Multiple aspects of the stress response under social evaluative threat: An electrophysiological investigation

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1 Psychoneuroendocrinology (2) 33, Available at journal homepage: Multiple aspects of the stress response under social evaluative threat: An electrophysiological investigation James F. Cavanagh, John J.B. Allen 1 Department of Psychology, University of Arizona, 153 University Avenue, Tucson, AZ, USA Received 2 April 27; received in revised form 14 September 27; accepted 25 September 27 KEYWORDS Stress; Cortisol; ERN; Anterior cingulate; Social evaluative threat; Emotion Summary Affective traits and states may be important moderators of stress reactivity, providing insight into stress-related consequences on cognitive functioning. This study assessed cognitive control processes using response-related brain electrical activities the errorrelated negativity (ERN) and error positivity (Pe) that are sensitive to trait and state affect. To assess the role of cognitive control in affective and cortisol reactivity to social evaluative threat, 55 undergraduates first completed a standard task designed to elicit the ERN in order to index baseline error monitoring. Participants then performed a difficult mathematical task designed to elicit the ERN under conditions of exposed failure and social evaluation. Baseline ERN amplitude predicted future cortisol reactivity to social evaluative threat in highly punishment-sensitive individuals (high self-reported Behavioral Inhibition System: Carver and White [1994. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. J. Pers. Soc. Psych. 67, ], although the presence of outliers suggest the need for replication. The math stress ERN amplitude was diminished in direct relationship to trait (punishment sensitivity) and state (fear and shame) negative affect. Individuals high in punishment sensitivity also showed specific deficits in task performance following error feedback under stress. High state affect related to a larger Pe amplitude. Results are interpreted as consequences of different motivational and affective reactivities under social evaluative threat. & 27 Elsevier Ltd. All rights reserved. Corresponding author. Tel.: addresses: jimcav@ .arizona.edu (J.F. Cavanagh), jallen@ .arizona.edu (J.J.B. Allen). 1 Tel.: Introduction Individual differences in stress reactivity may be strongly moderated by both vulnerability to distress and the concurrent emotional reaction. Some stress responsive /$ - see front matter & 27 Elsevier Ltd. All rights reserved. doi:1.116/j.psyneuen

2 42 J.F. Cavanagh, J.J.B. Allen phenotypes may prove to be optimal for health and wellbeing, where others may aggregate into a burden on wellbeing with consequences for physical and mental health. This burden has been defined by McEwen (199) as allostatic load, which offers a theoretical basis to interpret the health consequences of different stress reactive phenotypes. Examinations of stable (trait) and situational (state) variables may reveal mechanisms that interact to influence allostatic reactivities to social stress. However, selfreported affect has proven inadequate to reliably predict allostatic consequences of stress, such as cortisol mobilization via the hypothalamic pituitary adrenal (HPA) axis. Because the HPA axis is stimulated during social stress via a limbic circuit (Gold et al., 22; Kudielka and Kirschbaum, 25), it may be fruitful to utilize non-invasive measurements of affect-sensitive psychophysiology to monitor the role of cognitive control and affect systems involved in the diathesis/stress interactions that determine hormonal mobilization under stress. Manipulations such as the Trier Social Stress Task (TSST: Kirschbaum et al., 1993) are often utilized to elicit HPA axis reactivity, but social stressors are also powerful elicitors of emotion. Kemeny (23) and colleagues (Dickerson et al., 24; Kemeny et al., 24) have highlighted the importance of emotion specificity and cognitive appraisals in determining psychobiological reactivities. Specifically, the elicitation of shame has been hypothesized to be a focal determinant of HPA reactivity during social evaluative threat (Gruenewald et al., 24; Dickerson and Kemeny, 24), which may signal defeat and diminished social status (Dickerson et al., 24). Defeat and social submission share common psychobiological characteristics with depressive disorders and withdrawal-related emotionality (Gilbert et al., 22; Sloman et al., 23). Withdrawal-related affective reactions such as shame and fear may contribute to the negative self-evaluation under social evaluation (Dickerson et al., 24). An important difference between shame and fear is the social nature of shame, and the Social Self Preservation Theory (Dickerson et al., 24) highlights the importance of social emotions (over basic emotions such as fear) as determinants of the HPA response to social stress. It remains to be seen if measures of shame reliably correlate with HPA axis end-products such as salivary cortisol. Many retrospective self-report indices of emotion have failed to reliably predict HPA reactivity in the extant literature (Kudielka and Kirschbaum, 25; Lerner et al., 25). Lerner et al. (25) have shown that frequent facial expressions of fear during a TSST predict larger autonomic nervous system (ANS) and HPA reactivities, whereas facial expressions of indignation (anger and disgust) predict lower ANS and HPA reactivities. Although retrospective self-reported affect correlated with concurrent facial affect to the TSST in Lerner et al. (25), the self-report variables did not independently predict biological stress reactivities. Due to the difficulty in measuring social emotions such as shame, and the evidence that basic emotions also contribute to biological reactivities under stress, measurements of affect-sensitive physiology may offer unique predictive perspectives on HPA reactivity to social evaluative threat. The varying effects of stress on performance and arousal are well described as a classic inverted U, but little research has investigated individual differences in the psychobiological response that differentiates facilitative from debilitating effects of stress. Different cardiovascular responses to stress have been found to be dependent on task mastery (Blascovich et al., 1999) and individual differences in selfesteem (Seery et al., 24), which are interpreted as perceptions of challenge (facilitative) or threat (debilitative). Central nervous system (CNS) indices sensitive to signals of punishment and negative feedback may be especially well-suited for further assessments, as the HPA axis is stimulated during social stress via a limbic circuit involving the amygdala and medial prefrontal cortex (Gold et al., 22; Kudielka and Kirschbaum, 25). Measurements of neural activities in these regions may reveal processes by which emotional perturbation affects HPA reactivity. The medial prefrontal cortex and anterior cingulate cortex (ACC) are sensitive to a multitude of affectively weighted cognitive control functions, including physical pain sensitivity, social and emotional pain sensitivity and expectancy violations representing loss (MacDonald and Leary, 25; Somerville et al., 26). Stress-related hormones may function in the ACC as a part of a feedback circuit which is sensitive to stress and emotion. Corticotropin-releasing hormone (CRH) immunoreactive neurons show the greatest neocortical density in the ACC in monkeys (Lewis et al., 199). The ACC has been shown to mediate an inhibitory effect of glucocorticoids during stress in the rat (Diorio et al., 1993) and salivary cortisol has been shown to directly correlate with ACC activation during error commission in humans, as measured by a specific component of scalprecorded electrical potentials (the ERN) described below (Tops et al., 26) The ERN The error-related negativity (ERN), an electroencephalographic (EEG) potential originating from the ACC (Debener et al., 25), is observed over frontal-midline scalp sites ms after an erroneous response has been executed (Falkenstein et al., 1991; Gehring et al., 1993). A similar, yet much smaller potential is sometimes seen in correct trials as well (sometimes termed correct trial negativity: CRN). EEG source-localization techniques have provided considerable evidence that the ERN is generated as an endogenous error signal in the dorsal ACC (Dikman and Allen, 2; van Veen and Carter, 22), with possible contribution of rostral areas as well (Luu et al., 23). In the fmri environment, ACC blood oxygen level dependent (BOLD) activity positively correlates with ERN amplitude during error commission (Debener et al., 25). Holroyd and Coles (22) have hypothesized that the ERN potentials are generated when reinforcement learning signals are transmitted to the ACC from the mesolimbic dopamine system (phasic dopamine dips resulting from negative prediction errors), and that these signals may be used to guide future performance on the task at hand. Some interpretations of the ERN literature have characterized these potentials as representative of cognitive conflict, of which error detection is a specific instance (Yeung et al., 24). The ERN may be a sensitive metric of cognitive performance under stress, because both perceived cognitive

3 Stress and the ERN 43 conflict and error salience are important aspects of cognitive control that may be specifically compromised. ERN amplitude has been shown to be sensitive to the salience of negative outcomes, being larger in high value trials (Hajcak et al., 25; Pailing and Segalowitz, 24a). It is also larger as trait negative affect is larger (Luu et al., 2), as is the CRN (Hajcak et al., 24). The ERN also correlates with scores on Carver and White s (1994) Behavioral Inhibition System (BIS) scale, which reflects sensitivity to anxiety provoking stimuli and signals of punishment or non-reward (Boksem et al., 26). Other studies have parsed how ERN amplitude modulation to different incentive conditions is moderated by personality factors, such as low socialization (Dikman and Allen, 2), and high neuroticism (Pailing and Segalowitz, 24a; Tops et al., 26). Pailing and Segalowitz (24a) hypothesize that the personality traits of low socialization and high neuroticism share the phenomenon of attributing an external locus of control. Indeed, Hajcak et al. (25) demonstrated that the ERN is larger under conditions of experimenter evaluation and purported performance comparison, although social evaluative threat was not specifically investigated in this study. Available evidence suggests that the ERN may be sensitive to both trait and state level variables which signify a high salience of errors, especially in high punishment-sensitive individuals Sequelae of error detection Another affect-sensitive component elicited by errors is found in the error positivity (Pe), a posterior positive deflection occurring 2 5 ms following a response error. The Pe may reflect the awareness and conscious evaluation of an error, which may be contrasted with the relatively automatic functioning of the ERN (Overbeek et al., 25), Furthermore, the Pe is modulated by different affectsensitive functions than the ERN. Boksem et al. (26) have demonstrated that Pe amplitude correlates with scores on Carver and White s (1994) Behavioral Activation System (BAS) scale, particularly the BAS-fun subscale. BAS reflects sensitivity to signals of reward and is believed to be orthogonal to the BIS system, described earlier as a correlate of ERN amplitude. A smaller Pe has also been found in fear conditions (Moser et al., 25) and in individuals high in negative affect (Hajcak et al., 24). The Pe may be of further utility for examining the conscious evaluation of errors during social evaluative threat, although the exact psychometric properties of this potential are still undefined. Based on similarities in the eliciting circumstances, time course, and scalp topography, the late Pe is suggested to represent a P3-like component occurring after endogenous realization of errors (Overbeek et al., 25). The P3 is one of the best characterized ERP components, which is reflective of stimulus evaluation and salience (Polich and Kok, 1995). Both Pe and ERN amplitudes have been shown to correlate with post-error slowing (Hajcak et al., 23; Debener et al., 25), a behavioral modification whereby the trial following an error is characterized with a slower reaction time in order to correct behavior for continued accuracy. Poorer post-error accuracy is a characteristic of participants scoring high in depressive symptomology (Holmes and Pizzagalli, 27), and diminished tonic activity in rostral ACC regions may mediate these deficits in post-error adjustment seen in depression (Pizzagalli et al., 26). The error-associated metrics of the Pe and post-error behaviors (reaction time and accuracy) may provide additional insight into stress sensitive conscious processes and performance adjustments, respectively Possible dynamic activities of the ACC during stress and emotion Tops et al. (26) have proposed that both ERN amplitude and HPA mobilization relate to task engagement. These authors have shown that both the personality constructs of agreeableness and shame proneness (fear of negative social evaluation) correlate with ERN amplitude; as did the amount of baseline cortisol and the subsequent degree of cortisol decrease over time that the authors interpret as HPA mobilization. In line with the finding of Hajcak et al. (25) that the ERN is larger under conditions of experimenter evaluation, this component may be used as one measurement of the degree to which the ACC is involved in the response to social evaluative threat. Investigations of increased ACC activities during pain and punishment are well established, but few studies have investigated the effect of a prolonged, unavoidable and socially evaluative punishing situation. Diminished ERN amplitudes have been interpreted to be reflective of negative affect-driven task disengagement (Luu et al., 2), and a lower ERN and larger CRN have been found under conditions of uncertain responding (Pailing and Segalowitz, 24b). Since the ERN amplitude is sensitive to the degree of involvement and confidence during a response, it may provide a sensitive index of ACC involvement in engaged or disengaged responses to social stress Description of study This experiment was designed to investigate whether errorsensitive ERPs may provide useful indices of stress effects on motivation-sensitive action monitoring in the ACC (ERN) and affect-sensitive action regulation (Pe), both aspects of cognitive control. ERN amplitude elicited from a standard baseline task was predicted to correlate positively with future cortisol reactivity to social threat by virtue of a shared sensitivity to Carver and White s (1994) BIS scale, reflective of punishment and anxiety sensitivities. ERN amplitude elicited from a difficult goal-directed performance task under conditions of social threat was predicted to be modulated by both trait BIS as well as state withdrawal (fear and shame) affect. Consistent with the baseline task predictions, larger ERN amplitudes during the threat performance task may predict task engagement and greater cortisol reactivity, yet diminished ERN amplitudes reflective of task disengagement would not predict an increase in cortisol. Pe amplitude is predicted to directly correlate with state withdrawal affect during the threat performance task. Statistical tests of the Pe will investigate the moderating role of trait BAS score (Carver and White, 1994) based on previous research (Boksem et al., 26).

4 44 Behavioral adjustments following errors may reveal consequences of ACC reactivity and task disengagement during performance under stress, with less post-error slowing and lower post-error accuracy being reflective of compromised cognitive control. 2. Methods 2.1. Participants Fifty-five introductory psychology students (2 female) aged 1 23 served as participants to partially fulfill a research experience requirement for their introductory psychology class. All participants signed informed consent documentation and received two hours of experimental credit for participation in this study. All participants were right handed as assessed by the Chapman and Chapman (197) handedness scale, and reported that they were free from past neurological trauma, had normal or corrected-tonormal vision, and were free from current psychoactive medication use. Although participants were asked to abstain from tobacco and caffeine use on testing day, three participants reported caffeine use (closest: 2.5 h before arrival), and three others reported tobacco use (closest: 2 h before arrival). These participants were included in all analyses. Seven female participants were taking birth control medications, and female participants were almost evenly distributed in menstrual cycle phase (14 follicular, 11 luteal, 3 unreported) Procedure Participants were recruited via an online experimental signup system. The project was entitled Neural Correlates of Implicit Learning and brief information was given on the electrophysiological procedures involved. No information was given to the participants regarding the true nature of the task, and all students indicated in debriefing forms that they had not been told of the true purpose of the experiment before arrival. All saliva samples were taken between 12: and 1: to control for diurnal variations in cortisol. Two experimenters were always present during the experiment, both the lead researcher (JFC) and one of several possible assistants. Following informed consent, participants filled out the personality inventories including the Behavioral Inhibition/Activation Scales (BIS/BAS: Carver and White, 1994) as well as demographic and health-related behaviors. Participants were prepared for EEG recording, which is described in detail below. Participants were then moved to a sound attenuated recording room, where they were given computer-controlled instructions for a 6 min resting baseline. All tasks and instructions were programmed using DMDX (Forster and Forster, 23). Participants were continually monitored via a discrete video camera and microphone, and the experimenters could communicate to the participant using an intercom system throughout the experiment. The first saliva sample (T1) was gathered for 9 s using a Salivette sampling device (Sarstedt, Inc.; Newton, NC) following the resting baseline procedure, which was on average 41.6 (7SD ¼ 4.79) min after initial arrival Letters task J.F. Cavanagh, J.J.B. Allen Participants received computer-controlled instructions and practice sessions for a modified Erikson Flankers task (hereafter: Letters task), a procedure commonly used to elicit errors of commission for ERN measurement. All stimuli were in white text on a black screen. Participants responded to all tasks using two hand held thumb-response buttons which embedded the response in the electrophysiological data file while also signaling the stimulus presentation computer. Ten 4-flanker blocks were presented (4 trials total) of five letter-series (two blocks each: MMNMM; FFEFF; QQOQQ; VVUVV; TTITT). In each series, participants were required to identify the center letter, which could be the same as the flankers (congruent: MMMMM or NNNNN) or different (incongruent: MMNMM or NNMNN). The letter-hand mappings were reversed between consecutive blocks of the same letter string to increase response conflict. Each trial began with a blank screen for 1 ms, followed by an asterisk fixation point for 7 ms. The asterisk disappeared when the letter flankers were presented (4 ms duration). In order to increase response conflict, the center target letter appeared 135 ms after the onset of the flankers, thus leaving the entire target and flanker letter string on for 265 ms. The letter string offset was followed by an asterisk fixation point for 6 ms, and participants had the total 1 ms since flanker onset to respond. If they did not respond within this time limit, or if they responded incorrectly, feedback (WRONG) was displayed for 5 ms. No feedback was given for correct trials. Participants were only told that this task measured perceptual processes, and that speed and accuracy were important. Participants were encouraged to self-correct erroneous responses throughout the task. A 2 min break was given after the sixth block where participants were given instructions to sit still and rest with their eyes open, similar to the resting baseline instructions Social evaluative threat manipulation All social manipulations were designed to follow the criterion of Dickerson and Kemeny (24) to create an uncontrollable situation with overt displays of exposed failure in a socially evaluative environment while maximizing motivated performance. Following completion of the Letters task, the lead experimenter entered the room and gave a brief (standardized) description of the next task followed by questionnaires designed to appear to assess intelligence. This section was designed to be an analogue of the TSST anticipation period. Participants were informed that they had completed the verbal abilities portion of the learning experiment well enough to continue with the mathematical abilities portion. The assistant set up a video camera on top of the monitor, and the participants were told that the experimenters would be monitoring their performance visually as well from this time on since the mathematical task was more difficult. Participants were then given questionnaires asking their SAT scores, pre-task appraisals of performance ability and a test comprised of difficult verbal analogy and mathematics questions. Both experimenters left the room and participants were informed that they could have 5 min to complete the questionnaires

5 Stress and the ERN 45 before the task began. After 4 min, the lead experimenter entered the room and took the questionnaires, at which time 53 of the 55 participants had failed to finish the scale. The experimenter expressed surprise and disapproval that they had not finished, and indicated that perhaps they could find time at the end of the experiment for the participant to finish. The participants then received computer-controlled instructions and practice trials for the Math Stress task. Threats to the social self during the Math Stress task were largely focused on academic ability, although efforts were made to give negative feedback on the participant s undefined abilities Math Stress task The Math Stress task was designed to elicit response competition and performance feedback for ERP measurement during a difficult and evaluative task within the constraints of an electrophysiological experiment. Each trial consisted of two simple additive or subtractive equations displayed on either side of the center of the screen for 3 ms, with each total ranging from 2 to 1 (e.g., ). A greater than or less than sign subsequently appeared for 5ms, indicating that one specified total was larger than the other (e.g., ). The screen then went blank for 1 ms. Participants had this total 15 ms to decide whether the statement was true or false by pressing a designated response button. Following their response, feedback (5 ms) indicated whether they were correct (OK), too slow (Too Slow) or incorrect (WRONG). All text displays were similarly presented in white on a black screen, except for the WRONG feedback, which was in red. Following the offset of feedback stimuli, an asterisk fixation point appeared for 1 ms to mark the inter-trial interval. The asterisk disappeared at the instant that the next set of equations were presented. The Math Stress task consisted of 12 blocks of 2 trials each (24 trials), with true-false button mapping reversed between each block. To increase uncontrollability and exposed failure, a normal statistical curve was presented for 3 ms after every second block with a line purportedly indicating the participant s percentile ranking. The rankings were the same for each participant regardless of performance, beginning with the th percentile (then 15th, 12th, 9th, 17th and 12th). To increase social evaluative threat, the experimenter read standardized prompts following the practice session, after the first block, after each percentile ranking, and throughout the task if communication with the participant was necessary. The prompts were designed as failure feedback to question the participant s abilities to perform the task and encourage continual task engagement and motivated performance (i.e., You had a lot of problems there, are you sure you understand the directions? ; You re not performing up to criterion. You need to try harder to get them all correct ; Are you remembering to self-correct your mistakes? You have plenty of time to get them right ). Participants received the exact same rest instructions (2 min, eyes open) as during the letters task after the sixth block. After this rest period, the assistant gathered the second (T2) saliva sample, which occurred 25 min (M ¼ 24.9, 7SD ¼.57) after the initiation of the social evaluative threat condition (the time of the video camera setup and scholastic abilities questionnaire) State questionnaires After the last block of the Math Stress task, participants filled out state questionnaires and the final saliva sample (T3) was gathered at least 2 min (M ¼ 2.1, 7SD ¼.37 min) after T2. The questionnaires began with post-task appraisals of performance: (comparison to other students, how the experimenter will rate them, how difficult, was it too difficult, how threatening, how stressful). Items were coded to reflect aggregate negative selfevaluation and the coefficient alpha was computed for the composite of the six items (a ¼.77). Participants also completed an emotional experience word list similar to the one used in Lerner et al. (25). This scale included an alphabetical list of emotional adjectives rated on a scale of which were parsed into pre-determined clusters for analysis: Fearful (fear, nervous, anxious, afraid; a ¼.3); Angry (anger, irritation, frustration; a ¼.3) and Shame (ashamed, humiliated, embarrassed; a ¼.95). Since the Fearful and Shame constructs shared common conceptual ground, a Withdrawal construct was created which included their constituent questions (a ¼.92). A Rumination measure was included at the end of the questionnaires, asking participants whether they agreed with three ruminative statements (expressing worry during the task, still feeling upset at their performance, and having a hard time moving on; a ¼.7). The pre-task appraisals were also aggregated similarly, with a higher value reflecting better Anticipatory Positive Appraisal (expected difficulty, have the skills to do well, & expect to do well; a ¼.1). The last question on the questionnaires asked participants what they believed the experiment was truly measuring. The first question asked of the participant by the experimenter upon completion of the questionnaires was similar. Both the questionnaire and verbal responses were used as a manipulation check. 2 Participants were then unhooked from the electrophysiological setup and thoroughly debriefed to the true nature of the experiment Electrophysiological setup EEG was recorded from 26 channels on the scalp (Fz, Cz, Pz, Oz, Fp1/2, F3/4, F7/, C3/4, P3/4, T3/4, T5/6, O1/2, FTC1/2, TCP1/2, PO1/2) using a stretch-lycra tin-electrode cap (Electro-cap Intl. Inc.; Eaton Ohio). Additional tin electrodes were placed on the A1 & A2 mastoid, and three were used to record electrooculographic (EOG) signals: one placed below each eye and one over the nasion. All sites were referenced online to Cz, and grounded using an electrode anterior to Fz. Data were sampled at 1 Hz 2 Individuals who indicated at any point that they thought the experiment involved stress were coded as savvy (n ¼ 29), all others were coded as naïve (n ¼ 26). There were no differences in cortisol reactivity for the T3 T2 difference (savvy M ¼., 7SD ¼ 2.96; naïve M ¼ 1.74, 7SD ¼ 3.5) or cortisol b (savvy M ¼.22, 7SD ¼ 2.79; naïve M ¼.45, 7SD ¼ 3.16) between coded groups.

6 46 J.F. Cavanagh, J.J.B. Allen and amplified by a factor of 5 with a bandpass of.5 2 Hz using a Neuroscan Synamps amplifier. All impedances were kept below 5 ko. All data were stored with responses and stimulus codes in a single binary file directly on a laboratory server. Care was taken during the setup of all participants to keep the procedure standardized and professional, which mainly included a thorough description of electrophysiological recording procedures Response accuracy and reaction time All erroneous responses that had self-corrections within 2 1 ms post-stimulus for the Letters task and 2 15 ms post-stimulus for the Math Stress task were included in analyses. Uncorrected errors were not included, as such trials may reflect known errors that subjects fail to self-correct, or reflect undetected errors. Trials with responses that were either too slow or where the participant responded during the response window with an incorrect response that followed a correct response were rare and were excluded from analyses. Reaction times (RT) and accuracies were also tabulated for correct-following-correct trials, correct-following-error and error-following-error trials in the Letters and Math Stress tasks Electrophysiological data preparation All EEG data were re-referenced to computer averaged ( linked ) mastoids and visually inspected for artifacts. A single VEOG channel was then computed as the difference between nasion and Left VEOG channels. Continuous EEG data were filtered ( Hz) using a 33-point finite impulse response filter, following which response locked epochs ( 1 to 6 ms post-response) were created. Eye blinks identified from the VEOG channel were corrected in the epoched EEG data using a regression algorithm (Semlitsch et al., 196). All corrected epochs were then baseline adjusted ( 1 to ms) and averaged together by condition (Letters task correct, Letters task self-corrected, Math Stress task correct, Math Stress task self-corrected). The ERN was measured as the peak negativities at Cz from 3 to 12 ms post-response on error and correct trials. The Pe was measured as the maximum positivity at Pz from 2 to 3 To investigate the possibility of EEG setup procedures acting as a hidden stressor which might influence HPA activity, an additional saliva sample (T) was taken from 16 participants prior to their EEG setup (M ¼ min after arrival, 7SD ¼ 2.9). Differences in these participants between T1 (M ¼ min after T, 7SD ¼ 2.14) and T were examined as exploratory indices of HPA reactivity to the EEG setup procedure. Overall, salivary cortisol levels declined from T (M ¼.36 nmol/l, 7SD ¼ 5.9) to T1 (M ¼ 7.79 nmol/l, 7SD ¼ 3.99) time points. When considered individually, individuals remained within a % boundary of their T level, four individuals declinedo75%, while four individuals increased 4125%. While these last four individuals could possibly reflect a sub-sample of participants who experienced HPA activation due to the electrophysiological setup, the necessary questionnaires to address this question were not gathered. Overall, available evidence suggests that that the EEG setup in this experiment did not affect HPA activity to the extent of a confounding variable, if indeed to any extent, although further investigations could examine this methodological issue in greater depth. 5 ms post-response on error and correct trials. In order to isolate error-related processing in each task, the difference waveform (self-corrected error minus correct waveforms) was computed and the respective amplitudes of ERN_diff and Pe_diff were measured in the same time windows as their constituent components. Not all participants had sufficient artifact-free selfcorrected errors in the tasks. All participant ERNs were visually inspected to ensure a robust ERN was identifiable, and only ERN/Pe averages with at least ten self-corrected trials were included in ERP analyses, reducing the sample size from 55 to 43 for Letters task and to 39 for Math Stress ERP analyses. Although this is a slightly liberal epoch cut-off criterion, the limiting of only self-corrected error trials ensures that each ERN average is composed of entirely endogenously realized errors and may result in a greater signal-to-noise ratio within the computed ERPs than if all error trials had been included. One participant was missing data at the Pz electrode, and two participants were missing cortisol data due to small amounts of saliva in the Salivette, resulting in minor variations of degrees of freedom for analyses involving these data Salivary cortisol analysis Salivettes were stored in a laboratory freezer until shipping for assay. Assays were performed in Dresden, Germany using Competitive Chemiluminescence Immunoassay (LIA) with a sensitivity of.16 ng/ml (IBL, Hamburg, Germany). All samples had an intraassay variabilityo% Statistical analyses A metric of overall post-error slowing difference was computed for each task by subtracting post-correct RTs from post-error RTs. Total accuracy and post-error accuracy were also computed to examine task efficacy and errorrelated behavioral changes. Cortisol reactivity was investigated using independent samples t-tests between discrete time points, and individual growth curves were calculated as the unstandardized beta weight for each individual s T1, T2 and T3 cortisol samples to investigate relationships between cortisol b and predictor variables. Bivariate correlations were used to investigate relationships between ERP, behavioral and stress-reactive variables. Repeated Measures General Linear Models (RM GLMs) were used to examine the influence of psychological moderators entered as continuous variables on different ERPs (ERN, Pe) during different accuracy conditions (error, correct) between both tasks (Letters, Math Stress). In order to isolate ERP effects specific to the Math Stress task, Letters ERPs were regressed out of Math Stress ERPs and RM GLMs were run on both the raw and unstandardized residual Math Stress ERP. 3. Results 3.1. Behavioral performance Self-corrections occurred on 7% of erroneous responses in the Letters task, but only 41% of Math Stress task errors.

7 Stress and the ERN 47 Since the correct response decision in the Math Stress task must be deduced via arithmetic calculations rather than simply seen as in the letters task, a lower self-correction percentage in the Math Stress task was expected. Post-error slowing significantly predicted both accuracy (r[55] ¼.63, po.1) and post-error accuracy (r[55] ¼.27, po.5) in the Letters task, as well as accuracy (r[55] ¼.55, po.1) and post-error accuracy (r[55] ¼.51, po.5) in the Math Stress task. Figure 1 shows that post-error accuracy was significantly compromised in high BIS individuals during the Math Stress task when examined as a median split grouping variable (F[1,53] ¼ 4.9, po.5; partial Z 2 ¼.9) ERP data Response-locked ERPs are depicted in Figure 2. The ERN amplitude was largest at the Cz electrode for both tasks. A 2 (task) 2 (accuracy) RM GLM on ERN/CRN amplitudes at Cz revealed a main effect for accuracy (F[1,3] ¼ 1, po.1; partial Z 2 ¼.3) and a task by accuracy interaction (F[1,3] ¼ 24.13, po.1; partial Z 2 ¼.39), in the absence of a main effect of task (F[1,3] ¼.35, p ¼.55). 15 Post Error Slowing As expected, the negative amplitude was larger on selfcorrected error trials than on correct trials for each task. The interaction was driven by larger (more negative) correct trial and smaller error-trial amplitudes during the Math Stress task. Correspondingly, a paired-samples t-test revealed a smaller ERN_diff amplitude in the Math Stress task compared to the Letters task (t[3] ¼ 6.15, po.1). Since the Pe amplitude was largest at Pz for the Letters task, and at Cz for the Math Stress task, a 2 (task) 2 (accuracy) 2 (electrode) RM GLM was used to reveal a main effect for accuracy (F[1,37] ¼ 119., po.1; partial Z 2 ¼.76) as well as a task by accuracy interaction (F[1,37] ¼ 33.7, po.1; Z 2 ¼.4), in the absence of a main effect for task (F[1,37] ¼ 2.3, p ¼.13). There were no main or interaction effects with the electrode site. The Pe amplitude was larger than the correct-trial positivity for each task. The interaction was driven by larger correct-trial positivity and smaller error-trial positivity (Pe) amplitudes during the Math Stress task. Correspondingly, a pairedsamples t-test revealed a smaller Pe_diff amplitude in the Math Stress task compared to the Letters task at the Cz electrode (t[3] ¼ 5.4, po.1) as well as at the Pz electrode (t[37] ¼ 6.9, po.1) Stress response data milliseconds percent percent Low BIS High BIS Total Accuracy Low BIS High BIS Post Error Accuracy Inspection of the cortisol response over time, as shown by Figure 3, shows that the mid-session assessment (T2) did not capture the overall cortisol peak; rather this peak occurred at the end of the Math Stress task (T3), which would have been 25 min after the first few blocks of the Math Stress task. Since these first few blocks included manipulations of motivated performance, uncontrollability, exposed failure as well as social evaluative threat, it is likely that the Math Stress task itself (rather than the manipulative period) provoked the HPA activation. A paired-samples t-test showed a significant cortisol increase from T2 to T3 (t[52] ¼ 2.9, po.1). Table 1 shows relationships between trait level punishment sensitivity (BIS), and state-assessed Withdrawal emotionality and cognitive components of negative self-evaluation and rumination. These retrospective state level variables cluster together as expected, and a distinct negative correlation is found between pretask Anticipatory Positive Appraisal and negative selfevaluation after the task (r[55] ¼.42, po.1]. As expected, no questionnaire variables significantly predicted cortisol b. Low BIS High BIS 3.4. Predictive value of trait level neural activities Letters Math Stress Figure 1 Post-error slowing (in ms), total accuracy and posterror accuracy (in percent correct) across both the Letters and the Math Stress tasks are displayed (Means7SE). Despite apparent trends in behavioral measures of performance and post-error adjustment, BIS groups were only significantly different on post-error accuracy, showing specifically compromised Math Stress performance after negative feedback in high- BIS individuals. No amplitude-derived measurement of the Letters ERN was predicted by BIS (largest r: ERN-BIS r[44] ¼.24, p ¼.11), nor were there any significant correlations between Letters task Pe amplitude and any subscale (or aggregate) of BAS (largest r: BAS fun-pe at Pz r[43] ¼.14, p ¼.39). Figure 4A displays the moderating influence of BIS on the direct relationship between the Letters ERN_diff amplitude at the Cz electrode and cortisol b (Omnibus F[3,39] ¼ 5.33, po.1, partial Z 2 ¼.29; Letters ERN_diff F[1,39] ¼.5, po.1, partial Z 2 ¼.17; Letters ERN_diffBIS

8 4 J.F. Cavanagh, J.J.B. Allen Letters Math Fz ERN_diff Cz ERN_diff Amplitude in μv Pe_diff Pz Pe_diff msec Correct Error ERN_diff Figure 2 Grand average ERPs for the Letters and Math Stress tasks, time locked to the response ( ms). Note that negative is up on the Y-axis. The scalp distributions for the ERN_diff and Pe_diff are displayed at the time of maximum peak amplitude. Head maps are shown in absolute differences for ease of greyscale viewing, and they range from to 715 mv for Letters and 71 mv for Math Stress. Cortisol in nmol/l T1 Low BIS High BIS T2 Sample Time Figure 3 Cortisol change over time, median split by BIS group for display purposes (Means7SE). Although the T3 sample was significantly larger than the T2 sample (see text), BIS did not moderate this effect. F[1,39] ¼ 9.5, po.1, partial Z 2 ¼.2). Data are median split for display only in Figure 4. Removal of the apparent outlier in the top panel of Figure 4A, the highest ERN_diff/ cortisol b data point, strongly attenuates the interaction (F[3,3] ¼.53, p ¼.66). When examining only high BIS T3 Table 1 Bivariate correlations between trait punishment sensitivity (BIS) and negative state emotional and cognitive reports. BIS Withdrawal Rumination Pos appraisal Withdrawal.26 y Rumination.34*.72** Neg self Eval.9.59**.66**.42** Positive appraisals of performance before the task were inversely related to negative self-evaluation after the task. All n ¼ 55; y po.1, *po.5, **po.1. individuals (above median split: right panel of Figure 4A), bivariate correlations reveal a strong correlation between ERN amplitude at Fz (r[21] ¼.57, po.1, R 2 ¼.32) which diminishes when the highest value is removed (r[2] ¼.34, p ¼.14, R 2 ¼.12) A similar effect size is found when examining the entire high BIS sample using non-parametric statistics (r[21] ¼.33, p ¼.15, R 2 ¼.11).

9 Stress and the ERN 49 Low BIS High BIS Cortisol Growth (β) Letters ERN_Diff Amplitude in µv Low BIS High BIS Withdrawal Math Stress ERN_Diff Amplitude in µv Low BAS High BAS Withdrawal Math Stress Pe_Diff Amplitude in μv Figure 4 Moderators of the relationships between ERP peaks and measures of stress responsiveness. All ERP data are from the Cz electrode. Figures are median split by trait moderator for display purposes only. Note that increases along the X-axis represent greater negativity for ERN_diff measures and greater positivity for Pe_diff measures. (A) Letters ERN_diff amplitude predicts the cortisol individual growth curve, primarily in High BIS individuals. (B) Math Stress ERN_diff amplitude. BIS interacted with selfreported emotional Withdrawal during the Math Stress task to account for significant variance in the amplitude of the ERN_diff. Note the different relationships between the ERN_diff and Withdrawal between BIS groups, indicating that affective distress may have different motivational consequences for low BIS individuals (engaging) and high BIS individuals (disengaging). (C) Math Stress Pe_diff amplitude. BAS interacted with self-reported emotional Withdrawal during the Math Stress task to account for significant variance in the amplitude of the Pe_diff. Both the main effects of trait (BAS) and state (Withdrawal) were significantly positively related to Pe_diff amplitude, and this effect was especially apparent in Low BAS individuals State dependent modulation of neural activities under stress Figure 4B displays the interaction between BIS and Withdrawal (Fearful+Shame) during the Math Stress task, which accounted for a significant amount of variance in the amplitude of the Math Stress ERN_diff at the Cz electrode when tested in a RM GLM with BIS and Withdrawal entered as continuous variables (Omnibus: F[3,35] ¼ 3., po.5, partial Z 2 ¼.25, BIS: F[1,35] ¼ 11.29, po.1; partial Z 2 ¼.25, Withdrawal: F[1,35] ¼.23, po.1; partial Z 2 ¼.19, BISWithdrawal: F[1,35] ¼ 9.1, po.1, partial Z 2 ¼.21). When Letters ERN_diff amplitude was regressed out of Math Stress ERN_diff amplitude, the unstandardized residuals display the same relationship (Omnibus: F[3,35] ¼ 2.7, p ¼.59, partial Z 2 ¼.19, BIS: F[1,35] ¼ 7.92, po.1; partial Z 2 ¼.1, Withdrawal: F[1,35] ¼ 5.56, po.5; partial Z 2 ¼.14, BISWithdrawal: F[1,35] ¼ 6.4, po.5, partial Z 2 ¼.15). These findings show different effects of Withdrawal emotionality on the ERN_diff amplitude in Low BIS (more emotionality, larger amplitude) and High BIS individuals (more emotionality, smaller amplitude). BAS moderated the relationship between Pe_diff amplitude at the Cz electrode and Withdrawal during the Math Stress task, as shown in Figure 4C. Both BAS and Withdrawal displayed positive relationships with the Pe_diff amplitude, with the direct correlation most profound in Low BAS individuals (Omnibus: F[3,35] ¼ 3.36, po.5, partial Z 2 ¼.23; BAS: F[1,35] ¼ 7.7, po.5, partial Z 2 ¼.17; Withdrawal: F[1,35] ¼ 9., po.1, partial Z 2 ¼.22;

10 5 J.F. Cavanagh, J.J.B. Allen BASWithdrawal: F[1,35] ¼ 9.47, po.1, partial Z 2 ¼.21). When Letters Pe_diff was regressed out of Math Stress Pe_diff, the residuals display the same significant relationships (Omnibus: F[3,35] ¼ 3.52, po.5, partial Z 2 ¼.23; BAS: F[1,35] ¼ 6.7, po.5, partial Z 2 ¼.15; Withdrawal: F[1,35] ¼ 9.71, po.1, partial Z 2 ¼.22; BASWithdrawal: F[1,35] ¼ 9.2, po.1, partial Z 2 ¼.21). These findings show an overall positive relationship between Withdrawal emotionality and the Pe_diff amplitude, with this effect most profound in Low BAS individuals (more emotionality, larger amplitude) but slightly reversed in High BAS individuals (more emotionality, smaller amplitude). Neither personality variables (BIS or BAS) nor ERP amplitudes (ERN, ERN_diff, Pe, Pe_diff) in the Math Stress task significantly correlated with the number of self-corrections or the percentage of self-corrections as a fraction of total incorrect responses. Addition of the Anger construct to the Withdrawal construct did not alter any pattern of ERN or Pe results. No Math Stress ERPs significantly predicted cortisol b or behavioral performance, even when including trait and state variables as statistical moderators. 4. Discussion Withdrawal motivated emotionality (fear and shame) has been proposed to relate to either sustained cortisol response or task disengagement (Tops et al., 26), each engendering different stress reactive consequences. In line with Tops et al. (26), this experiment provided evidence that both the ERN and HPA activities are related to task engagement. Baseline ERN amplitude directly predicted future cortisol reactivity to stress, showing that individuals with higher trait-level error monitoring demonstrate greater HPA reactivity under social evaluative threat. It was predicted that the ERN may predict cortisol reactivity by indexing a shared sensitivity to the psychological mechanism of trait punishment sensitivity (as measured by Carver and White s (1994) BIS scale). However, replication is necessary to confirm the role of trait punishment sensitivity, as these effects were attenuated with the removal of an outlying value in this sample. Despite the lack of robust statistical support in this experiment, the ERN may still offer predictive insight into psychological correlates of HPA reactivity when appropriate methodological constraints are taken into account. Other candidate trait level variables sensitive to motivation or engagement with the environment may prove to be more resilient moderating variables, and replication in a TSST-like experiment may provide more robust cortisol reactivity and increased range for inferential analysis. During the Math Stress task, error trials were characterized with lower ERN (less negative) and lower Pe (less positive) amplitudes, but correct trials were characterized with greater amplitudes when compared to the Letters task amplitudes. Thus social evaluative stress reduced the magnitude of differentiation between error and correct trials. Although some of this effect may reflect that the Math Stress task itself may reduce differentiation by virtue of its difficulty or even due to fatigue, the relationship of these modulations to trait and state variables sensitive to the stress manipulation indicate that the altered ERP amplitudes were directly relevant to the social evaluative threat manipulation. Affective withdrawal accounted for significant variance in both: (1) the reduced ERN difference amplitude in high BIS individuals, and: (2) the higher Pe difference amplitude, especially in low BAS individuals. The fact that these relationships were statistically significant even when accounting for corresponding Letters task ERP amplitudes supports the conclusions that the ERP modulations in the Math Stress task were unique indicators of stress reactivity. Reduced ERN amplitudes over the course of a task have previously been proposed to reflect task disengagement (Luu et al., 2) and increased Pe activities may indicate a sustained or enhanced awareness of the importance of the error (Overbeek et al., 25). These findings also support previous research on the role of individual differences in the facilitative or debilitative response to stress (Blascovich et al., 1999; Seery et al., 24), implicating a dynamic role of the ACC in engagement or disengagement under social evaluative threat (see Figure 4B; left panel vs. right panel). The effect of withdrawal-related emotionality on ERP indices of action monitoring and action regulation was moderated by different trait level constructs, which may be parsimoniously explained by the inherent relationship between the trait variable and the psychological construct related to the ERP (ERN & BIS reflecting punishment sensitivity; Pe & BAS reflecting aspects of responsiveness to the environment; Boksem et al., 26). Although correlations between ERN-BIS and Pe-BAS (Boksem et al., 26) were not significantly replicated in this study, the proposed psychological constructs reflected by the errorrelated ERPs remained relevant during the stress manipulation. Differences between the Boksem et al. (26) investigation and this study include the specific method to measure ERP components (mean window amplitude in Boksem et al. vs. maximum amplitude in this study), sample differences (24 paid females vs. 44 unpaid mixed sex), and the use all errors in Boksem et al. (26) versus only selfcorrected errors in this study. Any or all of these differences may have contributed to the lack of a statistically significant replication. For this study, it was proposed that high BIS individuals may be more sensitive to a social evaluative threat manipulation, but no such prediction was made for low BAS individuals. In the present experiment there was a significant positive relationship between Withdrawal and Pe amplitude, even without BAS moderation. In all cases, a high Pe/Withdrawal relationship indicates that attentional resources are still being utilized following commission of an error. A simplified interpretation of these responses would define highly vulnerable (high BIS) and reactive (fear and shame) individuals as disengaging in their performance (lower ERN) but still being affectively perturbed (higher Pe) by their errors Affect and performance In this experiment, the cluster of relationships between BIS, negative emotionality (fear & shame) and negative cognition (self-evaluation & rumination) were unrelated to peak cortisol reactivity. Since no sample was taken of true cortisol recovery, the present findings are unable to address