O bsessive-compulsive disorder (OCD) is a psychological disorder characterized by involuntary, recurrent, obsessive thoughts (e.g., fear of hurting somebody) and/or a repetitive, ritualized behavior (e.g., washing, checking, hoarding, etc.). In several studies, OCD was associated with structural aberrations in the orbitofrontal cortex (OFC), the anterior cingulate cortex (ACC), and the basal ganglia, especially the nucleus caudatus (NC). 1 – 3 Magnetic resonance spectroscopic and imaging findings support these sites as essential for the development and perpetuation of OCD. 4 – 10 In a recent meta-analysis, Whiteside, Port, and Abramowitz 11 analyzed the results of functional imaging studies in OCD using positron emission tomography (PET) and single photon emission computed tomography (SPECT) and found significant effects for the orbital gyrus and the head of the caudate nucleus. Functional imaging studies using MRI are also in line with these findings. 6, 7, 10 These results support the neuropathological model of OCD by Baxter, 12 modified by Saxena et al., 13 which suggests a dysfunctional fronto-striatal loop as the neurobiological correlate of OCD. Although OCD cannot be characterized by a distinctive neuropsychological profile, several impairments have been found which might be connected to the cerebral origin of the disorder. Disturbances in visuospatial processing and memory seem to be the most prominent deficit. Impairments in memory are observed in relation to inefficient verbal organization strategies during encoding. 14, 15 Slower information processing and executive dysfunctions are found less consistently. 16 One reason for these controversial findings might be that most of the neuropsychological tasks cover several cognitive functions and cannot be attributed to a circumscribed brain region. According to the model proposed by Saxena et al., 13 deficits should be found in neurocognitive functions affected by the fronto-striatal loop, a cerebral system not routinely assessed by standard neuropsychological tests. The search for an adequate paradigm could be facilitated using functional imaging techniques. Thus, tasks leading to a fronto-striatal activation in functional imaging studies of healthy comparison subjects could be applied to assess the cerebral pathology of OCD. A study by Cools et al. 17 has used a reversal learning task in healthy comparison subjects to investigate the relearning of stimulus-reward associations and the processing of negative feedback. Concomitant with the last reversal error (the indicator for relearning), they found an activation of the ventrolateral prefrontal cortex and the ventral striatum, two areas implicated in the neuropathology of OCD. In the present study the authors investigated whether the reversal learning task, developed by Cools et al., 17 could be used as a neuropsychiatric measurement of the ventrostriatal dysfunction in OCD. Based on the model by Baxter 12 and Saxena et al., 13 the authors hypothesized that patients with OCD should be impaired concerning different aspects of this task, especially regarding the numbers and reaction times of the reversal errors.
METHOD
Sample
Twenty inpatients diagnosed with OCD according to DSM-IV criteria, a score of greater than or equal to 22 in the Yale-Brown Obsessive Compulsive Scale (Y-BOCS), 18 and an illness duration of at least 1 year were included in this study. Exclusion criteria were defined as follows: major depression, acute psychosis, epilepsy, left-handedness, drug abuse or dependency, cerebral injury, or other serious neurological or medical problems. The age range was between 18 and 47 years with a mean of 29.7 years. Twenty healthy comparison subjects were matched individually according to age, sex, and school education as well as for intelligence as estimated by a verbal IQ test (Mehrfachwahl-wortschatztest, MWT-B). 19 The authors included only inpatients to ensure that patients met their inclusion and exclusion criteria, which especially pertains to the exclusion of the previously defined psychiatric comorbidities. Since the authors mainly treat inpatients at the Psychiatric Hospital of Freiburg, the inclusion of inpatients also enabled them to recruit the sample in a short period of time. Patients were characterized by the following compulsions and obsessions: seven patients presented with washing compulsions, one with checking compulsions, five patients had predominantly obsessive thoughts, mainly aggressive or with a sexual content, and seven presented with mixed OCD symptoms. Of the patients participating in this study, seven were medication-free, 12 were treated with selective serotonin reuptake inhibitors, and two were treated with tricyclic antidepressant drugs. To make sure that antidepressive medication did not affect the reversal learning task performance, the authors compared patients with OCD on a regimen of medication to patients with OCD who were medication free. The protocol was approved by the Ethical Committee of the Albert-Ludwigs-University Freiburg. Informed written consent was obtained from each subject prior to the study.
Instruments
Screening included the following clinician ratings: Structured Clinical Interviews for DSM-IV Axis I Disorders-Clinician Version (SCID-I), 20 the Yale-Brown Obsessive Compulsive Scale, 18 Global Assessment Scale (GAS), 21 Clinical Global Impression Scale (CGI), 22 and Hamilton Depression Rating Scale (HAM-D). 23 Patients had to fill in different self-rating scales, including the Obsessive Compulsive Inventory (OCI-R), 24 the Beck Depression Inventory (BDI), 25 and the Patient’s Global Impression Scale (PGI). The Patient’s Global Impression scale is similar to the Clinical Global Impression scale. It is a seven point self-rating scale in which patients rate themselves from “very much better” (score=1) to “very much worse” (score=7). Demographic data are summarized in Table 1 .
TABLE 1. Demographics of the OCD Patients and the Healthy Comparison Subjects
Reversal Learning Paradigm
The reversal learning task was administered in a computerized version. Two different objects (square and triangle) were presented on a computer screen. Subjects had to respond to one of these objects by using either a left or a right button-press depending on whether their chosen object was on the left or right side of the screen. After their response, feedback in the shape of either a green smiling face or a red sad face appeared, indicating whether their response was correct or incorrect. After 10 to 15 (randomized) correct responses, the strategy changed and subjects had to adapt their reactions and respond to the formerly wrong stimulus. To distract subjects, probabilistic errors were interspersed, indicating a wrong choice despite a correct response. In 20% of all cases, two consecutive probabilistic errors appeared. A visual explanation of the reversal learning task is given in Figure 1 . If a subject changed his or her strategy after a probabilistic error, this was counted as a mistake (SCAPE=strategy change after a probabilistic error). Subjects were asked to both avoid mistakes and respond as fast as possible. Subjects’ reactions were classified according to the number of correct responses, strategy changes after a probabilistic error, reversal errors, and other errors. The last reversal error indicated the moment when a subject changed his or her strategy. Furthermore, reaction times of each reaction parameter were determined. Three blocks with 10 discrimination phases each were presented. Each discrimination phase contained between 0 and 4 probabilistic errors. Objects appeared for 2 seconds in which subjects had to respond. Feedback was presented for 0.5 seconds, followed by a fixation cross. The inter-stimulus interval was 3.3 seconds ( Figure 1 ).
FIGURE 1. The Reversal Learning Task
A square and a triangle are presented on a computer screen. A subject must respond to one of these objects by pressing either the left or the right button depending on whether his or her chosen object is on the left or right side of the screen. After his or her response, the screen gives feedback in the shape of either a green smiling face or a red sad face, indicating whether the reaction was correct or incorrect. After 10 to 15 correct responses, the strategy changes and the subject must adapt his or her reactions and respond to the previously wrong stimulus. To distract subjects, probabilistic errors are interspersed, indicating a wrong choice despite a correct response.
Statistical Analysis
Group comparisons were conducted using Kruskal-Wallis and Mann-Whitney U tests. The following parameters of the reversal learning task were analyzed: number of reversal errors and strategy changes after a probabilistic error, as well as reaction times of hits, strategy changes after a probabilistic error, reversal errors preceding the last reversal error, and last reversal errors. Correlation analyses to assess the impact of psychopathology on the behavioral parameters of the reversal learning task were conducted using Spearman’s rank correlation. Significance levels for all analyses were two-tailed and set at p≤0.05.
RESULTS
Group Comparisons: OCD Patients versus Healthy Comparison Subjects
Patients with OCD did not show any differences concerning the number of strategy changes after a probabilistic error and reversal errors compared to healthy comparison subjects. There were also no differences in the reaction times of hits, strategy changes after a probabilistic error, reversal errors preceding the last reversal error and last reversal errors. Means, standard deviations, and z and p values are shown in Table 2 .
TABLE 2. Different Responses and Reaction Times for OCD Patients and Healthy Comparison Subjects
Correlations
Spearman rank correlation analyses for the patients with OCD between the different indicators of symptom severity (Yale-Brown Obsessive Compulsive scale score for obsessions, Yale-Brown score for compulsions, and Yale-Brown summary score, and the Obsessive Compulsive Inventory score) and the parameters of the reversal learning task revealed significant positive correlations between reaction times of hits, strategy changes after a probabilistic error, and last reversal errors on the one hand and the Yale-Brown Obsessive Compulsive scale score for compulsions on the other hand. The results of the correlation analysis are shown in Table 3 .
TABLE 3. Spearman Rank Correlation Coefficients (ρ) Between Y-BOCS, OCI and the Different Responses and Reaction Times
There were no significant correlations between Global Assessment Scale, Clinical Global Impression Scale, Hamilton Depression Rating Scale, or intelligence scores and any behavioral parameters of the reversal learning task.
To further analyze the impact of compulsion severity, patients with OCD were divided by median split concerning compulsion severity. Comparisons of the two patient groups and the healthy comparison subjects revealed a significant difference in reaction times of the last reversal errors (chi-square=5.94, df=2, p=0.05). Furthermore, patients with low compulsion severity showed significantly faster reaction times concerning hits (z=−2.0, p=0.04), strategy changes after a probabilistic error (z=−2.2, p=0.03), and last reversal errors (z=−2.2, p=0.03), but also a higher number of reversal errors (z=−2.1, p=0.04) than patients with high compulsion severity. Patients with low compulsion severity reacted significantly faster in terms of the last reversal errors (z=−2.0, p=0.05) than healthy comparison subjects as well. There were no significant differences between patients with high compulsion severity and healthy comparison subjects. Means and standard deviations are shown in Figure 2 and Figure 3 .
FIGURE 2. Different Responses of OCD Patients On Reversal Learning Tasks
*p≤0.05
SCAPE=strategy change after probalistic error; OCD-LC =OCD Patients With Low Compulsion Severity; OCD-HC=OCD Patients With High Compulsion Severity
FIGURE 3. Reaction Times of OCD Patients On Reversal Learning Tasks
*p≤0.05
OCD-LC=OCD Patients With Low Compulsion Severity; OCD-HC=OCD Patients With High Compulsion Severity
No significant differences between patients with OCD on medication and patients off medication were found on any of the relevant reversal learning task parameters (number of strategy changes after a probabilistic error and reversal errors; reaction times of hits, strategy changes after a probabilistic error, reversal errors preceding the last reversal error, and last reversal errors). Means, standard deviations and z and p values are shown in Table 4 .
TABLE 4. Different Responses and Reaction Times of OCD Patients on Antidepressive Medication (AD) and Medication-Free OCD Patients
DISCUSSION
This study compared patients with OCD and healthy comparison subjects on a reversal learning task supposed to activate areas of the fronto-striatal loop, a possible cerebral correlate of OCD. 12, 13 The main findings of this study are prolonged reaction times of several behavioral measures of the reversal learning task with increasing severity of compulsions in the patients with OCD. These results are further corroborated by significantly faster reaction times concerning hits, strategy changes after a probabilistic error and last reversal errors of the patients with minor compulsions compared to those with severe compulsions. The positive correlation between severity of compulsions and the different reaction times demonstrates stronger response reluctance with increasing compulsion severity in OCD. Although patients respond correctly, theses reactions are delayed. Considering probabilistic errors, patients with OCD do not show more strategy changes after a probabilistic error than healthy comparison subjects, but it takes them longer to make a decision in a confusing situation. These findings are in line with the results of a study by Maltby et al., 26 who used a speeded reaction time task with high conflict trials to investigate action-monitoring processes in patients with OCD. Only correctly rejected, high-conflict trials produced excessive activation in fronto-striatal regions. According to Maltby et al., 26 these findings suggest that correctly rejected, high-conflict trials that require response inhibition might be a better model of compulsive behaviors in OCD than error trials. A recent study by Chamberlain et al. 27 also employed a reversal learning task comparing patients with OCD to patients with trichotillomania and healthy comparison subjects. As in our study, the authors did not find any differences concerning the overall number of errors made as well as the number of perseverative errors after reversal. Based on these findings they concluded an intact performance of the patients with OCD. It would be interesting to analyze additional response parameters besides the different numbers of errors and also consider correlation analyses, since in our study the authors found deficits only in association with symptom severity and in consideration of the reaction times. Interestingly, only the reaction time corresponding to the last reversal error, but not to the reversal errors preceding the last reversal error, slows down with increasing symptom severity. On the one hand this argues against a general slowdown of reactions. On the other hand it shows that flexibility and the ability to change a pattern of behavior might be impaired by severe compulsions. Impaired cognitive flexibility and set shifting abilities have been a major finding in neuropsychological as well as functional imaging studies with OCD patients, 28 – 30 thus supporting our results. Interestingly, Cools et al. 17 found an activation of the ventrolateral prefrontal cortex and the ventral striatum concomitant only with the last reversal error. Thus, our finding of a slowdown in reaction time concerning the last reversal error with increasing compulsion severity supports the disturbance of these brain areas at least in patients with distinct OCD compulsions. This interpretation is further corroborated by Remijnse et al., 31 who for the first time examined patients with OCD using reversal learning in combination with functional imaging. Investigating the specific neural response on reward and affective switching (comparable to the last reversal error in our paradigm), they found evidence for a disturbance of the orbitofrontal-striatal loop in patients with OCD. Their behavioral data cannot be directly compared to our findings since, as in the study by Chamberlain et al., 27 Remijnse et al. only assessed the number of reversal learning parameters, but did not measure reaction times. Furthermore, they did not distinguish patients according to symptom severity, but mainly included outpatients with mild to moderate symptom severity. Considering the findings by Cools et al. 17 and Remijnse et al., 31 an association between reversal learning and fronto-striatal dysfunction in OCD seems to be plausible. Nevertheless, deficits in reversal learning are not restricted to OCD, and dysfunctions in associated neurotransmitter systems need to be considered. A study by Gorrindo et al. 32 found reversal learning deficits in pediatric bipolar patients, characterized by higher error rates and a smaller likelihood of meeting the learning criterion. Furthermore, patients with attention-deficit hyperactivity disorder, patients with antisocial behavior, and pediatric patients with autism also displayed deficits in reversal learning. 33 – 35 Reversal learning deficits in these patients were mainly associated with orbitofrontal dysfunction. In patients with mild Parkinson’s disease medication status significantly influenced their performance in a reversal learning task. 36 Patients on a regimen of medication exhibited impaired reversal shifting relative to patients not taking medication, possibly mediated by an overdose of dopaminergic agents in the ventral fronto-striatal system. Thus, dopamine also seems to play a role in reversal learning. Subsequent group comparisons of patients with OCD with minor compulsions to those with severe compulsions and to healthy comparison subjects further emphasize the effect of symptom severity. Differences were found between patients with low compulsion severity and patients with high compulsion severity concerning various reaction times, again including the last reversal error, with the patients with low compulsion severity being faster than the patients with high compulsion severity. Patients with low compulsion severity were also faster in terms of the last reversal errors than healthy comparison subjects. This implies that patients with OCD do not represent a uniform patient group. On the contrary, deficits in fronto-striatal brain areas might only lead to detectable cognitive impairments at a high level of pathology. Interestingly, patients with high compulsion severity made fewer reversal errors than patients with low compulsion severity. As known from a study by Frost and Steketee, 37 patients with OCD have significantly elevated scores on measures of perfectionism, especially the subscales “concern over mistakes” and “doubts about actions.” To prevent mistakes, the more severely disturbed OCD patients might have responded more carefully, resulting in significantly delayed reaction times, but also less mistakes. Reversal learning consists of different cognitive domains and could be considered a kind of alternation learning. So far, few studies have examined alternation learning in OCD, primarily by using the Delayed Alternation Task (DAT) or the Object Alternation Task (OAT). Findings are equivocal. Whereas some studies have found impairments in alternation learning in OCD patients, 38 – 41 the authors 42 and others 43 could not replicate these findings. As the authors have pointed out, these discrepancies might be due to confounding factors such as interpersonal or social cognitive variables or differences between the Object Alternation Task offline and PC version. There may be different reasons for the fact that our findings are restricted to the severity of compulsions. On the one hand, dysfunction of the fronto-striatal system might be more pronounced in patients with predominantly compulsive symptomatology. There is a need for imaging studies examining cerebral correlates of different classes of symptoms. On the other hand, many of the patients reporting compulsive symptoms suffered from washing compulsions. Hence, the authors cannot exclude the possibility that performance in those cases was disturbed by preoccupation with fear of contamination when completing the task. The authors did not find any correlations between symptom severity and the number of SCAPEs or reversal errors. These results suggest that prolonged reaction times serve as a compensating mechanism for deficits of cognitive flexibility. Whereas others have suggested comorbidity as a confounding variable, possibly blurring group differences in alternation learning, 44 the authors did not find support for this hypothesis. Neither depressive symptoms nor general functioning of the OCD patients influenced their performance on the reversal learning task.
This study has some limitations. Since OCD is supposed to be mediated by a general fronto-striatal dysfunction, the authors intended to include patients of all OCD symptom dimensions. Nevertheless, this heterogeneity could have blurred some effects. As the study by Mataix-Cols and colleagues 45 pointed out, different subgroups of OCD seem to be associated with impairments in different brain networks. Future studies should include a higher number of patients to allow for statistical subgroup analyses concerning different symptom clusters (obsessions versus compulsions, but also different types of obsessions and compulsions) as well as concerning the severity of symptoms. More than one third of our patients were unmedicated; the others were mainly treated with selective serotonin reuptake inhibitors (SSRIs). To exclude an influence of medication on reversal learning, the authors compared the performance of medicated versus unmedicated patients with OCD. In accordance with the finding that SSRIs improve rather than impair behavioral performance, with the exception of long-term memory, 46 the authors could not find any behavioral differences between medicated and unmedicated patients with OCD on the relevant reversal learning task parameters. These findings argue against an influence of medication. Future studies should use functional neuroimaging techniques to determine neural correlates of cognitive functioning. Furthermore, not only symptom severity and subtype, but also possible gender differences, need to be considered, since some studies suggest an influence of gender on neuropsychological performance and clinical characteristics.
In summary, our findings indicate a direct neuropsychological correlate of compulsions resulting in a general slowdown of decision making. On a neural level fronto-limbic impairments seem to subserve this deficit. In support of the proposed neuropathological model the authors found a prolongation in reaction times in OCD patients with increasing severity of compulsions. More generally, the authors suggest the development of neuropsychological assessments in psychiatric populations on the basis of functional neuroimaging findings in healthy comparison subjects.
Footnote
Received August 21, 2006; revised March 19, 2007; accepted April 2, 2007. Dr. Valerius is affiliated with the Department of Psychosomatic Medicine and Psychotherapy at the Central Institute of Mental Health in Mannheim, Germany; Drs. Lumpp, Kuelz, Freyer, and Voderholzer are affiliated with the Department of Psychiatry at the University of Freiburg, Germany. Address correspondence to Gabriele Valerius, Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, J5, D-68159 Mannheim, Germany.
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