Journal of Abnormal Psychology 2014, Vol. 123, No. 4, 705-714

© 2014 American Psychological Association 0021 -843X714/$ 12.00 http://dx.doi.org/10.1037/abn0000012

Performance Monitoring in Obsessive-Compulsive Disorder and Social Anxiety Disorder Tanja Endrass

Anja Riesel and Norbert Kathmann

Otto-von-Guericke-Universitat Magdeburg and Humboldt-Universitat zu Berlin

Humboldt-Universitat zu Berlin

Ulrike Buhlmann Westfalische Wilhelms-Universitat Munster Overactive performance monitoring, indexed by greater error-related brain activity, has been frequently observed in individuals with obsessive-compulsive disorder (OCD). Similar alterations have been found in individuals with major depressive and generalized anxiety disorders. The main objective was to extend these findings by investigating performance monitoring in individuals with social anxiety disorder (SAD) and to evaluate the specificity of performance-monitoring changes in OCD. Event-related potentials were used to examine error-related brain activity during a flanker task in 24 individuals with OCD, 24 individuals with SAD, and 24 healthy controls with no history of neurological or psychiatric disorders. Error-related negativity (ERN) and correct-related negativity served as electrophysiological indicators for performance monitoring. Enhanced ERN was expected for both clinical groups, but differential associ­ ations with clinical symptoms were explored. ERN amplitudes were larger in individuals with OCD and SAD than in healthy controls. Correlational analyses did not reveal significant associations between ERN and clinical symptomatology in OCD, but a significant correlation with depressive symptoms was found in the SAD group. These findings further strengthen the idea that overactive performance monitoring is independent of clinical symptoms in OCD. Furthermore, it may also represent a transdiagnostic vulner­ ability indicator, although the relationship with clinical symptoms observed in the SAD group needs additional evaluation. Keywords: performance monitoring, obsessive-compulsive disorder, social anxiety disorder, depression, error-related negativity

Obsessive-compulsive disorder (OCD) is considered a severe psychiatric condition. The lifetime prevalence is between 1% and 3% (Weissman et al., 1994; Wittchen & Jacobi, 2005), and the disorder causes severe impairment in everyday life (Mendlowicz & Stein, 2000). Specifically, OCD is characterized by intrusive thoughts (obsessions) that cause distress, and compensatory be-

haviors (compulsions) are used to reduce or neutralize distress (American Psychiatric Association, 2013). Compulsions in OCD are motivated by the avoidance of potential negative consequences and have been suggested to result from persistent high error signals that cannot be reduced through behavioral adjustments (Pitman, 1987). Detection of mistakes and errors signals are necessary for adap­ tive behavior to compensate for errors or to avoid committing the same errors again. Errors signals are generated by the posterior medial frontal cortex whenever deviations from predicted events occur (e.g., Ullsperger, Danielmeier, & Jocham, 2014). A neural marker of error processing is the error-related negativity (ERN), which is a negative component in the electroencephalogram that occurs about 50 ms after erroneous responses (Falkenstein, Hohnsbein, Hoormann, & Blanke, 1991; Gehring, Goss, Coles, Meyer, & Donchin, 1993) and is reliably larger than its counterpart on correct responses, the correct-related negativity (CRN; Endrass, Klawohn, Gruetzmann, Ischebeck, & Kathmann, 2012; Ford, 1999). The ERN has a frontocentral distribution and is assumed to originate in the posterior medial frontal cortex (Debener et al., 2005; Dehaene, Posner, & Tucker, 1994). Furthermore, the ERN is considered a performance-monitoring signal coding suboptimal outcomes and is used to adjust subsequent behavior to ensure optimal performance (Ridderinkhof, Ullsperger, Crone, & Nieu-

This article was published Online First October 6, 2014. Tanja Endrass, Institute of Psychology, Otto-von-Guericke-Universitat Magdeburg; Department of Psychology, Humboldt-Universitat zu Berlin; Anja Riesel and Norbert Kathmann, Department of Psychology, Humboldt-Universitat zu Berlin; Ulrike Buhlmann, Department of Psy­ chology, Westfalische Wilhelms-Universitat Munster. We thank Melanie Vroomann, Julia Preuss, and Teresa Katthagen for their help in data collection. Furthermore, we thank Eva Kischkel and Rudiger Spielberg for clinical assessments and Rainer Kniesche and Thomas Pinkpank for technical assistance. This project was funded by the German Research Foundation (EN 906/1-1, BU 1814/7-2). The funding source had no further influence on study conduction and publication. We assure that we have no competing financial interests regarding the pre­ sented work. Correspondence concerning this article should be addressed to Tanja Endrass, Otto-von-Guericke-Universitat Magdeburg, Institut fur Psycholo­ gic II, Universitatsplatz 2, 39016 Magdeburg, Germany. E-mail: endrass@ gmail.com

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wenhuis, 2004; Ullsperger, Danielmeier, et al., 2014; Ullsperger, Fischer, Nigbur, & Endrass, 2014). A hyperactive error detection system in OCD might cause inappropriate compensatory behavior in situations in which no adjustment is necessary. In fact, numerous studies have investi­ gated error processing in simple response choice tasks and have shown altered error processing as indexed by potentiated ERN amplitudes in individuals diagnosed with OCD (Carrasco, Harbin, et al., 2013; Carrasco, Hong, et al., 2013; Endrass, Klawohn, Schuster, & Kathmann, 2008; Endrass et al., 2010; Gehring, Himle, & Nisenson, 2000; Hajcak, Franklin, Foa, & Simons, 2008; Johannes et al., 2001; Klawohn, Riesel, Griitzmann, Kathmann, & Endrass, 2014; Riesel, Endrass, Kaufmann, & Kathmann, 2011; Riesel, Kathmann, & Endrass, 2014; Ruchsow et al., 2005; Stem et al., 2010; for a review, see Endrass & Ullsperger, 2014) and in healthy individuals reporting high levels of obsessive-com pulsive symptoms (Griindler, Cavanagh, Figueroa, Frank, & Allen, 2009; Hajcak & Simons, 2002; Santesso, Segalowitz, & Schmidt, 2006). The ERN enhancement in OCD has been found independent of pharmacological intervention (Stem et al., 2010), symptom expres­ sion (Riesel et al., 2014), and symptom reduction with treatment (Hajcak et al., 2008). Furthermore, enhanced ERN amplitudes have been found in unaffected first-degree relatives of OCD pa­ tients (Carrasco, Harbin, et al., 2013; Riesel et al., 2011). Based on these findings, altered performance monitoring has been suggested to represent a biom arker or potential endophenotype for OCD (Olvet & Hajcak, 2008; Riesel et al., 2011). Similar to error processing alterations in OCD, ERN enhance­ ments also have been observed in major depressive disorder (MDD) and generalized anxiety disorder (GAD). Although several studies found increased ERN in individuals diagnosed with MDD (Aarts, Vanderhasselt, Otte, Baeken, & Pourtois, 2013; Chiu & Deldin, 2007; Georgiadi, Liotti, Nixon, & Liddle, 2011; Holmes & Pizzagalli, 2010), other studies found normal (Olvet, Klein, & Hajcak, 2010; Schrijvers et al., 2008, 2009) or reduced ERN (Ladouceur et al., 2012) in MDD. These findings suggest that performance monitor­ ing is enhanced in mild to moderate depression, whereas it is reduced in more severe depression, possibly due to symptoms such as apathy and anhedonia (Schrijvers et al., 2009). Similarly, altered performance monitoring has also been observed in GAD. Whereas two studies found larger ERN (Weinberg, Olvet, & Hajcak, 2010; Xiao et a l, 2011), one study found no ERN enhancement but a larger difference between ERN and CRN (Weinberg, Klein, & Hajcak, 2012). M oreover, this enhancement was seen only in individuals without comorbid MDD as compared with individuals with comorbid depression. Taken together, these findings suggest that enhanced performance monitoring occurs beyond diagnostic categories, although some depressive symptoms may attenuate performance monitoring. This is also in accordance with two recent meta-analyses demonstrating moderate relationships be­ tween increased trait-anxiety measures and ERN amplitude (Ca­ vanagh & Shackman, 2014; Moser, Moran, Schroder, Donnellan, & Yeung, 2013). It has been suggested that the enhancement of ERN, as a signal for behavioral adaptation in uncertain conditions, may result from the greater uncertainty in anxiety-related disorders (Cavanagh & Shackman, 2014). These findings emphasize the need to investigate performance monitoring in a wider range o f anxiety disorders. Social anxiety disorder (SAD) is characterized by an intense anxiety and the fear

o f being judged negatively in social situations (American Psychi­ atric Association, 2013). It is the most common anxiety disorder, with a lifetime prevalence of 13% (Kessler, 2003), and is highly comorbid with depression and substance-related disorders (Kauf­ man & Chantey, 2000; Kessler, 2003). One important aspect in cognitive models of social anxiety disorder is enhanced selffocused attention in social situations (Clark & W ells, 1995), and patients are concerned about potential mistakes in social situations. Performance monitoring has not been directly investigated in SAD, but there is some evidence that the ERN might also be enhanced in SAD based on the relationship between trait-anxiety and ERN (Cavanagh & Shackman, 2014; M oser et al., 2013). Furthermore, enhanced ERN amplitudes have been reported in heterogeneous groups o f childhood anxiety disorders including individuals with SAD (Ladouceur, Dahl, Birmaher, Axelson, & Ryan, 2006; M eyer et al., 2013). More specifically, an association between high behavioral inhibition, larger ERN, and the risk for psychiatric disorders (McDermott et al., 2009) and social anxiety disorder (Lahat et al., 2014) has been demonstrated. The ERN is followed by a centroparietal error positivity (Pe) that occurs 2 0 0 -4 0 0 ms after an error (Ullsperger, Fischer, et al., 2014). The Pe is associated with conscious error awareness and is considered a P3b reflecting evidence accumulation for the neces­ sity o f behavioral adjustments (Steinhauser & Yeung, 2010; U ll­ sperger, Fischer, et al., 2014). Although many studies investigated ERN alterations, the subsequent Pe has received less attention in clinical studies. Studies investigating anxiety disorders, including OCD and GAD, did not observe significant group differences for this later positivity (Endrass et al., 2008, 2010; Riesel et al., 2011; W einberg et al., 2010; Xiao et al., 2011). In contrast, several studies in MDD observed reduced Pe amplitudes (Aarts et al., 2013; Georgiadi et al., 2011; Olvet et al., 2010; Schrijvers et al., 2008, 2009; but see Chiu & Deldin, 2007; Holmes & Pizzagalli, 2008). The current study examined performance monitoring in SAD and compared ERP correlates o f performance monitoring (ERN and Pe) between SAD, OCD, and healthy controls. For the SAD group, we predicted enhanced ERN amplitudes, which is based on the relationship between ERN and trait anxiety (Cavanagh & Shackman, 2014; M oser et al., 2013) and enhanced ERN ampli­ tudes in mixed anxiety disorder samples (Ladouceur et al., 2006; M eyer et al., 2013). As it has been shown in many studies, ERN amplitudes should be enhanced in OCD (Endrass & Ullsperger, 2014). In addition, we examined Pe amplitude and behavioral perform ance, but did not predict group differences. Finally, we exam ined in an explorative fashion group differences with regard to the association betw een ERN and sym ptom expres­ sion. A previous study, w hich exam ined a large sam ple of individuals w ith OCD (N = 72), indicated that the ERN en­ hancem ent in OCD should be independent o f sym ptom expres­ sion (Riesel et al., 2014).

Method Participants Twenty-four participants were included in each study group; demographic and clinical characteristics are presented in Table 1. Individuals with OCD were recruited from the outpatient unit of

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Table 1

Demographic, Clinical, and Performance Data o f OCD, SAD, and Healthy Control Groups Variable Demographic Mean (SD) age (years) Gender (males/females), n Mean (SD) education (years) Mean (SD) verbal IQ Mean (SD) clinical score BDI-II OCI-R Y-BOCS LSAS-SR Mean (SD) task performance Accuracy (%) Error reaction time (ms) Correct reaction time (ms) Posterror slowing (ms) Posterror increase in accuracy (%)

OCD group (n = 24)

SAD group (n = 24)

Control group (n = 24)

31.5 (8.7) 7/17 12.1 (1.2) 109.0 (9.3)

31.4(8.8) 7/17 12.5(1.1) 109.0 (9.9)

32.1 (8.4) 7/17 12.2(1.2) 110.5 (9.6) 1.7 (2.0) 3.3 (2.9)

13.4(10.4) 25.8(11.5) 22.0 (4.9) —

92.5 (3.7) 230 (29) 329 (31) 6(16) 4.7 (3.7)

13.5 (8.1) 13.1 (10.3) —

66.3 (22.2) 92.0 (4.0) 237 (23) 343 (26) 16 (35) 3.4 (3.1)

F(2, 69)

P

0.40

.96

0.95 0.19

.39 .83

18.48 36.82

.001 .001

2.73 0.71 2.11 0.83 1.68

.07 .49 .13 .44 .20

— —

90.0 (3.9) 231(19) 328(27) 8(30) 2.8 (4.2)

Note. OCD = obsessive-compulsive disorder; SAD = social anxiety disorder; BDI-II = Beck Depression Inventory II; OCI-R = ObsessiveCompulsive Inventory—Revised; Y-BOCS = Yale-Brown Obsessive-Compulsive Scale; LSAS-SR = Liebowitz Social Anxiety Scale—Self-Report.

the Humboldt-Universitat zu Berlin. Individuals with SAD and healthy comparison subjects were recruited through local adver­ tisement. Groups were matched and did not differ significantly in age, gender, years of education, and verbal intelligence (as mea­ sured by a German vocabulary test; Schmidt & Metzler, 1992). The OCD group included 10 individuals, who were also partici­ pants in our previous study (Riesel et al., 2014). All participants were examined with the Structured Clinical Interview for DSM -IV Axis I Disorders (SCID; First, Spitzer, Gibbon, & Williams, 1995). OCD or SAD had to be the principal diagnosis for each participant in the two clinical groups, according to patient and clinical judgm ent and based on symptom severity. OCD and SAD were not allowed as comorbid disorders in the respective other group. Diagnostic assessments were conducted by trained clinicians (postgraduate level) using SCID interviews. Ex­ clusion criteria for the clinical groups were motoric tics, current substance abuse, lifetime substance dependence, psychotic disor­ ders, previous head trauma, or known neurological disorders. Individuals with SAD and psychiatrically healthy control partici­ pants were first screened by a telephone interview to determine potential exclusion criteria. In addition, psychiatrically healthy control participants, also assessed with the SCID, could not have a lifetime diagnosis o f any Axis I psychological disorder. Depressive and obsessive-com pulsive symptoms were assessed in all participants with the Beck Depression Inventory II (BD I-II; Steer, Ball, Ranieri, & Beck, 1997) and the O bsessive-Compulsive Inventory— Revised (O CI-R; Foa et al., 2002). OCD symptom severity was evaluated using the Y ale-Brow n O bsessiveCompulsive Scale (Y-BOCS; Goodman et al., 1989) in the OCD group, and social anxiety symptoms were evaluated with the Liebowitz Social Anxiety Scale— Self-Report (LSA S-SR; Liebowitz, 1987) in the SAD group. Individuals in the OCD group fulfilled the Diagnostic and Statistical Manual o f Mental Disorders (4th ed.; DSM-IV) criteria for OCD, and 10 individuals had one to three of the following comorbid diagnoses: major depression (n = 7), generalized anxi­ ety disorder (n = 1), panic disorder (n = 2), posttraumatic stress

disorder (n = 1), specific phobia (n — 2), bulimia nervosa in = 1), binge eating disorder (n — 1), and adjustment disorder (n = 1). Individuals in the SAD group fulfilled the DSM-IV criteria for social anxiety disorder, and 11 individuals had one to three of the following comorbid diagnoses: major depression (n = 5), dysthy­ mic disorder (n = 1), panic disorder (n = 3), posttraumatic stress disorder (n = 1), and specific phobia (n = 4). Nine individuals (n = 3 with comorbid disorders) in the OCD group (selective serotonin reuptake inhibitors: n = 9) and six individuals (n = 5 with comorbid disorders) in the SAD group (selective serotonin reuptake inhibitors: n = 1; tricyclic antidepressant: n = 3; benzo­ diazepine: n = 2) were taking psychotropic medication. The study was in accordance with the ethical guidelines o f the Declaration of Helsinki and approved by the local ethics commit­ tee. Participants received verbal and written information about the procedures o f the study, gave written informed consent, and ob­ tained a reimbursement.

Task and Procedure Participants completed an arrow version o f the flanker task (Eriksen & Eriksen, 1974; Kopp, Rist, & Mattler, 1996) during electroencephalography (see Figure 1). On every trial, a target stimulus consisting of five vertically arranged arrows was pre­ sented. Arrows pointed to the left or the right side of the computer screen. Participants were instructed to respond as accurately and as quickly as possible with their right or left index finger according to the direction o f the middle target arrow. The surrounding flanker arrows were all pointing in the same direction and were not relevant for responding. Flanker and target arrows pointed in the same direction in the compatible condition and in opposite direc­ tions in the incompatible condition. Each trial started with a fixation display (900-1,500 ms), which was replaced by the four flanker arrows. After 100 ms, the target arrow was presented for 50 ms together with the flanker arrows and a response interval of 1,000 ms began. The target stimulus consisting of five arrows was 1.2° wide and 1.2° high at a viewing distance of 65 cm. The task

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ENDRASS, RIESEL, KATHMANN, AND BUHLMANN

Figure 1. Schematic depiction of the flanker task. Participants were instructed to respond as fast and as accurately as possible upon presentation of the target screen with the left or right response button in the direction of the middle arrow. Prior to target presentation, four flanker arrows were presented to increase error rates for incompatible trials (flanker and target arrows pointing in opposite directions).

contained 20 practice trials and eight blocks including 60 trials per block. Stimulus compatibility and direction were equally distrib­ uted and pseudorandomized across trials. After each block, partic­ ipants received an instruction to increase response speed in case error rates were below 10%, to increase accuracy in case error rates were above 20%, or to respond as accurately and quickly as possible in the remaining cases. The completion of the task took about 25 min including short breaks between blocks.

2000). Amplitudes were determined at frontocentral electrodes (Fz, FCz, Cz, FC1, and FC2) and time windows were defined from - 5 0 to 0 ms for the positive peak preceding the ERN/CRN and from 0 to 100 ms for the negative peak of ERN/CRN. To enhance signal quality, we determined amplitudes in the time interval ±20 ms surrounding each peak and then averaged them across electrodes. The Pe was quantified as mean amplitude from 200 to 400 ms following response at the electrodes CPz and Pz. Demographic and clinical data as well as response accuracy were compared using one-way analyses of variance. RTs and ERP activity were analyzed with repeated measures analyses of vari­ ance with the within-subject factor response type (correct and error) and between-subjects factor group (OCD, SAD, and control group). Posterror slowing was defined as the difference of RTs in correct trials following incorrect responses minus the RT in correct trials following correct responses. Posterror increase of accuracy was calculated by subtracting the percentage of correct responses in trials following correct responses from the percentage of correct responses in trials following erroneous responses. Pearson corre­ lations were calculated between ERN amplitude and clinical symp­ toms (BDI-II, OCI-R, Y-BOCS, and LSAS-SR) to examine the relationship between clinical symptoms and error processing.

Results Electroencephalogram Recording and Data Analysis Electroencephalographic data were recorded with 64 Ag/AgCl electrodes using two 32-channel BrainAmp amplifiers (Brain Products GmbH, Munich, Germany) and an equidistant EasyCap electrode cap (EasyCap GmbH, Herrsching-Breitbrunn, Germany). Impedances were below 5 kfl, the ground was mounted below T2, and data were referenced to electrode Cz. Two electrodes were placed below the left and right eye and were used to capture eye movements in combination with electrodes mounted in the cap. Data were continuously registered at 500 Hz sampling frequency and bandpass filtered with 0.01 to 250 Hz. Offline, data were filtered with 0.5 to 30 Hz, rereferenced to common average refer­ ence, and ocular artifacts were removed using the multiple source eye correction (Berg & Scherg, 1994) implemented in BESA5 (Brain Electrical Source Analysis, MEGIS Software GmbH, Grafelfing, Germany). Epochs spanning from 400 ms before to 800 ms after response onset were extracted. The average activity of the first 200 ms of each segment served as baseline and was subtracted from the data. Epochs containing voltages exceeding ±100 p,V or voltage steps exceeding ±40 p.V between consecu­ tive data points were excluded from further analysis. Averages were computed for correct and incorrect responses and for each participant. Only trials with response times ranging from 100 to 700 ms were included in averages. On average, this resulted in the exclusion of 0.3 (SD = 0.98) trials due to early and 0.8 (SD = 2.2) trials due to late responses. Groups did not differ with regard to the number of trials excluded due to early, F{2, 69) = 1.31, p = .28, or late reaction time (RT), F(2, 69) = 0.51, p = .60. All partici­ pants committed at least six errors, which is considered sufficient for the analysis of ERN data (Olvet & Hajcak, 2009). ERN and CRN were quantified as peak-to-peak measure to obtain baseline-independent amplitudes of negative deflections by subtracting the amplitude of the preceding positive peak from the negative peak (Falkenstein, Hoormann, Christ, & Hohnsbein,

Demographic and Behavioral Data Groups did not differ in age, education, verbal IQ, and gender (see Table 1). Group differences were observed for depressive, F(2, 69) = 18.48, p < .001, rip = .35, and obsessive-compulsive symptom scores, F(2, 69) = 36.82, p < .001, rip = .52. Both clinical groups had higher symptom scores for depressive (BDIII), and obsessive-compulsive symptoms (OCI-R) than the com­ parison group (ps < .001). The OCD group showed higher OCI-R scores than the SAD group, F (l, 46) = 16.15,p < .001, p{; = .26, but groups did not differ in the degree of depressive symptoms, F( 1, 46) < 0.01, p = .98, rip < .01. Group differences were not observed for behavioral data (see Table 1).

Neural Response During Performance Monitoring Group averages and topographies are displayed in Figure 2. Negativities for errors were more pronounced than for correct responses, F (l, 69) = 145.25, p < .001, Pp = .68. A significant main effect of group was found, F(2, 69) = 6.60, p = .002, pj; = .16. Averaged amplitudes were smaller in healthy controls than in individuals with SAD, F (l, 46) = 10.78, p = .002, pp = .19, and OCD, F (l, 46) = 11.96, p = .001, pp = .21, whereas amplitudes did not differ between clinical groups, F (l, 46) = 0.06, p = .81, Pp < .01. Furthermore, a significant interaction of group and response type was found, F(2, 69) = 3.50, p = .04, pj; = .09. Follow-up analyses indicate that group differences were more pronounced on erroneous than on correct responses. Post hoc comparisons suggest enhanced ERN amplitudes of the SAD group, F (l, 46) = 8.06, p = .007, p^ = .15, and the OCD group, F (l, 46) = 13.37,p = .001, Pp = .23, compared with the control group. In contrast, CRN amplitudes were only significantly enhanced in the SAD group compared with comparison subjects, F (l, 46) = 5.45, p = .02, pp = .11, whereas the amplitude difference between

PERFORMANCE MONITORING IN OCD AND SAD

709

Figure 2. (A) Response-locked event-related potential waveforms for the obsessive-compulsive disorder (OCD) group (red), social anxiety disorder (SAD) group (blue), and healthy control group (black) averaged for all erroneous responses (left) and correct response (right) at frontocentral electrode FCz (upper graph) and centroparietal electrode CPz (lower graph). Negative values are plotted upward. ERN = error-related negativity; CRN = correct-related negativity; Pe = error positivity. Solid lines indicate averaged activity and shades represent standard errors. (B) Topographic distribution (top view) of error-related negativity (upper graph) and correct-related negativity (lower graph). See the online article for the color version of this figure.

the OCD and the control group was not significant, F( 1, 46) = 2.47, p = .12, -rip = .05. Clinical groups did not differ in ERN, F (l, 46) = 0.08, p = .93, < .01 (OCD: M = -9 .3 , SD = 3.7; SAD: M = —9.2, SD = 5.0), and CRN amplitudes, F (l, 46) = 0.83, p = .37, = .02 (OCD: M = -2 .9 , SD = 1.6; SAD: M = -3 .4 , SD = 2.0). The Pe was distributed at parietal electrodes and was more positive for errors than for correct responses, F (l, 69) = 187.18, p < .001, rip = .73 (see Figure 2, lower panel CPz waveform). Groups differences in Pe amplitude were not observed as the main effect of group, F(2, 69) = 1.85, p < .16, Pp = .05, and the interactions of group and response type, F(2, 69) = 2.15, p = .13, rip = .06, were not significant.

Relationship Between Performance Monitoring and Clinical Measures Across all participants, significant correlations of ERN and CRN with depressive symptoms (BDI-II) and of ERN with obsessive-compulsive symptoms (OCI-R) were found, such that higher symptom scores were related to more negative amplitudes

(see Table 2). However, these correlations partially result from group differences in both ERP amplitudes and symptom scores. Therefore, correlations were analyzed separately for each group. Significant correlations between symptom scores and ERN or CRN amplitude were not found in the OCD or control group. In the SAD group, however, significant correlations of depressive symptoms with ERN and at trend level with CRN were found (see Figure 3), whereas correlations with OCI-R or social anxiety symptoms (LSAS-SR) were not significant. Note that within the SAD group, depressive symptoms were not significantly correlated with OCD symptoms, r .25, p = .25, or SAD symptoms, r = .30, p = .15. Visual inspection of the relationship of ERN and depressive symptoms in the SAD group (see Figure 3) suggests that the correlation may depend on one subject, but the analysis using Cook’s distance (Cook & Weisberg, 1982) indicated that none of the subjects exceeded the critical thresh­ old. Furthermore, the correlation between ERN and BDI-II was still significant in the SAD group after excluding the potential outlier, r = —.44, p = .04. To further evaluate differential associations between ERN and BDI-II scores, we determined and then compared regression

ENDRASS, RIESEL, KATHMANN, AND BUHLMANN

710

slopes for the OCD and SAD groups. BDI-II scores significantly predicted ERN amplitude in SAD, p = —.54, t(22) = —3.04, p = .006, but not OCD patients, P = .02, t(22) = 0.10, p = .92 (see Figure 3 for a comparison of regression slopes). The first model included group and BDI-II score, accounting for 6.7% of the variance, was not significant, F(2, 45) = 1.62, p = .21. Including the interaction of group and BDI-II score in the second step increased the amount of explained variance to 19.3%, F (l, 44) = 6.82, p = .012. The interaction term indicates that ERN amplitude was differentially predicted by BDI-II scores between groups, P = -.7 0 , r(44) = -2 .6 1 , p = .012. Figure 3.

Control Analyses Because both groups included a number of participants with comorbid affective disorder diagnosis (MDD and dysthymia), ERN and CRN data were reanalyzed including only individuals without these diagnoses in the OCD (n = 17) and SAD (n = 18) groups and comparing them with healthy controls (n = 24). This analysis revealed significant main effects of group, F(2, 56) = 6.78, p = .002, T|p = .20, response type, F (l, 56) = 139.11, p < .001, T|p = .71, and a group X response type interaction, F(2, 56) = 4.24, p < .02, rip = .13. Both clinical groups showed larger ERN amplitudes than the control group, ps < .05, but the ERN did not differ between the OCD and SAD groups, p = .95. The CRN amplitude did not differ between groups, ps > .19. In addition, larger ERN amplitudes in OCD than in control participants were still seen after excluding individuals with comor­ bid diagnoses or those taking psychotropic medication, p < .002. However, in the OCD group, individuals with medication (n = 9)

Table 2 Pearson Correlations Between Neural Correlates o f Performance Monitoring (Amplitudes o f ERN and CRN) and Clinical Symptoms Group All participants (N = 72) BDI-II OCI-R OCD (n = 24) BDI-II OCI-R Y-BOCS SAD (n = 24) BDI-II OCI-R LSAS-SR Healthy control (n = 24) BDI-II OCI-R

SAD group OCD group

ERN

CRN

-.40** -.34**

-.33** -.1 8

.021 -.1 3 .012

- .1 7 -.0 1 - .1 7

-.54** -.2 3 -.2 7

- .3 8 f -.2 4 - .0 6

.01 -.1 5

.03 .004

Note. ERN = error-related negativity; CRN = correct-related negativity; OCD = obsessive-compulsive disorder; SAD = social anxiety disorder; BDI-II = Beck Depression Inventory II; OCI-R = Obsessive-Compulsive Inventory— Revised; Y-BOCS = Yale-Brown Obsessive-Compulsive Scale; LSAS-SR = Liebowitz Social Anxiety Scale— Self-Report. Clini­ cal symptoms are displayed for all participants and for all three groups separately. < .10. " p < .05. **p < .01. All other correlations are nonsignifi­ cant, ps > .1.

Scatterplots and regression slopes for correlation of errorrelated negativity (ERN) and depression scores (Beck Depression Inven­ tory II; BDI-II) for individuals with social anxiety disorder (SAD; blue) and individuals with obsessive-compulsive disorder (OCD; red). See the online article for the color version of this figure.

showed smaller ERN amplitudes than individuals without medi­ cation (n = 15), t(22) = 2.38, p = .03.1

Discussion This study investigated psychophysiological indicators of per­ formance monitoring in individuals diagnosed with OCD or SAD and healthy control subjects. OCD and SAD groups exhibited altered error monitoring indicated by enhanced ERN amplitudes. Overactive error processing in OCD is in line with previous studies (Endrass & Ullsperger, 2014), but this is the first study providing evidence for ERN alterations in SAD. Although both groups showed similar ERN enhancement, differential effects for depres­ sive symptoms were found. The ERN in SAD was modulated by depressive symptom severity in that larger ERN was found for individuals with SAD with higher BDI-II scores than in individ­ uals with lower scores. In contrast, the ERN was independent of depressive and obsessive-compulsive symptoms in OCD. The finding of enhanced ERN in both clinical groups, OCD and SAD, is in line with studies showing ERN enhancements in other clinical groups, such as GAD (Weinberg, Klein, et al., 2012; Weinberg et al., 2010; Xiao et al., 2011) and MDD (Chiu & Deldin, 2007; Georgiadi et al., 2011; Holmes & Pizzagalli, 2010). Enhanced ERN in SAD is also consistent with findings in healthy populations with higher symptom scores on anxiety-related ques­ tionnaires or samples including individuals with various anxiety disorders (Aarts & Pourtois, 2010; Boksem, Tops, Wester, Meijman, & Lorist, 2006; Hajcak, McDonald, & Simons, 2003, 2004; Ladouceur et al., 2006; Luu, Collins, & Tucker, 2000; Meyer et al., 2013; Meyer, Weinberg, Klein, & Hajcak, 2012). Importantly,

1 To control for potential differences in the signal-to-noise ratio due to a different number of trials included in averages for correct and incorrect responses, we created additional correct response averages based on a random subset of correct trials comparable in number to error trials. Both correct response averages were highly similar (Cronbach’s alpha = .95). In addition, event-related potential analyses were repeated and results did not change. The analysis of variance revealed significant main effects of group, F(2,69) = 5.10,p = .009, ti| = .13, response type, F(2,69) = 100.28,p < .001, tip = .60, and interaction of both factors, F(2, 69) = 4.27, p = .02, ■Up = -11.

PERFORMANCE MONITORING IN OCD AND SAD

there was no difference in ERN amplitude between SAD and OCD groups. These findings suggest that ERN alterations may represent a transdiagnostic marker for internalizing psychopathology (Vaidyanathan, Nelson, & Patrick, 2012; Weinberg, Riesel, & Hajcak, 2012) or trait anxiety (Cavanagh & Shackman, 2014; Moser et al., 2013). In addition, the Pe, a centroparietal positivity and potential response-related P3b, did not differ between groups, which is consistent with earlier studies (Endrass & Ullsperger, 2014). The ERN is considered a fast alarm signal generated in the posterior medial frontal cortex that indicates incoming evidence for the potential necessity of action adaptation (e.g., Ullsperger, Fischer, et al., 2014). Although the current study showed larger ERN signals in OCD and SAD, evidence for associated behavioral performance changes or alterations in posterror behavior was not obtained. This is consistent with other studies reporting ERN enhancements in clinical populations in the absence of altered performance. Thus, it has been suggested that anxiety and depres­ sion may cause qualitative changes in the performance-monitoring system (Aarts & Pourtois, 2010; Aarts et al., 2013). In fact, there is evidence for not only enhanced error monitoring but also en­ hanced general response monitoring in OCD (Klawohn et al., 2014). In healthy individuals, enhanced early performance moni­ toring has been related to more efficient posterror adaptation in order to prevent future errors (Danielmeier, Eichele, Forstmann, Tittgemeyer, & Ullsperger, 2011; Debener et al., 2005). Because no such association was found in OCD, enhanced ERN could therefore indicate a higher concern about errors or their potential consequences that is independent from actual action consequences (Endrass et al., 2010). In addition to the ERN enhancement in both clinical groups, the current study also found differential effects regarding the influence of depression. The association between ERN and depressive symp­ toms was significantly higher in the SAD than in the OCD group as revealed by the comparison of regression slopes between groups. Neither depressive nor obsessive-compulsive symptoms were significantly correlated within the OCD group, which is consistent with earlier studies suggesting that ERN alterations may represent a biomarker or vulnerability indicator for OCD indepen­ dent of current symptoms (e.g., Hajcak et al., 2008; Riesel et al., 2014). In SAD, however, larger ERN amplitudes were related to more severe depressive symptoms. This is in line with studies showing that the ERN is sensitive to mood state manipulations (Olvet & Hajcak, 2012; Wiswede, Munte, Goschke, & Russeler, 2009). However, interpretation and specificity of the relationship between ERN and depressive symptoms is compromised by the fact that only mild-to-moderate depressive symptoms were ob­ served and by moderate nonsignificant correlations of ERN with social anxiety and obsessive-compulsive symptoms in the SAD group. Furthermore, the assessment of trait-anxiety and worry symptoms would have been necessary to determine differential relationships between clinical symptoms and ERN as relationships were revealed for these constructs by two recent meta-analyses (Cavanagh & Shackman, 2014; Moser et al., 2013). Although a modulation of ERN with depression was observed in the SAD group, the ERN was still enhanced in individuals with SAD without comorbid MDD diagnosis, indicating that the ERN en­ hancement is not only a consequence of comorbid depression. Because this was the first study that examined performance mon­

711

itoring in SAD, further studies are necessary to evaluate this relationship and its functional significance. Currently, it is discussed whether changes in performance mon­ itoring represent compensatory consequences of clinical symptoms or a vulnerability indicator for uncertainty or anxiety. Moser et al. (2013) suggested a compensatory error-monitoring hypothesis to explain enhanced ERN in anxiety. The idea is that anxiety and worry lead to diminished resources and reduced task-related pro­ cessing, which is compensated by recruiting increased reactive control as it is observed by the ERN to minimize behavioral deficits. However, based on this interpretation, intraindividual changes in ERN would be expected with changes in clinical symptoms, which was not observed for OCD (Hajcak et al., 2008). Alternatively, the ERN is considered a vulnerability indicator of threat sensitivity or defensive reactivity (Proudfit, Inzlicht, & Mennin, 2013). More specifically, anxiety may cause greater un­ certainty about optimal performance, which is responsible for the increase of ERN amplitudes (Cavanagh & Shackman, 2014). Im­ portantly, all accounts suggest that performance-monitoring alter­ ations may reflect a transdiagnostic phenomenon underlying both anxiety and affective disorders, which is also supported by the current findings of enhanced ERN in SAD and OCD. Limitations of the present study concern sample sizes and the fact that between-subjects comparisons do not inform about causal associations between ERN and depressive symptoms. Stratified samples including individuals showing various degrees of depres­ sive symptoms or the comparison before and after symptom re­ mission (or symptom onset) could elucidate a more causal rela­ tionship. Interpretation of correlational results is also limited by the fact that not all symptom scores were assessed in all groups. Furthermore, clinical groups included individuals with comorbid­ ity and psychotropic medication. However, the ERN in OCD remained enhanced after excluding individuals taking medication or having comorbid diagnoses. The inclusion of individuals taking medication even may have led to an underestimation of ERN amplitudes as indicated by reduced ERN in these individuals. Furthermore, an additional analysis excluding individuals with comorbid MDD, revealed that both clinical groups had larger ERN amplitudes than healthy controls. Finally, the exploratory analysis of the influence of depressive symptoms needs further investiga­ tion because current clinical samples included only individuals reporting mild to moderate depressive symptoms. In conclusion, this study examined performance monitoring in OCD and SAD and revealed that both clinical groups had larger ERN amplitudes than control participants. Initial evidence is pro­ vided for a differential influence of depression on ERN in SAD and OCD. Therefore, further studies are needed to examine whether ERN alterations represent a vulnerability indicator for SAD or a consequence of clinical symptoms.

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Received February 20, 2014 Revision received August 25, 2014 Accepted September 2, 2014 ■

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Performance monitoring in obsessive-compulsive disorder and social anxiety disorder.

Overactive performance monitoring, indexed by greater error-related brain activity, has been frequently observed in individuals with obsessive-compuls...
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