Performance monitoring and error significance in patients with obsessive-compulsive disorder.
ABSTRACT Performance monitoring has been consistently found to be overactive in obsessive-compulsive disorder (OCD). The present study examines whether performance monitoring in OCD is adjusted with error significance. Therefore, errors in a flanker task were followed by neutral (standard condition) or punishment feedbacks (punishment condition). In the standard condition patients had significantly larger error-related negativity (ERN) and correct-related negativity (CRN) ampliudes than controls. But, in the punishment condition groups did not differ in ERN and CRN amplitudes. While healthy controls showed an amplitude enhancement between standard and punishment condition, OCD patients showed no variation. In contrast, group differences were not found for the error positivity (Pe): both groups had larger Pe amplitudes in the punishment condition. Results confirm earlier findings of overactive error monitoring in OCD. The absence of a variation with error significance might indicate that OCD patients are unable to down-regulate their monitoring activity according to external requirements.
- SourceAvailable from: Tanja Endrass[Show abstract] [Hide abstract]
ABSTRACT: Obsessive-compulsive disorder (OCD) is characterized by overactivity in frontal and striatal brain regions, and event-related potential studies have shown increased brain activity during performance monitoring. The error-related negativity (ERN) is a component of the event-related potential that is observed following incorrect responses, and signals the need for behavioral adjustments. ERN enhancements have even been considered as a biomarker or endophenotype of OCD. However over the past years, enhanced ERN amplitudes, although less reliably, were also found in anxiety and affective disorders. These results question the specificity of ERN alterations to OCD. The present review summarizes current findings on performance monitoring and feedback processing in OCD and their relation to behavioral measures. Further, it discusses possible differential mechanisms contributing to amplitude variations in different clinical conditions.Neuroscience & Biobehavioral Reviews 04/2014; · 10.28 Impact Factor
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ABSTRACT: Background Obsessive–compulsive disorder (OCD) is characterized by maladaptive repetitive behaviors that persist despite feedback. Using multimodal neuroimaging, we tested the hypothesis that this behavioral rigidity reflects impaired use of behavioral outcomes (here, errors) to adaptively adjust responses. We measured both neural responses to errors and adjustments in the subsequent trial to determine whether abnormalities correlate with symptom severity. Since error processing depends on communication between the anterior and the posterior cingulate cortex, we also examined the integrity of the cingulum bundle with diffusion tensor imaging. Methods Participants performed the same antisaccade task during functional MRI and electroencephalography sessions. We measured error-related activation of the anterior cingulate cortex (ACC) and the error-related negativity (ERN). We also examined post-error adjustments, indexed by changes in activation of the default network in trials surrounding errors. Results OCD patients showed intact error-related ACC activation and ERN, but abnormal adjustments in the post- vs. pre-error trial. Relative to controls, who responded to errors by deactivating the default network, OCD patients showed increased default network activation including in the rostral ACC (rACC). Greater rACC activation in the post-error trial correlated with more severe compulsions. Patients also showed increased fractional anisotropy (FA) in the white matter underlying rACC. Conclusions Impaired use of behavioral outcomes to adaptively adjust neural responses may contribute to symptoms in OCD. The rACC locus of abnormal adjustment and relations with symptoms suggests difficulty suppressing emotional responses to aversive, unexpected events (e.g., errors). Increased structural connectivity of this paralimbic default network region may contribute to this impairment.NeuroImage: Clinical. 01/2014; 5.
Article: Endophänotypen der Zwangsstörung[Show abstract] [Hide abstract]
ABSTRACT: Zusammenfassung. Die Zwangsstörung ist eine teilweise genetisch vermittelte psychische Störung, die mit neuropsychologischen Be-einträchtigungen einhergeht. Bisher war die Suche nach den genetischen Ursachen wenig erfolgreich, was an der polygenetischen Über-tragung und an der Heterogenität im klinischen Erscheinungsbild der Zwangsstörung liegen könnte. Die Verwendung des Endophäno-typenkonzepts kann möglicherweise dazu beitragen, diese Probleme zu reduzieren. Endophänotypen sind zustandsunabhängige Marker, die näher an den biologischen Ursachen einer Erkrankung liegen als der klinische Phänotyp und mit einem erhöhten genetischen Risiko für die Erkrankung einhergehen. Die im Bereich der Zwangsstörung existierenden Befunde zu Endophänotypen werden in dem vorlie-genden Artikel diskutiert und Implikationen für zukünftige Studien abgeleitet. Zusammenfassend lässt sich sagen, dass vielversprechende Kandidaten-Endophänotypen in den Bereichen Reaktionshemmung, Handlungsüberwachung und kognitive Flexibilität vorliegen. Abstract. Obsessive-compulsive disorder (OCD) is a heritable condition that is associated with neuropsychological deficits. However, genetic underpinnings are difficult to identify and results have been inconsistent. Reasons for this difficulty may be that multiple genes are involved in the etiology of OCD and that the clinical phenotype of OCD is heterogeneous. The use of cognitive and biological endo-phenotypes was suggested as a resolution to these problems. Endophenotypes are state independent markers that exhibit a closer relation with genetic underpinnings than the clinical phenotype itself. In the current review, we discuss the current state of research on candidate endophenotypes for OCD and consider implications and future directions. In conclusion, several promising candidate endophenotypes for OCD have been identified, namely response inhibition, performance monitoring, and cognitive flexibility.Zeitschrift für Psychiatrie Psychologie und Psychotherapie 01/2013; 61(3):155-165. · 1.99 Impact Factor
Performance monitoring and error significance in patients with
Tanja Endrass*, Beate Schuermann, Christan Kaufmann, Ru ¨diger Spielberg, Rainer Kniesche,
Humboldt-Universita ¨t zu Berlin, Germany
Obsessive-compulsive disorder (OCD) is a mental disorder
characterized by the presence of obsessions, i.e. recurrent and
persistent thoughts that are unwanted, and compulsions, i.e.
repetitive behaviors or mental acts that the person feels driven to
perform. Patients typically feel that something is incomplete or
wrong and that an action is needed to compensate. Neuroimaging
studies consistently report enhanced activity in fronto-medial and
striatal brain regions, including the anterior cingulate cortex (ACC,
Aouizerate et al., 2004), which plays an important role in
performance monitoring (Ridderinkhof et al., 2004). Originally,
studies on performance monitoring in OCD were driven by the
hypothesis of Pitman (1987) who suggested in his cybernetic
model of obsessive-compulsive pathophysiology that excessive or
hyperactive error signals might be a common characteristic of OCD
The error negativity (Ne, Falkenstein et al., 1990) or error-
related negativity (ERN, Gehring et al., 1993) is a negative
component in the event-related potential (ERP) that occurs 50–
100 ms after the execution of an incorrect response and has its
maximum at fronto-central scalp locations. The source of this
activity is located in the anterior cingulate cortex (ACC; Dehaene
et al., 1994; Debener et al., 2005). The ERN is typically followed by
the error positivity (Pe, Falkenstein et al., 1991, 2000). The Pe has a
centro-parital distribution and occurs within 200–500 ms after
incorrect responses. The functional significance of these compo-
nents is still under discussion. Originally, it has been suggested
that the ERN might reflect an error detection process (Falkenstein
et al., 1990; Gehring et al., 1993). Alternatively, Holroyd and Coles
(2002) consider the ERN as indicator of a reinforcement learning
signal, originating from the midbrain dopamine system, and
signaling ‘‘worse than expected’’ outcomes. In terms of the conflict
theory (Botvinick et al., 2001; Yeung et al., 2004), the ERN
represents a conflict signal that also originates in the ACC and is
elicited by multiple, simultaneously active response tendencies.
The models accounting for the ERN converge in the assumption
that the consequence of error or conflict processing is the
adjustment of cognitive control serving to prevent future errors.
The Pe has been shown to be related to error awareness. Whereas
ERN amplitude and ACC activity remain unchanged, the Pe
amplitude is significantly reduced when errors are not recognized
(Endrass et al., 2005, 2007; Klein et al., 2007; Nieuwenhuis et al.,
2001; O’Connell et al., 2007). Additionally, it has been suggested
that the Pe would reflect error salience or the motivational
significance of an error (Overbeek et al., 2005).
The question whether performance monitoring is altered in
OCD patients has been addressed with several ERP studies and
Biological Psychology 84 (2010) 257–263
A R T I C L EI N F O
Received 12 November 2009
Accepted 3 February 2010
Available online 10 February 2010
Obsessive-compulsive disorder (OCD)
Error-related negativity (ERN)
A B S T R A C T
Performance monitoring has been consistently found to be overactive in obsessive-compulsive disorder
(OCD). The present study examines whether performance monitoring in OCD is adjusted with error
significance. Therefore, errors in a flanker task were followed by neutral (standard condition) or
punishment feedbacks (punishment condition). In the standard condition patients had significantly
larger error-related negativity (ERN) and correct-related negativity (CRN) ampliudes than controls. But,
in the punishment condition groups did not differ in ERN and CRN amplitudes. While healthy controls
showed an amplitude enhancement between standard and punishment condition, OCD patients showed
no variation. In contrast, group differences were not found for the error positivity (Pe): both groups had
larger Pe amplitudes in the punishment condition. Results confirm earlier findings of overactive error
monitoring in OCD. The absence of a variation with error significance might indicate that OCD patients
are unable to down-regulate their monitoring activity according to external requirements.
? 2010 Elsevier B.V. All rights reserved.
* Corresponding author at: Humboldt-Universita ¨t zu Berlin, Institut fu ¨r Psycho-
logie, Rudower Chaussee 18, 12489 Berlin, Germany. Tel.: +49 30 2093 4737;
fax: +49 30 2093 4859.
E-mail address: firstname.lastname@example.org (T. Endrass).
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/biopsycho
0301-0511/$ – see front matter ? 2010 Elsevier B.V. All rights reserved.
revealed enhanced ERN amplitudes in this patient group (Endrass
et al., 2008; Gehring et al., 2000; Johannes et al., 2001; Ruchsow
et al., 2005). Larger ERNs were also reported in a subclinical group
with elevated self-reported obsessive-compulsive (OC) character-
istics (Gru ¨ndler et al., 2009; Hajcak and Simons, 2002) and in
children with OC behaviors (Santesso et al., 2006). Further,
increased ERN amplitudes may be a trait marker for obsessive-
compulsive psychopathology since amplitudes did not change
with successful treatment in children with OCD diagnosis (Hajcak
et al., 2008). Inconsistent results were obtained from two studies
with probabilistic learning tasks that failed to reveal group
differences (Gru ¨ndler et al., 2009; Nieuwenhuis et al., 2005).
Interestingly, OCD patients showed also enhanced amplitudes
after correct reactions (Endrass et al., 2008; Hajcak and Simons,
2002), the so-called correct-related negativity (CRN, Ford, 1999).
This might indicate that OCD patients not only generate
hyperactive error signals but that this overactivity might be
caused by hyperactive response monitoring in general, a process
that contributes to both ERP components. In contrast to the ERN,
the error positivity has been examined in OCD only in a few
studies. An amplitude enhancement was reported by Santesso
et al. (2006), whereas no alteration was found by Endrass et al.
(2008). Further evidence for an overactive performance monitor-
ing system in OCD has been revealed from functional magnetic
resonance imaging (fMRI). In a continuous performance task with
four conflict levels, OCD patients showed both higher error-related
and conflict-related activity in the ACC, and these activities were
positively correlated with symptom severity (Ursu et al., 2003).
Consistent with this finding, Maltby et al. (2005) reported
enhanced error- and conflict-related activity in the ACC and in
fronto-striatal regions, and Fitzgerald et al. (2005) found higher
error-related activation in the rostral part of the ACC in OCD
Although hyperactive performance monitoring has been
repeatedly found in OCD patients, the function of this alteration
and its behavioral implications are still poorly understood. In
healthy subjects performance monitoring is strengthened in
conditions with higher error relevance or salience. The ERN is
enhanced when accuracy is emphasized over speed (Falkenstein
et al., 2000; Gehring et al., 1993), when errors are associated with a
high monetary risk, or when errors are committed during social
evaluation (Hajcak et al., 2005). Furthermore, error-related brain
activity predicted subsequent post-error slowing (Debener et al.,
2005). In a probabilistic learning task individuals who learned
more from negative than from positive feedback (negative
learners) had larger ERNs than positive learners (Frank et al.,
2005, 2007). Taken together, these studies indicate that in healthy
subjects the ERN amplitude is susceptive to manipulations of the
value of anerror and codes subsequent behavioraladjustment. Yet,
behavioral correlates of performance monitoring alterations in
OCD have not been identified. OCD patients showed normal
response accuracy and only one study found an increase of post-
error slowing (Fitzgerald et al., 2005; but see Endrass et al., 2008;
consistent with the clinical impression that OCD patients feel
correlates have not been identified yet.
The aim of the present study is to elucidate the functional
relevance of performance monitoring alterations in OCD. Especial-
ly, we aimed at exploring whether perceived error significance is
related to these alterations. Therefore, we tested whether ERN and
money. Whereas a clear effect of error significance on ERN
amplitude is expected in healthy controls, we suspect that OCD
patients are less able to adjust the activity of their performance
monitoring system to actual error significance. Second, we also
examined whether the Pe in OCD patients depends on error
significance. If the Pe reflects conscious motivational significance
of an error, enhanced Pe amplitudes in OCD patients might be
expected and could reflect their excessive concern about errors.
22 OCD patients and 22 healthy control subjects participated in the experiment.
Further subject characteristics are listed in Table 1. All patients fulfilled the DSM-IV
criteria for OCD as assessed with the Structured Clinical Interview for DSM-IV
(SCID-I, German version: Wittchen et al., 1997). They received cognitive-behavioral
treatment at the outpatient clinic of the Department of Psychology, Humboldt-
Universita ¨t zu Berlin. Six patients had current comorbid diagnoses: major
depression (n = 2), anxiety disorder (n = 2) and personality disorder (n = 3). Seven
patients were taking psychotropic medications (clomipramine, n = 2; sertaline,
n = 1; fluoxetine, n = 2; mirtazapine, n = 1; fluvoxamine, n = 1).
Healthy comparison subjects were matched for gender, age and verbal
intelligence. Verbal intelligence was measured using a German vocabulary test
(Wortschatztest, WST, Schmidt and Metzler, 1992). No past or present psychiatric
diseases were reported by the comparison subjects. All participants had normal or
corrected-to-normal vision and reported no history of head trauma or neurological
disease. Obsessive-compulsive psychopathology was assessed in patients via self
report using the Obsessive-Compulsive Inventory-Revised (OCI-R, Foa et al., 2002),
and via expert rating using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS,
Goodman et al., 1989) administered by a trained clinician. OCD patients also
reported the degree of their depressiveness using the Beck Depression-Inventory
(BDI, Beck et al., 1961). Participants were paid 8s per hour for participation and an
additional bonus depending on performance. Prior to study participation, all
subjects received verbal and written explanation of the purpose and procedures of
the study and gave their written informed consent in accordance to the ethical
guidelines of the Declaration of Helsinki. Thestudy was approved by thelocal ethics
2.2. Task and procedure
A modified version of the flanker interference task (Eriksen and Eriksen, 1974;
Kopp et al., 1996) was used, with an additional manipulation of error significance.
Subsequent to each response participants received feedback about its correctness.
The task was administered in a standard and a punishment condition. In the
punishment condition 20 cents were subtracted from the starting amount of 20 s
each time an error was committed or the response was too slow. As shown in Fig. 1,
in the beginning of each trial participants saw a fixation mark at the center of the
screen with a variable duration of 800–1200 ms. Subsequently, four horizontal
flanker arrows were presented, all pointing either to the left or to the right. After
100 ms, the target arrow was presented between the flanker arrows for 30 ms. The
complete display consisting of target and flanker arrows was 1.28 tall and 1.28 wide.
Participants were instructed to respond as quickly and as accurately as possible
with the left or right index finger in accordance with the direction of the target
arrow. 900 ms after target onset a feedback was presented. In the standard
condition feedbacks indicated whether the last response was correct, incorrect, or
slower than an individually determined response deadline. In the punishment
condition, incorrect and slow responses were additionally punished with a loss of
20 cents. Individual response deadlines were determined during initial practice
In each experimental condition 480 trials were presented in two separate blocks.
Half of the trials in each condition were compatible trials with target and flanker
arrows pointing in the same direction and half of the trials were incompatible trials
with target and flanker arrows pointing in opposite directions. Stimulus
compatibility and direction (left and right) were varied pseudo-randomly across
Demographic and psychopathological characteristics of OCD patients and healthy
controls (means and standard deviations).
Healthy controlsOCD patients
Years of education
Age at illness onset
Illness duration (years)
Abbreviations: BDI, Beck Depression-Inventory; OCI-R, Obsessive-Compulsive
Inventory-Revised; Y-BOCS, Yale-Brown Obsessive Compulsive Scale.
T. Endrass et al./Biological Psychology 84 (2010) 257–263
trials. The sequence of standard and punishment blocks was counterbalanced
between participants. Each punishment block started with an amount of 20 s and
participants were told that they would receive the real sum of money that was left
at the end of the better one of the two punishment blocks. The total duration of the
experiment was about 45 min.
2.3. Data recording and analysis
The electroencephalogram (EEG) was recorded with an EasyCap electrode
system (EASYCAP GmbH, Herrsching-Breitbrunn, Germany) from 61 head sites of
an equidistant electrode montage and four additional positions (IO1, IO2, Nasion
and Neck). All electrodes were referenced to Cz and impedances of the electrodes
(Brain Products GmbH, Munich, Germany). Signals were digitized with a sampling
rate of 500 Hz and a resolution of 0.1 mV. The time constant was set to 10 s.
The EEG data were referenced offline to average reference and eye movement
artifacts were removed using the multiple source eye correction method (MSEC,
Surrogate Method, Berg and Scherg, 1994) implemented in BESA5 (Brain Electrical
were conducted using BrainVision Analyzer 1.05 software (Brain Products GmbH,
Munich, Germany). The continuous EEG data were filtered with a low-pass filter of
40 Hzand segmentedinto epochs. Theepochs started200 msbefore response onset
and lasted 1200 ms. The mean activity in the interval from 200 to 100 ms before
response onset was used for baseline correction. Epochs still containing artifacts
were excluded from further analyses. Individual averages were obtained separately
for correct and incorrect response in the two experimental conditions.
For statistical analysis ERN and CRN amplitudes were determined in response-
locked averages. Peak-to-peak amplitudes were calculated by subtracting the
positive peak amplitude immediately preceding the ERN or CRN from the negative
peak amplitude of the ERN or CRN. The positive peak was searched in the 100 ms
interval before response onset and the negative peak in the 150 ms interval
following response onset. Peaks were searched at FCz and Fz and amplitudes were
calculated. Although a peak-to-peak measure helps to prevent that ERN/CRN effects
are due to overlapping processes that differ in timing or slow activity, it is also
relevant to compare groups in terms of mean amplitude measures since groups
might also differ in absolute ERN/CRN activity. Therefore, mean amplitudes were
determined in the time range from 0 to 80 ms after the response. Pe amplitudes
were determined as mean amplitude in the time window 300–500 ms after
response at CPz and Pz because there was not always a clear peak detectable.
Repeated-measurement ANOVAs were computed with the between-subjects
factor group (OCD vs. control) and the within-subject factors electrode (for ERN/
CRN: Fz, FCz; for Pe: CPz, Pz), response type (correct vs. error), and condition
(standard vs. punishment). When main effects or interactions were significant,
Bonferroni corrected p-values are reported for post hoc comparisons.
Additional analyses within the OCD group were conducted to examine the
influence of medication status and symptom severity on ERP results. The
medication effect was analyzed with post hoc between group comparisons (t-
test) for ERN/CRN amplitudes in both conditions. Correlation coefficients (Pearson
r) were used to examine the association between obsessive-compulsive or
depressive symptom severity and ERN/CRN amplitudes at FCz.
3.1. Behavioral results
Behavioral results are presented in Table 2. Significant
differences between standard and punishment condition were
not obtained with regard to error rates (F(1,42) = 1.19, p = .28),
error reaction time (F(1,42) = 1.27, p = .27), and correct reaction
time (F(1,42) = 2.30, p = .13). Further, groups did not differ
regarding errors committed or reaction times for correct or
incorrect responses (all F-values < 1); there was also no interac-
tion of condition with group (all F-values < 1). Post-error slowing
was observed by comparing reaction times in correct trials
following correct trials with reaction times in correct trials
following errors (F(1,42) = 107.32, p < .001). Post-error slowing
did not vary with condition or group status (F-values < 1).
Consistent with earlier studies reaction times were faster for
incorrect than correct responses (F(1,42) = 503.80, p < .001), and
for responses in compatible trials than incompatible trials (277 ms
vs. 355 ms, F(1,42) = 718.93, p < .001). Again, OCD patients and
healthy controls displayed similar reaction times in both condi-
tions (F-values < 1).
3.2. ERP results
Fig. 2 presents response-locked ERPs for OCD patients and
healthy participants. Both groups show pronounced negativities
following errors compared to correct responses with a fronto-
central distribution. For a detailed overview of ERP measures,
average peak amplitudes are reported in Table 3. A repeated-
measurement ANOVA revealed that the ERN was more negative
than the CRN as reflected by a significant main effect of response
type (F(1,42) = 156.34, p < .001). Whereas the ERN had a clear
maximum at FCz, the CRN amplitude did not differ between
electrodesites(response type ? electrode
p < .001). A significant main effect condition (F(1,42) = 9.20,
p < .01) and its interaction with response type (F(1,42) = 4.84,
p < .05) indicates that amplitudes were selectively enhanced for
erroneous responses (p < .01) in the punishment condition
compared to the standard condition. There was no overall
difference between groups (F(1,42) = 2.54, p = .119), but there
were significant interactions between group and condition
(F(1,42) = 17.64, p < .001), and between group, condition and
response type (F(1,42) = 10.74, p < .001). Groups differed only in
F(1,42) = 66.88,
Fig. 1. Schematic depiction of the modified flanker task. Participants were
instructed to respond with the left or right index finger in accordance with the
direction of the target arrow (Flanker + Target). The response was followed by a
feedback indicating whether the response was correct (‘‘richtig’’), incorrect
(‘‘falsch’’), or too slow (‘‘zu langsam’’) in the standard condition. In the
punishment condition, incorrect and slow responses were additionally punished
with loss of 20 cents.
Taskperformanceintermsoferror rates,reaction timesandpost-errorslowinginthestandardandpunishmentconditionfor22OCDpatients and22healthycontrols(means
and standard deviations).
Percentage of errorsCorrect RT compatibleCorrect RT incompatibleError RT Post-error slowing
T. Endrass et al./Biological Psychology 84 (2010) 257–263
the standard condition where patients had more negative ERN
(p < .01) and CRN (p < .05) amplitudes compared to controls. In
the punishment condition, both groups had similar ERN ampli-
tudes, but patients still had larger CRN amplitudes, that did not
differ significantly from controls (p = .159). Whereas in OCD
patients neither ERN nor CRN amplitudes differed between
conditions (p’s > .20), healthy controls had larger ERN amplitudes
in the punishment condition than in the standard condition
(p < .01), but similar CRN amplitudes in the two conditions
(p = .35). In fact, in OCD patients ERN amplitudes were numerically
even smaller in the punishment compared to the standard
condition (?8.49 mV vs. ?9.20 mV).
A second analysis on early response-locked negativities used
mean amplitude data and revealed similar effects with respect to
group differences (Fig. 2B). A marginally significant group main
effect(F(1,42) = 3.98,
p = .053) varied with condition
Fig. 2. (A) Response-locked grand average waveforms for the error-related negativity (ERN) and the error positivity (Pe) of healthy controls (left) and OCD patients (right) at
FCz (upper graph) and CPz (lower graph) for correct (dashed lines) and incorrect responses (solid lines) in the standard (black) and punishment condition (red). (B) To
compare between OCD patients (black lines) and healthy controls (grey lines), response-locked grand average waveforms are displayed at FCz in the standard (left) and
punishment condition (right). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
Peak ERN and CRN amplitudes (inmV) at Fz and FCz and mean Pe amplitudes at CPz
and Pz (300–500ms) in OCD patients (OCD) and healthy controls (HC) aredisplayed
separately for the standard and punishment condition and for erroneous and
Standard conditionPunishment condition
ErrorCorrect Error Correct
OCDHC OCD HCOCDHCOCDHC
T. Endrass et al./Biological Psychology 84 (2010) 257–263
(F(1,42) = 4.81, p < .05) and with condition and response type
(F(1,42) = 5.30, p < .05). Compared to controls, patients had
significantly lager ERN (p < .05) and CRN (p < .05) amplitudes in
the standard condition. In the punishment condition, the ERN
amplitude did not differ between groups, but the CRN was also
enhanced in patients, though not significantly (p = .086). Again,
only controls showed larger ERN amplitudes in the punishment
condition (p < .05). Further, the analysis revealed main effects for
responsetype(F(1,42) = 145.92,
(F(1,42) = 39.44, p < .001) as well as an interaction between these
factors (F(1,42) = 59.82, p < .001).
The error positivity is also depicted in Fig. 2. Statistical analysis
condition and electrode site (CPz vs. Pz). Compared with correct
trials, errors were followed
(F(1,42) = 146.40, p < .001) and the Pe was significantly more
pronounced in the punishment than in the standard condition
(F(1,42) = 5.78, p < .03). The response type effect significantly
interacted with electrode site (F(1,42) = 5.88, p < .02). Group
differences were not found (F-values < 1.1).
p < .001) and electrode
by larger positive deflections
3.3. Medication effects
Since seven patients were taking medication at the time of
study participation, ERN/CRN amplitudes were compared between
patients with and without current medication. An ANOVA with
medication status (7 patients vs. 15 patients) as between subject
factor did neither reveal a significant main effect for medication
status nor an interaction with this factor (F(1,20) < 1.5). Subse-
quent between subject comparisons for ERN/CRN amplitudes in
both conditions also failed to reveal significant results (p’s > .30).
In fact, rather similar ERN/CRN amplitudes were measured for
medicated and unmedicated patients (e.g. ERN in standard
condition: ?10.76 mV vs. ?10.67 mV; in punishment condition:
?9.85mV vs. ?10.42 mV).
Correlations between ERN/CRN amplitudes in both conditions
with symptom measures were computed (uncorrected p-values
are reported). A meaningful relation between depressive symp-
toms and ERN or CRN amplitudes was not found (p’s > .25). A weak
association appeared between standard condition ERN amplitude
and obsessive-compulsive symptoms (OCI-R: r = ?.23, p = .156; Y-
BOCS: r = ?.38, p < .05). This correlation suggests that patients
with more severe OCD symptoms had more negative ERN
amplitudes. All other correlations were not significant.
This experiment investigated the influence of error significance
on performance monitoring in OCD patients. Consistent with
earlier research, OCD patients had larger ERN amplitudes than
healthy controls during performance monitoring (Endrass et al.,
2008; Gehring et al., 2000; Gru ¨ndler et al., 2009; Hajcak et al.,
2008; Hajcak and Simons, 2002; Johannes et al., 2001; Ruchsow
et al., 2005; Santesso et al., 2006). Importantly, in contrast to
healthy subjects who showed an ERN enhancement with higher
error significance (Hajcak et al., 2005), this effect was not observed
in OCD patients. Instead, patients showed already large negative
deflections in the standard condition and amplitudes were not
patients had not only larger negative deflections following errors
but also larger CRN amplitudes following correct responses
(Endrass et al., 2008; Hajcak and Simons, 2002). In contrast to
ERN and CRN, the Pe did not reveal group differences. Independent
of group status, the Pe varied between standard and punishment
condition with larger positive deflections in the punishment
condition. ERP effects are not associated with performance
variations between groups or conditions since differences at the
behavioral level were not obtained.
Originally, it has been suggested that OCD patients show
hyperactive error signals and thus enhanced ERN amplitudes
because of a comparator dysfunction that detects a mismatch
between actual and intended response (Gehring et al., 2000;
Pitman, 1987). Apart from enlarged ERN amplitudes the present
study as well as earlier studies revealed also enhanced CRN
amplitudes in OCD patients (Endrass et al., 2008; Hajcak and
Simons, 2002). This suggests that performance monitoring is not
only altered during error processing, but also during correct
response processing. One possibility is, that OCD patients might
show overactive response monitoring or evaluation that con-
tributes to both ERP components (Endrass et al., 2008). Alterna-
tively, it has been suggested that the CRN might reflect an
independent monitoring process that signals a response strategy
conflict and the need to optimize performance (Bartholow et al.,
2005). According to this account the larger CRN in OCD could be
interpreted independently from ERN alterations and might reflect
an error-independent monitoring process that represents an
increased signal to further optimize performance even during
correct behavior. Group differences in CRN amplitudes were also
supported by the finding that OCD patients not only demonstrated
larger peak-to-peak CRN amplitudes but also more negative
sustained activity for correct responses in the mean amplitude
analysis (Fig. 2B). Accordingly, OCD patients might show both a
true CRN enhancement as well as a difference in slow activity
compared to control. However, differences between conditions
were less clear for the CRN. Whereas, the CRN did not differ
between conditions in controls and patients, group differences
werepresentinthestandard conditionand wereabsentorreduced
in the punishment condition. Further studies will be needed to
fully understand the function of the CRN and its alteration in OCD.
In the present study performance monitoring of OCD patients
did not vary with action consequences. Only healthy controls had
significantly increased error-related brain activity in the punish-
ment condition compared with the standard condition. This
replicates earlier findings and supports the interpretation that
the ERN is sensitive to the motivational significance of errors
(Hajcak et al., 2005). In contrast, OCD patients showed enhanced
with error significance. Accordingly, OCD patients demonstrated
overactive performance monitoring only in situations with lower
error significance.However, performancemonitoring didnot differ
between groups in the punishment condition. This could be due to
a ceiling effect in that OCD patients already reached the maximum
monitoring activity in the standard condition and were unable to
further increase monitoring activity. Alternatively, OCD patients
might show normal monitoring activity in the punishment
condition but overactive monitoring in the standard condition.
performance monitoring activity according to context require-
ments. Thus, OCD patients do not adequately adjust monitoring
patients (Chiu and Deldin, 2007; Hajcak et al., 2005). This is also
consistent with the finding that performance monitoring altera-
tions remained stable even after symptom remission during
psychotherapy (Hajcak et al., 2008).
Interestingly, the size of the error positivity did not differ
between groups while amplitudes were larger in the punishment
condition. ERN and Pe appear to reflect different aspects in
performance monitoring. While the ERN reflects an early
automatic process that is directly linked to error commission
T. Endrass et al./Biological Psychology 84 (2010) 257–263
awareness (Endrass et al., 2007; Nieuwenhuis et al., 2001) and
might reflect a motivational evaluation of an error (Overbeek et al.,
2005). The enhancement of the Pe in the punishment condition
might be due to enhanced subjective error salience, and as a
consequence error awareness is also higher in this condition. The
absence of Pe group differences together with the experimental
variation indicates that this later aspect of performance monitor-
ing reflecting the conscious motivational evaluation of errors is
unimpaired in OCD patients.
Two previous studies failed to find enhanced error-related brain
activity in OCD patients (Nieuwenhuis et al., 2005) and in a
subclinical group with high OC symptomatology (Gru ¨ndler et al.,
2009). Both studies used probabilistic learning tasks and examined
response- and feedback-related brain potentials. Interestingly,
Gru ¨ndler et al. (2009) showed within the same sample smaller
for participants with higher OC symptoms. The present study
revealed a very similar pattern of results. ERN group differences
were only obtained in the standard condition but not in the high
the error significance might be higher during probabilistic learning
because participantshavetocarefullyattend tofeedbackinorderto
learn in this task. The absence of group differences in these highly
demanding tasks might be caused by the enhancement of
monitoring activity of healthy controls to the level of OCD patients.
The interpretation of the present results may be limited since
six patients with comorbid psychiatric disorders were included. In
particular, depressive symptoms might cause a problem since ERN
enhancements have also been found for depression (Chiu and
Deldin, 2007; Tucker et al., 2003; but Ruchsow et al., 2004, 2006;
Schrijvers et al., 2009). Therefore, it has been suggested that
overactive performance monitoring might not be specific to OCD
but might be caused by a common process that underlies both
disorders. Although depressive and OCD patients have both
enhanced ERN amplitudes, there are also pronounced differences.
CRN enhancement is only present in OCD patients and the ERN
variation with error significance differs between groups. Patients
with depression show a marked increase of error-related brain
activity with punishment (Chiu and Deldin, 2007), which could not
be found for OCD patients in the present study. This dissociation
suggests that the present results cannot be explained with
depressive comorbidity in OCD patients. Furthermore, significant
associations between depressive symptoms and ERN or CRN
amplitudes were not detected in the present sample. A second
limitation is that seven patients were taking antidepressant
medication during the study. In accordance with previous
research, post hoc comparisons did not reveal group differences
(de Bruijn et al., 2004, 2006).
In summary, the present study confirmed earlier results
indicating that OCD patients not only show enhanced ERN but
also enhanced CRN amplitudes. Second, the error-related brain
activity of OCD patients could not be further enhanced with
experimentally induced higher error significance. Since alterations
in the standard condition were not only found for errors but also
for correct reactions, we suggest that the OCD patients may suffer
from overactive alarm signals that indicate that the current
response strategy is suboptimal and needs to be optimized,
independent from actual response outcome. This deviation is
observable in situations when the consequence of an action is less
relevant, but dissolves in more threatening situations when non-
OCD subjects also increase their monitoring activity. This effect
was interpreted as a dysfunction of OCD patients to adequately
adjust or down-regulate performance monitoring activity to
context requirements. Conscious motivational evaluation of errors
as reflected by the Pe appears to be normal in OCD patients.
This work was supported by the German Research Foundation
Aouizerate, B., Guehl, D., Cuny, E., Rougier, A., Bioulac, B., Tignol, J., et al., 2004.
Pathophysiology of obsessive-compulsive disorder: a necessary link between
phenomenology, neuropsychology, imagery and physiology. Progress in Neu-
robiology 72 (3), 195–221.
Bartholow, B.D., Pearson, M.A., Dickter, C.L., Sher, K.J., Fabiani, M., Gratton, G., 2005.
Strategic control and medial frontal negativity: beyond errors and response
conflict. Psychophysiology 42 (1), 33–42.
Beck, A.T., Erbaugh, J., Ward, C.H., Mock, J., Mendelsohn, M., 1961. An inventory for
measuring depression. Archives of General Psychiatry 4 (6), 561–571.
Berg, P., Scherg, M., 1994. A multiple source approach to the correction of eye
artifacts. Electroencephalography and Clinical Neurophysiology 90 (3), 229–
Botvinick, M.M., Braver, T.S., Barch, D.M., Carter, C.S., Cohen, J.D., 2001. Conflict
monitoring and cognitive control. Psychological Review 108 (3), 624–652.
Chiu, P.H., Deldin, P.J., 2007. Neural evidence for enhanced error detection in major
depressive disorder. American Journal of Psychiatry 164 (4), 608–616.
de Bruijn, E.R., Hulstijn, W., Verkes, R.J., Ruigt, G.S., Sabbe, B.G., 2004. Drug-induced
stimulation and suppression of action monitoring in healthy volunteers.
Psychopharmacology 177 (1–2), 151–160.
de Bruijn, E.R., Sabbe, B.G., Hulstijn, W., Ruigt, G.S., Verkes, R.J., 2006. Effects of
antipsychotic and antidepressant drugs on action monitoring in healthy volun-
teers. Brain Research 1105 (1), 122–129.
Debener, S., Ullsperger, M., Siegel, M., Fiehler, K., von Cramon, D.Y., Engel, A.K., 2005.
Trial-by-trial coupling of concurrent electroencephalogram and functional
magnetic resonance imaging identifies the dynamics of performance monitor-
ing. Journal of Neuroscience 25 (50), 11730–11737.
Dehaene, S., Posner, M.I., Tucker, D.M., 1994. Localization of a neural system for
error detection and compensation. Psychological Science 5 (5), 303–305.
Endrass, T., Franke, C., Kathmann, N., 2005. Error awareness in a saccade counter-
manding task. Journal of Psychophysiology 19 (4), 275–280.
Endrass, T., Klawohn, J., Schuster, F., Kathmann, N., 2008. Overactive performance
monitoring in obsessive-compulsive disorder: ERP evidence from correct and
erroneous reactions. Neuropsychologia 46 (7), 1877–1887.
Endrass, T., Reuter, B., Kathmann, N., 2007. ERP correlates of conscious error
recognition:aware andunawareerrorsinanantisaccadetask. EuropeanJournal
of Neuroscience 26 (6), 1714–1720.
Eriksen, B., Eriksen, C.B., 1974. Effects of noise letters upon the identification of a
target letter in a non-search task. Perception and Psychophysics 16, 143–169.
Falkenstein, M., Hohnsbein, J., Hoormann, J., Blanke, L., 1990. Effects of errors in
choice reaction tasks on the ERP under focused and divided attention. In:
Brunia, C.H.M., Gaillard, A.W.K., Kok, A. (Eds.), Psychophysiological Brain Re-
search. 1st ed. Tilburg University Press, Tilburg, pp. 192–195.
Falkenstein, M., Hohnsbein, J., Hoormann, J., Blanke, L., 1991. Effects of crossmodal
divided attention on late ERP components: II. Error processing in choice reac-
tion tasks. Electroencephalography and Clinical Neurophysiology 78 (6), 447–
Falkenstein, M., Hoormann, J., Christ, S., Hohnsbein, J., 2000. ERP components on
reaction errors and their functional significance: a tutorial. Biological Psychol-
ogy 51 (2–3), 87–107.
2005. Error-related hyperactivity of the anterior cingulate cortex in obsessive-
compulsive disorder. Biological Psychiatry 57 (3), 287–294.
Foa, E.B., Huppert, J.D., Leiberg, S., Langner, R., Kichic, R., Hajcak, G., et al., 2002. The
obsessive-compulsive inventory: development and validation of a short ver-
sion. Psychological Assessment 14 (4), 485–496.
Ford, J.M., 1999. Schizophrenia: the broken P300 and beyond. Psychophysiology 36
Frank, M.J., D’Lauro, C., Curran, T., 2007. Cross-task individual differences in error
processing: neural, electrophysiological, and genetic components. Cognitive
Affective & Behavioral Neuroscience 7 (4), 297–308.
Frank, M.J., Woroch, B.S., Curran, T., 2005. Error-related negativity predicts rein-
forcement learning and conflict biases. Neuron 47 (4), 495–501.
Gehring, W.J., Goss, B., Coles, M.G.H., Meyer, D.E., Donchin, E., 1993. A neural system
for error-detection and compensation. Psychological Science 4 (6), 385–390.
Gehring, W.J., Himle, J., Nisenson, L.G., 2000. Action-monitoring dysfunction in
obsessive-compulsive disorder. Psychological Science 11 (1), 1–6.
Goodman, W.K., Price, L.H., Rasmussen, S.A., Mazure, C., Fleischmann, R.L., Hill, C.L.,
et al., 1989. The Yale-Brown Obsessive Compulsive Scale. I. Development, use,
and reliability. Archives of General Psychiatry 46 (11), 1006–1011.
Gru ¨ndler, T.O., Cavanagh, J.F., Figueroa, C.M., Frank, M.J., Allen, J.J., 2009. Task-
related dissociation in ERN amplitude as a function of obsessive-compulsive
symptoms. Neuropsychologia 47 (8–9), 1978–1987.
Hajcak, G., Franklin, M.E., Foa, E.B., Simons, R.F., 2008. Increased error-related brain
activity in pediatric obsessive-compulsive disorder before and after treatment.
American Journal of Psychiatry 165 (1), 116–123.
Hajcak, G., Moser, J.S., Yeung, N., Simons, R.F., 2005. On the ERN and the significance
of errors. Psychophysiology 42 (2), 151–160.
T. Endrass et al./Biological Psychology 84 (2010) 257–263
Hajcak, G., Simons, R.F., 2002. Error-related brain activity in obsessive-compulsive
undergraduates. Psychiatry Research 110 (1), 63–72.
Holroyd, C.B., Coles, M.G., 2002. The neural basis of human error processing:
reinforcement learning, dopamine, and the error-related negativity. Psycholog-
ical Review 109 (4), 679–709.
Johannes, S., Wieringa, B.M., Nager, W., Rada, D., Dengler, R., Emrich, H.M., et al.,
2001. Discrepant target detection and action monitoring in obsessive-compul-
sive disorder. Psychiatry Research 108 (2), 101–110.
Klein, T.A., Endrass, T., Kathmann, N., Neumann, J., von Cramon, D.Y., Ullsperger, M.,
2007. Neural correlates of error awareness. Neuroimage 34 (4), 1774–1781.
Kopp, B., Rist, F.,Mattler, U., 1996. N200 in theflanker taskas a neurobehavioral tool
for investigating executive control. Psychophysiology 33 (3), 282–294.
Maltby, N., Tolin, D.F., Worhunsky, P., O’Keefe, T.M., Kiehl, K.A., 2005. Dysfunctional
action monitoring hyperactivates frontal-striatal circuits in obsessive-compul-
sive disorder: an event-related fMRI study. Neuroimage 24 (2), 495–503.
Nieuwenhuis, S., Nielen, M.M., Mol, N., Hajcak, G., Veltman, D.J., 2005. Performance
monitoring in obsessive-compulsive disorder. Psychiatry Research 134 (2),
Nieuwenhuis, S., Ridderinkhof, K.R., Blow, J., Band, G.P.H., Kok, A., 2001. Error-
related brain potentials are differentially related to awareness of response
errors: evidence from an antisaccade task. Psychophysiology 38 (5), 752–760.
O’Connell, R.G., Dockree, P.M., Bellgrove, M.A., Kelly, S.P., Hester, R., Garavan, H.,
et al., 2007. The role of cingulate cortex in the detection of errors with and
without awareness: a high-density electrical mapping study. European Journal
of Neuroscience 25 (8), 2571–2579.
Overbeek, T.J.M., Nieuwenhuis,S., Ridderinkhof, K.R., 2005. Dissociable components
of error processing—on the functional significance of the Pe vis-a-vis the ERN/
Ne. Journal of Psychophysiology 19 (4), 319–329.
Pitman, R.K., 1987. A cybernetic model of obsessive-compulsive psychopathology.
Comprehensive Psychiatry 28, 334–343.
Ridderinkhof, K.R., Ullsperger, M., Crone, E.A., Nieuwenhuis, S., 2004. The role of the
medial frontal cortex in cognitive control. Science 306 (5695), 443–447.
Ruchsow, M., Gron, G., Reuter, K., Spitzer, M., Hermle, L., Kiefer, M., 2005. Error-
related brain activity in patients with obsessive compulsive disorder and in
healthy controls. Journal of Psychophysiology 19 (4), 298–304.
Ruchsow, M., Herrnberger, B., Beschoner, P., Gron, G., Spitzer, M., Kiefer, M., 2006.
Error processing in major depressive disorder: evidence from event-related
potentials. Journal of Psychiatric Research 40 (1), 37–46.
Ruchsow, M., Herrnberger, B., Wiesend, C., Gron, G., Spitzer, M., Kiefer, M., 2004. The
effect of erroneous responses on response monitoring in patients with major
depressive disorder: a study with event-related potentials. Psychophysiology
41 (6), 833–840.
Santesso, D.L., Segalowitz, S.J., Schmidt, L.A., 2006. Error-related electrocortical
responses are enhanced in children with obsessive-compulsive behaviors.
Developmental Neuropsychology 29 (3), 431–445.
Schmidt, K.-H., Metzler, P., 1992. Wortschatztest (WST). Beltz, Weinheim.
Schrijvers, D., De Bruijn, E.R., Maas, Y.J., Vancoillie, P., Hulstijn, W., Sabbe, B.G., 2009.
Action monitoring and depressive symptom reduction in major depressive
disorder. International Journal of Psychophysiology 71 (3), 218–224.
Tucker, D.M., Luu, P., Frishkoff, G., Quiring, J., Poulsen, C., 2003. Frontolimbic
response to negative feedback in clinical depression. Journal of Abnormal
Psychology 112 (4), 667–678.
Ursu, S., Stenger, V.A., Shear, M.K., Jones, M.R., Carter, C.S., 2003. Overactive action
monitoring in obsessive-compulsive disorder: evidence from functional mag-
netic resonance imaging. Psychological Science 14 (4), 347–353.
DSM-IV. Hogrefe, Go ¨ttingen.
Yeung, N., Botvinick, M.M., Cohen, J.D., 2004. The neural basis of error detection:
conflict monitoring and the error-related negativity. Psychological Review 111
T. Endrass et al./Biological Psychology 84 (2010) 257–263