, p\u0026thinsp;=\u0026thinsp;.008), neutral (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.39, p\u0026thinsp;=\u0026thinsp;.006) and pleasant (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.31, p\u0026thinsp;=\u0026thinsp;.025) pictures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSelf-Assessment Manikin (SAM) scale\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e includes the SAM ratings for the affective pictures (higher values denote more positive valence and greater arousal). The ANOVA for the valence ratings yielded main effects of Group (\u003cem\u003eF\u003c/em\u003e(1, 40)\u0026thinsp;=\u0026thinsp;7.86, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.008, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.16) and Picture Category (\u003cem\u003eF\u003c/em\u003e(2, 80)\u0026thinsp;=\u0026thinsp;266.59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.87); the interaction effect was not significant (\u003cem\u003eF\u003c/em\u003e(1, 40)\u0026thinsp;=\u0026thinsp;2.65, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.085, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.062). Valence ratings were most positive for pleasant pictures, followed by neutral and unpleasant pictures (p\u0026thinsp;\u0026lt;\u0026thinsp;.001 for all differences). The Group effect denotes more positive picture evaluations in participants with high IGT performance. The ANOVA for the arousal ratings revealed a main effect of Picture Category (\u003cem\u003eF\u003c/em\u003e(2, 80)\u0026thinsp;=\u0026thinsp;50.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.56). The Group (\u003cem\u003eF\u003c/em\u003e(1, 40)\u0026thinsp;=\u0026thinsp;0.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.84, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.001) and interaction (\u003cem\u003eF\u003c/em\u003e(1, 40)\u0026thinsp;=\u0026thinsp;2.87, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.062, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.067) effects were not significant. Pleasant and unpleasant pictures were rated as more arousing than neutral pictures (pleasant vs. neutral: \u003cem\u003eF\u003c/em\u003e(1, 41)\u0026thinsp;=\u0026thinsp;86.90, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.68; unpleasant vs. neutral: \u003cem\u003eF\u003c/em\u003e(1, 41)\u0026thinsp;=\u0026thinsp;75.70, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.65); arousal ratings did not differ between pleasant and unpleasant pictures (\u003cem\u003eF\u003c/em\u003e(1, 41)\u0026thinsp;=\u0026thinsp;0.56, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.46, \u003cem\u003eη\u003c/em\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.013).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated for the first time the possible implications of the activity of the startle reflex for decision-making. The eyeblink response to aversive noise stimulation was recorded during the viewing of pleasant, neutral and unpleasant affective pictures in healthy individuals classified according to their performance on the IGT. Participants with low IGT performance exhibited a larger startle response overall than those with high IGT performance. In the entire sample, the response amplitude increased from pleasant to unpleasant pictures. Furthermore, inverse linear associations were seen between IGT performance and the response amplitude during the viewing of pleasant, neutral and unpleasant pictures.\u003c/p\u003e \u003cp\u003eThe startle reflex involves an automatic response to sudden and intense stimulation that is associated with the mobilization of defensive systems and unpleasant subjective experience (Lang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). It is regarded as a protective mechanism, facilitating coping with potential threats by interrupting current behaviors and focusing attention on the source of the threat (Oskarsson et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Though the startle reflex affects the entire body, the eyeblink constitutes the fastest and most reliable component thereof and is therefore commonly assessed in psychophysiological research (Bradley \u0026amp; Lang, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The affective modulation of the startle reflex amplitude observed in the present study is in accordance with the literature. A large database substantiates startle potentiation during negative affective states; despite its somewhat smaller extent, attrition of the reflex during positive affect is also widely acknowledged (see Bradley \u0026amp; Lang, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e and Grillon \u0026amp; Baas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e for overview). According to the SAM ratings, pleasant and unpleasant pictures were perceived as more arousing than neutral pictures. Nevertheless, the startle response progressively increased across pleasant, neutral and unpleasant pictures. This supports the notion that the reflex changes as a function of emotional valence and is virtually unaffected by arousal (Bradley \u0026amp; Lang, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Grillon \u0026amp; Baas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). While the startle reflex is characterized as a brainstem reflex, neuroimaging studies in humans suggest a crucial role of the amygdala in its affective modulation (Anders at al., 2004; Kuhn et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to the motivational priming hypothesis, defensive mechanisms, such as the startle reflex, are automatically primed during aversive experience; by contrast, positive emotional experience is connected to the inhibition of defensive mechanisms and activation of appetitive motivation (Lang, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Lang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs illustrated by the learning curves, the group with higher IGT scores showed a strong increase in advantageous, and decrease in disadvantageous, decisions across the five blocks of the task. In contrast, no learning was evident in the group with lower IGT scores. The described connection between the startle reflex and emotional and motivational states may be relevant to the association of the startle response with decision-making. There is evidence that positive and negative emotional states are associated with different cognitive processing modes and specific behaviors in decision situations (Angie et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bolte et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). According to the personality systems interaction theory, a negative emotional state supports an analytic processing mode, whereas positive emotional state relates to a holistic processing mode and more intuitive decision-making (Kuhl, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In accordance with this reasoning, Bolte et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) reported that positive affect improved participants\u0026acute; ability to make intuitive judgments about the semantic coherence of verbal stimuli; negative affect had the opposite effect. As mentioned previously, individuals also performed more poorly on the IGT during a negative, and better during a positive, emotional state (e.g., Buelow \u0026amp; Suhr, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; De Vries et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Suhr \u0026amp; Tsanidis, 2006). With reference to the somatic marker hypothesis, it was claimed that under a positive emotional state, decisions are more likely to be made based on feelings and information arising from within the body (Bolte et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; de Vries et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Wagar \u0026amp; Dixon, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In complex and uncertain situations, such as that simulated by the IGT, unambiguous information enabling deduction of a rational strategy is unavailable; thus, affectively guided and intuitive strategies are more effective (Wagar \u0026amp; Dixon, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This is illustrated by the observation that healthy individuals tend to decide advantageously on the task before being aware of the advantageous strategy (Bechara et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Furthermore, somatic markers (represented by anticipatory SCRs) are developed at a relatively early stage of task execution, and their generation relates positively to performance (Bechara et al., 1996; Wagar \u0026amp; Dixon, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In contrast, explicit conscious knowledge of the relative value of the four card desks is gained in later stages (Bechara et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Maia \u0026amp; McClelland, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Considering this, in the IGT, decisions driven by emotion and \u0026ldquo;gut feelings\u0026rdquo; (i.e., somatic markers), such as those related to a positive emotional state, may be superior to decisions based on analytic strategies, such as those related to a negative emotional state.\u003c/p\u003e \u003cp\u003eAs a defense mechanism, the startle reflex is closely associated with the processing of threat and anxiety; hence, individual differences in its magnitude reflect differences in threat-related physiological reactivity (Lang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). It may be that individuals characterized by high threat-related reactivity also exhibit stronger bodily responses during the IGT, especially when considering risky decisions (decks A and B). In terms of the somatic marker hypothesis, highly reactive individuals would command a larger amount of somatic information, helping to avoid risky and thus disadvantageous decisions. Evidently, this was not the case in this study, as greater startle responses were associated with more frequent instead of less frequent disadvantageous decisions. It may be hypothesized that strong physiological activation does not necessarily imply improved emotional guidance in decision-making. To serve as somatic markers, physiological changes must be linked to behavioral options and, in addition, must be accessible to central nervous and mental processing. This is illustrated by a study concerning the role of interoceptive sensibility in decision-making (Werner et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2009b\u003c/span\u003e). Performance on the IGT was compared between individuals with high and low interoceptive sensitivity, assessed via a heartbeat perception task (Schandry, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). While high interoceptive sensitivity was associated with better IGT performance, heart rate recorded during anticipation of decisions and feedback pertaining to gain and loss did not differ between individuals with high and low interoceptive sensitivity. This underlines that decision-making varies according to the accessibility of somatic feedback rather than its actual magnitude.\u003c/p\u003e \u003cp\u003eThe extent of affective modulation of the startle reflex was unrelated to IGT performance in this study. Alterations in affective modulation were mainly observed in clinical conditions. While individuals with specific phobias exhibited greater affective modulation than controls (Lang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), the opposite was reported, for example, in depression and sociopathy (Kaviani et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Oskarsson et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This was discussed in terms of emotional and motivational dysregulations in the pathogenetic mechanisms (Grillon \u0026amp; Baas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Some studies also related individual differences in affective startle modulation to psychological features in healthy individuals (Cook et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Gr\u0026uuml;sser et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Vaidyanathan et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2008\u003c/span\u003e); however, according to the present study, individual differences in the response magnitude seem more relevant to decision-making than variations therein according to emotional stimuli.\u003c/p\u003e \u003cp\u003eIn addition to the impact of emotion on the use of emotional and somatic information during decision-making, top-down effects of high-order cognition on emotional processing should be taken into account in the connection between the startle reflex and decision-making. Decision-making involves weighing multiple alternatives and selecting an advantageous option while reflecting on potential positive and negative consequences; these abilities strongly depend on cognitive control (Fellows, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Miller \u0026amp; Cohen, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). As a neural correlate of cognitive control, the prefrontal cortex plays a key role in decision-making (Miyake et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Miller \u0026amp; Cohen, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The neurovisceral integration model posits a close interaction between the prefrontal cortex and activity in limbic structures, especially in the amygdala (Thayer \u0026amp; Lane, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In turn, the amygdala is crucial in the impact of affect on the startle reflex (Anders at al., 2004; Kuhn et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The amygdala becomes active during conditions of uncertainty; in terms of negative bias, it preferentially responds to threatening information (Cunningham et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Amygdala activation is regarded as part of a \u0026ldquo;default response\u0026rdquo; to uncertainty that corresponds to defense mechanisms like the startle reflex or the fight-and-flight response, protecting the organism and mobilizing energetic resources to ensure survival. Importantly, amygdala activity is inhibited most of the time via projections from the prefrontal cortex. However, inhibition strongly varies among individuals. Differences in prefrontal cortex function modulate top-down control of the amygdala, where poorer prefrontal function is accompanied by weaker inhibition and thus greater amygdala activity (Thayer \u0026amp; Lane, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Considering this, larger startle response magnitudes may relate to amygdala disinhibition and greater threat processing due to poorer prefrontal function.\u003c/p\u003e \u003cp\u003e According to the SAM scale of valence, the participants in this study with high IGT performance perceived the emotional pictures as more pleasant than those with low IGT performance. This suggests a tendency toward more positive emotional reactivity in these individuals, which does not conflict with the proposed interpretations. A relevant limitation of this study pertains to the lack of assessment of variables that would have facilitated interpretation of the results in terms of relevant psychophysiological mechanisms. Measurements of emotional state during the IGT and subjective responses to noise stimuli could have substantiated the hypothesized role of individual differences in emotional state in the detected associations. In addition, recording of a parameter of autonomic function like electrodermal activity or heart rate during the IGT would have been beneficial. In future research, the role of prefrontal cortex function in the linkage between decision-making and startle reflex activity could be investigated by recording vagally mediated heart rate variability (vmHRV). vmHRV constitutes an index of the integrity of prefrontal processing (Berntson et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Thayer \u0026amp; Lane, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Moreover, individual differences in vmHRV are associated with cognitive control and emotional regulation (Appelhans \u0026amp; Luecken, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Bair et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hansen et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Another restriction is the relatively small sample size, which limited the power of the statistical tests and thus the possibility of detecting possible small effects.\u003c/p\u003e \u003cp\u003eIn sum, this study revealed evidence of a connection between startle reflex activity and decision-making in healthy individuals. This association may be explained by individual differences in emotional state, which affect the startle response and modulate cognitive processing modes and decision-making strategies. Moreover, top-down effects of prefrontal cortex function on decision-making, emotional processing and the startle reflex are feasible. The study adds to the research on the peculiarities of the startle reflex in mental disorders like post-traumatic stress disorder, obsessive compulsive disorder, psychopathy or substance abuse (Jurado-Barba et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kumari et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Medina et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Oskarsson et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and its associations with personality characteristics like trait anxiety, aggressiveness and reward sensitivity (Aluja et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Blanch et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sege et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Vaidyanathan et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The findings illustrate that the startle paradigm may be a useful tool to investigate the interaction between bodily states and higher-order cognitive processing in future psychophysiological research.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean (SD in parentheses) Self-Assessment Manikin (SAM) ratings of valence and arousal in both study groups; higher values denote more positive valence and greater arousal. The presented data are based only on the pictures during which noises were delivered.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePleasant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnpleasant\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAM valence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh IGT performance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.80 (0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.26 (0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.96 (1.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow IGT performance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.79 (1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.35 (0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.63 (0.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSAM arousal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh IGT performance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.67 (2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.42 (1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.48 (2.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow IGT performance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.87 (1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.29 (1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.66 (2.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that there are no conflicts of interests.\u003c/p\u003e\n\u003cp\u003eThe research data is available on request.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors have contributed equally to research and manuscript preparation and have reviewed the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe research data is available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAluja, A., Balada, F., Blanco, E., Lucas, I., \u0026amp; Blanch, A. 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Relationships between affective states and decision-making. \u003cem\u003eInternational Journal of Psychophysiology\u003c/em\u003e, \u003cem\u003e74\u003c/em\u003e, 259\u0026ndash;265. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijpsycho.2009.09.010\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpsycho.2009.09.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWerner, N. S., Jung, K., Duschek, S., \u0026amp; Schandry, R. (2009b). Enhanced cardiac perception is associated with benefits in decision-making. \u003cem\u003ePsychophysiology\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e, 1123\u0026ndash;1129. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1469-8986.2009.00855.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1469-8986.2009.00855.x\" 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":"psychological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prpf","sideBox":"Learn more about [Psychological Research](http://link.springer.com/journal/426)","snPcode":"426","submissionUrl":"https://submission.nature.com/new-submission/426/3","title":"Psychological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"startle reflex, decision-making, emotional state, Iowa Gambling Task, somatic marker hypothesis","lastPublishedDoi":"10.21203/rs.3.rs-5324668/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5324668/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTheories such as the somatic marker hypothesis posit that emotions and feedback from bodily states support higher cognition and decision-making. This study investigated the connection between decision-making and activity of the startle reflex, a defense reflex that is sensitive to emotional states. Decision-making was assessed using the Iowa Gambling Task (IGT), which simulates real-life decision-making with respect to complexity and uncertainty. The startle reflex was quantified, via electromyography, as the eyeblink following intense noise stimulation during the viewing of pleasant, neutral, and unpleasant emotional pictures. Forty-two healthy participants were classified according to their performance on the IGT using the median-split method. In the entire sample, the startle response amplitude progressively increased from pleasant to unpleasant picture exposure. Participants with high IGT performance exhibited smaller response amplitudes than those with low IGT performance, independent of picture valence. Furthermore, inverse linear associations were seen between IGT performance and response amplitudes. The association between decision-making and startle reflex activity may be mediated by individual differences in emotional state. According to previous studies, a positive emotional state, as opposed to a negative emotional state, relates to smaller startle amplitudes and a preference for decision-making strategies based on intuition and body-related information (i.e., somatic markers), which are beneficial in situations involving complex and uncertain decisions. Moreover, an impact of individual differences in prefrontal cortex function on decision-making and startle reflex activity is feasible. The startle paradigm may be a useful tool to investigate the interaction between bodily states and higher-order cognitive processing in future research.\u003c/p\u003e","manuscriptTitle":"The Linkage between Decision-making and Bodily States: An Investigation Using an Emotional Startle Reflex Paradigm and the Iowa Gambling Task","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-11 19:44:05","doi":"10.21203/rs.3.rs-5324668/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-19T00:11:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-18T17:28:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9233930567486567806526960970091557352","date":"2025-02-10T07:32:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-01T04:41:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88811741968631759405734134176991100271","date":"2025-01-23T01:57:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-19T00:18:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-16T00:03:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-25T03:18:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Psychological Research","date":"2024-10-24T09:31:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"psychological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prpf","sideBox":"Learn more about [Psychological Research](http://link.springer.com/journal/426)","snPcode":"426","submissionUrl":"https://submission.nature.com/new-submission/426/3","title":"Psychological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c9b698c0-2b10-472d-822c-6e660b349558","owner":[],"postedDate":"November 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-07T16:07:59+00:00","versionOfRecord":{"articleIdentity":"rs-5324668","link":"https://doi.org/10.1007/s00426-025-02114-3","journal":{"identity":"psychological-research","isVorOnly":false,"title":"Psychological Research"},"publishedOn":"2025-04-05 15:57:04","publishedOnDateReadable":"April 5th, 2025"},"versionCreatedAt":"2024-11-11 19:44:05","video":"","vorDoi":"10.1007/s00426-025-02114-3","vorDoiUrl":"https://doi.org/10.1007/s00426-025-02114-3","workflowStages":[]},"version":"v1","identity":"rs-5324668","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5324668","identity":"rs-5324668","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}