Understanding Obsessive-Compulsive Disorder in Students: Symptoms and School-Based Interventions

C 2006) Neuropsychology Review, Vol. 16, No. 1, March 2006 (
DOI: 10.1007/s11065-006-9001-y Understanding Obsessive–Compulsive Disorder: Focus on Decision Making Paolo Cavedini,1,3 Alessandra Gorini,1,2 and Laura Bellodi1 Published online: 18 May 2006 Current approaches to obsessive-compulsive disorder (OCD) have suggested that neurobiological abnormalities play a crucial role in the etiology and course of this psychiatric illness. In particular, a fronto-subcortical circuit, including the orbitofrontal cortex, basal ganglia and thalamus appears to be involved in the expression of OCD symptoms. Neuropsychological studies have also shown that patients with OCD show deficits in cognitive abilities that are strictly linked to the functioning of the frontal lobe and its related fronto-subcortical structures, such as executive functioning deficits and insufficient cognitive-behavioral flexibility. This article focuses on decision making, an executive ability that plays a crucial role in many real-life situations, whereby individuals choose between pursuing strategies of action that involve only immediate reward and others based on long-term reward. Although the role of decision-making deficits in the evolution of OCD requires further research, the collected findings have significant implications for understanding the clinical and behavioral heterogeneity that characterizes individuals with OCD. KEY WORDS: decision-making; executive functions; gambling task; obsessive–compulsive disorder; reward. Obsessive–compulsive disorder (OCD) is characterized by the presence of recurrent unwanted thoughts (obsessions) that increase subjects’ anxiety, often accompanied by persistent and distressing ritualized acts (compulsions) that decrease the anxiety (American Psychiatric Association, 2000). These symptoms represent a severe disabling condition and significantly interfere with the patient’s daily life. The importance of better understanding psychological and neural mechanisms involved in this disorder is justified by the fact that, at present, OCD is the fourth most common psychiatric disorder (El-Sayegh et al., 2003) and is considered one of the most disabling medical conditions (Murray and Lopez, 1996), with a progressively increasing need for effective intervention strategies. Current approaches to OCD suggest that neurobiological abnormalities play a crucial role in its etiology and course and provide biological models based on direct and indirect investigations of the possible brain circuits involved in the expression of obsessive–compulsive symptoms. In particular, both direct observations, usually performed via neuroimaging techniques (Baxter et al., 1987; Kim et al., 2001; Perani et al., 1995; Swedo et al., 1989;), and indirect observations from a variety of neuropsychological studies (see Greisberg and McKay, 2003 for a review), provide growing evidence for involvement of a fronto-subcortical circuit, including orbitofrontal cortex (OFC), basal ganglia, and thalamus, in the expression of OCD. From a neuropsychological aspect, the integrity of this orbitofrontal–striatal–thalamic–orbitofrontal loop is believed to be specifically related to the cognitive functions termed executive, which are the higher-level mental processes that modulate sensory, motor, cognitive, memory, and affective abilities (Chamberlain et al., 2005). Through executive functions we plan future actions, 1 San Raffaele Scientific Institute, Department of Neuropsychiatric Sciences, Universitá Vita-Salute San Raffaele, Faculty of Psychology, Milan, Italy. 2 Maastricht University, Department of Psychiatry and Neuropsychology, Maastricht, The Netherlands. 3 To whom correspondence should be addressed at San Raffaele Hospital Scientific Institute, Department of Neuropsychiatric Sciences, Universitá Vita-Salute San Raffaele, Faculty of Psychology, 20, Via Stamira D’Aneona 20127, Milan, Italy; e-mail: cavedini.paolo@hsr.it. 3 C 2006 Springer Science+Business Media, Inc. 1040-7308/06/0300-0003/0
4 monitor our behavior, and alter it in response to specific feedback and changes in environmental contingencies. Thus, executive functions depend on the intact functioning of many of the more fundamental cognitive operations, such as memory and attention. A relevant cognitive skill linked to the executive functions is decision-making, the ability to process environmental information in order to make advantageous decisions. Studies on neurological patients (Bechara et al., 1996; Damasio, 1994) have shown that the ability to make helpful real-life decisions, involving choices between actions leading to uncertain outcomes and the ability to calibrate between rewards and punishments, depends on the integrity of the orbitofrontal cortex and its interconnected circuits, which are some of the same structures assumed to be involved in the pathogenesis of OCD. This article presents a critical review of the available data on the neuropsychological aspects of decisionmaking in OCD, as well as subjects’ perceptions of reward and punishment. Analysis of this cognitive ability could help us to better understand OCD behavior, dissecting the observed clinical and behavioral heterogeneity in the many ways in which this disorder is expressed. We also discuss the decision-making deficit in relation to anatomical correlates and emphasize the use of neurocognitive criteria for subtyping OCD, which can serve as a guide for development of more specific, and potentially more successful, behavioral and pharmacological interventions. AN OVERVIEW OF NEUROBIOLOGICAL MODELS OF OBSESSIVE–COMPULSIVE DISORDER In the last few decades, many investigators have contributed to the hypothesis that OCD involves dysfunctions in a neuronal loop extending from the orbitofrontal cortex and cingulate gyrus to the striatum (caudate nucleus and putamen), globus pallidus, thalamus, and back to the frontal cortex (Saxena et al., 1998; Szeszko et al., 2004) (Fig. 1). Neuroimaging studies have shown that in OCD patients activity within this cortico–basal ganglia network is increased at rest (Machlin et al., 1991; Swedo et al., 1989), accentuated during provocation of symptoms (Hollander et al., 1995; Mataix-Cols et al., 2004; Rauch et al., 1994), and attenuated after successful treatment (Baxter et al., 1992; Rubin et al., 1995; Saxena et al., 1999). Both empirical and theoretical studies have shown that the orbitofrontal cortex (OFC), posited to lie within the basal ganglia-cortico-thalamic circuit, is strictly implicated in the pathophysiology of OCD. This theory is P. Cavedini, A. Gorini, and L. Bellodi Fig. 1. Orbitofrontal striato–thalamo–orbitofrontal loop involved in the pathogenesis of OCD: there are two antagonistic pathways through which the striatum influences the globus pallidus internus/substantia nigra (GPi/SNr) output nuclei. The most well studied of these is the direct striatal-GPi/SNr pathway that inhibits the GPi/SNr output nuclei, and thus causes a disinhibition of the thalamus. This direct striatalGPi/SNr pathway is counterbalanced by an indirect pathway from the striatum to the GPi and SNr that acts to oppose the disinhibition of the thalamus. By maintaining a balance between the direct and indirect pathways, the basal ganglia regulates the excitability of the thalamus and determines what information should be passed to the cortical processing areas. supported by neurophysiological (Bannon et al., 2002; Di Russo et al., 2000; Leocani et al., 2001), neuroradiological (Jenike et al., 1996; Kim et al., 2001; Scarone et al., 1992; Stein et al., 1993), and metabolic (Baxter et al., 1987; Benkelfat et al., 1990; Perani et al., 1995) studies that have reported a relationship between OCD and brain circuits that are posited to connect the frontal cortex to basal ganglia structures in the physiological model proposed by Alexander (1986). From a biochemical aspect, it has been observed that the serotonin and the dopamine systems could be especially important in mediation of OCD symptoms (Denys et al., 2004; Pogarell et al., 2003; Simpson et al., 2003). In fact, while standardized treatments with selective serotonin reuptake inhibitors in OCD are associated with significant reductions in OFC metabolism, the administration of dopamine agonists leads to stereotypic behavior and exacerbates OCD symptoms. Finally, clinical and behavioral researchers have shown that typical clinical features of OCD are present in both humans and nonhumans with lesions in the frontal lobes and basal ganglia (Pitman, 1982; Rapoport and Wise, 1988). Contribution of Neuropsychology to Understanding OCD Specific neuropsychological tests have confirmed the role of the fronto–cortico–subcortical circuit in OCD. For Decision-Making in Obsessive–Compulsive Disorder example, the Tower of Hanoi, the Wisconsin Card Sorting Test, and the Object Alternation Test, have been used to investigate the functioning of different brain areas on the basis of localizatory hypothesis. In particular, OCD patients show a significantly poor performance in the Tower of Hanoi task, which seems to be sensitive to frontostriatal circuits and basal ganglia damage (Cavedini et al., 2001; Mataix-Cols et al., 1999) and in the Object Alternation Test, which is sensitive to a malfunctioning of the OFC (Abbruzzese et al., 1995a; Cavedini et al., 1998; GrossIsseroff et al., 1996). Although the findings are contradictory (Lacerda et al., 2003), the prevailing empirical evidence appears to support the notion that OCD patients show normal performance on the Wisconsin Card Sorting Test, that is specifically related to the correct functioning of the dorsolateral prefrontal cortex, which is not directly implicated in OCD (Abbruzzese et al., 1995b; Cavallaro et al., 2003). Neuroimaging and neuropsychology are complementary disciplines that provide powerful means for assessing the structure and function of cortico-striatal circuits. Two studies (Kwon et al., 2003; Lacerda et al., 2003) combined neuropsychological functioning of OCD patients with their brain structural abnormalities and metabolic activity. Correlations between volumetric abnormalities and metabolic rates, and neuropsychological performance were found in the prefrontal cortex and subcortical structures (globus pallidus, anterior cingulate gyrus, and putamen) only in the OCD group. Impaired activation of basal ganglia was also found by Fernandez and colleagues (Fernandez et al., 2003) who evaluated changes in cerebral blood flow in OCD and control subjects during the Tower of Hanoi test. This study supports the supposed modification of the activating systems of basal ganglia functions in OCD compared with normal subjects. Using the same test, van den Heuvel et al. (2005) showed a decreased frontal-striatal responsiveness during planning in OCD patients. These findings support the hypothesis that decreased prefrontal-striatal responsiveness is associated with impaired planning ability in OCD patients. Since the described frontal-striatal dysfunction in OCD is independent from state anxiety and disease symptom severity, they concluded that executive impairment is a core feature in OCD. THE ORBITOFRONTAL CORTEX AND REWARD PERCEPTION When a malfunctioning of the OFC occurs, subjects show specific deficits in the perception of reward and lose the ability to make advantageous decisions in many 5 real-life situations, even if their other cognitive functions appear intact. Studies on animals (Mora and Cobo, 1990; Mora et al., 1979; Nakano et al., 1984; Phillips et al., 1979;) and humans (Tataranni et al., 1999) have shown that OFC and the ventromedial prefrontal regions are implicated in different aspects of reward mechanisms, and now it seems clear that one of the functions of the OFC is the association between reward and behavior (Rolls, 2000). It has also been observed that OFC cells fire in response to any kind of stimulus whenever the stimulus is presented as a reinforcer. The OFC reward-related processes work with far greater sensitivity than other structures of frontal cortex (i.e., the ventral striatum) do and are responsible for coding “satiety,” which consists of a reduction in the motivational value of stimuli after prolonged exposure. Failure of this process leads to prolonged exposure to reinforcers. Perception of Reward in Obsessive–Compulsive Patients Clinical observations of OCD patients reveal some pathological behaviors strictly connected to unadaptive perception of reward. For example, while in a nonpathological condition the normal desire to wash the hands after touching a dirty object disappears after the hands are washed, compulsive washers never perceive “satiety” and continue to feel forced to wash themselves humans (Phillips et al., 2000). At the same time, acting on compulsions (negative reinforcement), they obtain a temporary relief of anxiety (reward) but never feel “full”. Through similar mechanisms, other patients use avoidance behaviours to avoid contact with anxiety-provoking stimuli and situations. Again, avoidance produces a decrease of subjective anxiety, becoming a sort of reward (Fig. 2). In this perspective, compulsive behaviors and obsessive thoughts often appear to completely disrupt planning of real-life strategies. A life quality compromised, despite a normal cognitive functioning and normal abilities in problem solving tasks, associates OCD patients with neurological patients with lesions to the OFC who develop a severe impairment in real-life decision-making. The extensive literature on ventromedial patients shows that they often pursue actions that bring some reward in the immediate future, in spite of severe long-term negative consequences such as the loss of job, home, and family. These patients show deficits in executive functions and insufficient flexibility in cognitive–behavioral aspects, which make them oblivious to the future 6 P. Cavedini, A. Gorini, and L. Bellodi Fig. 2. The OCD behavioral loop. The appearance of obsessions causes an increase of anxiety that would spontaneously decrease in time and can be compared to a short-term penalty. The pathways of behavior that OCD patients follow can be avoidance or acting on compulsions. Both give an immediate reward in terms of anxiety decrease, but greatly impair the patient’s daily life, representing a long-term penalty. Moreover, compulsions reinforce obsessive thoughts, perpetuating the obsessive–compulsive mechanism and representing a long-term penalty. consequences of their actions (Bechara et al., 1994, 1996, 2000). They pay attention only to their immediate reward and seem to be unable to modulate their next decisions at the light of previous errors. In other words, despite normal intellect, ventromedial patients show abnormalities in decision-making together with abnormalities in emotion and feeling. Similarities with OCD behavior are clear: lack of behavioral flexibility (continuous repetition of the same behavior), search for an immediate reward (relief of anxiety from compulsions), and blindness to negative future consequences (compromised life-quality) are also characteristic traits of OCD patients. A NEUROPSYCHOLOGICAL APPROACH TO THE STUDY OF DECISION MAKING Different neuropsychological tests have been proposed for laboratory investigations of functional and anatomical substrates of decision making. They have been theoretically distinguished on the basis of how they operationalize the processes involved in decision making (Bechara et al., 1999). Perhaps some of them are based on the concept of delay, and others on the notion of risk. Delay-based tasks require subjects to choose between small, immediate rewards or larger, delayed rewards and the optimal choice is to choose delayed rewards. Otherwise, risk-based tasks contain elements of uncertainty, and in order to succeed participants must adopt a preference for small but certain rewards over larger, uncertain rewards. These latter tasks are classified as probabilistic or risk-taking tasks. The Gambling Task Here, we consider only the risk-based tasks and, in particular, we will focus our attention on the very well known Gambling Task (GT), a card game that detects and measures decision-making impairment, testing the subject’s ability to balance immediate rewards against longterm negative consequences. This test was initially developed by Damasio et al. (Bechara et al., 1994) to assess the “myopia for the future” in ventromedial patients because, as in real life, the task offers them choices that may be risky, without any obvious explanation of how, when, or what to choose. In other words, the task resembles realworld contingencies in which we are frequently exposed to ambiguous situations that do not permit an exact calculation of future outcomes and in which choices must often be based on approximations and guesses. In particular, the task assesses the ability of subjects to acquire a preference through rewards and punishments as represented by gains and losses of play money. Briefly stated, the GT requires 100 card selections from four decks of cards identical in appearance; subjects are asked to maximize their profit starting from a $2000 loan of play money. To attain this goal they must find the most advantageous decks and persistently pick up cards from those decks. After turning over some cards, subjects are both given money and sometimes asked to Decision-Making in Obsessive–Compulsive Disorder pay a penalty according to a pre-programmed schedule of reward and punishment. Gains and losses are different for each card selected from the four decks: decks A and B are “disadvantageous,” as, though they pay $100, the penalty amounts are higher, so they cost more in the long run; decks C and D are “advantageous” because they pay only $50, but the penalty amounts are lower resulting in an overall gain in the long run. In summary, decks A and B are equivalent in terms of overall net loss over the trials, as are decks C and D; the difference is that in decks A and C the penalty is more frequent, but of smaller magnitude, while in decks B and D the penalty is less frequent but of larger magnitude. Several studies suggest that the performance at the GT evaluates the decision-making function mediated by a ventromedial prefrontal cortex (Bechara et al., 1998; Grant et al., 2000). In fact, only patients with damage to the ventromedial, but not to the dorsolateral or dorsomedial sectors of the prefrontal cortex, persist in drawing cards from the high payout/high penalty decks despite the ultimately punishing consequences of this behavior. DECISION-MAKING DEFICIT IN PSYCHIATRIC CONDITIONS The experimental strategies used to study decision making in neurological patients provide parallels and direct implications for understanding the neurobiological mechanisms of several neuropsychiatric disorders (Table 1). In fact, using the GT, many studies have demonstrated similar decision-making impairments in cocaine, opiate, and alcohol abusers (Bechara et al., 2001a; Grant et al., 2000; Rogers et al., 1999), who have shown abnormalities in the ventromedial prefrontal cortex during functional neuroimaging studies (Hommer et al., 1997; Volkow et al., 1991). Following the line of research that suggests a possible link between addictive and compulsive behavior (Volkow and Fowler, 2000) and the previously discussed evidence of an important involvement of the brain circuits connecting the frontal cortex to basal ganglia structures in the pathophysiology of OCD, the GT has also been proposed as a good tool to assess decisionmaking impairment in OCD. Study of Decision Making in OCD Starting from these considerations, Cavedini et al. (2002a) investigated decision-making abilities in OCD compared to panic disorder patients and healthy control 7 subjects. OCD and panic groups were compared to examine whether the expected poor performance in the GT was unique to OCD or whether it was also present in other related anxiety disorders, although there are notable clinical and cognitive differences between these two pathologies. As expected, the results showed different decisionmaking performance between OCD and panic patients. In fact, the OCD subjects showed a significant preference for the disadvantageous decks, while panic and control subjects made significantly more selections from the advantageous decks, avoiding the bad decks. Analysis of the 100 card selections demonstrated that control subjects and patients with panic disorder started from random choices and gradually shifted their preferences toward the “good” decks during the test. By contrast, OCD patients failed to operate this shift in card selection: they rapidly shifted their preferences toward the “bad” decks, encouraged only by the prospect of immediate gain. Analysis of strategies adopted by OCD patients from the beginning to the end of the test suggested that during the 100 selections, all subjects understood the differences that characterize the four decks but, while control subjects and panic patients increased the number of advantageous choices, OCD patients deliberately increased the number of disadvantageous selections (Fig. 3). OCD patients appeared to be encouraged greatly by the prospect of immediate reward, being less sensitive to the future consequence of their choices. Another study (Cavallaro et al., 2003) used the GT to confirm the hypothesis of a double dissociation between different frontal lobe dysfunction in schizophrenic versus OCD patients. They found, as expected, that OCD individuals performed significantly worse at the GT than schizophrenic patients, confirming a specific involvement of the ventromedial cortex in OCD (Saxena et al., 1998) not present in the latter, in which the principal compromised part of the frontal lobe is the dorsolateral prefrontal cortex. Similar results were obtained by Wilder et al. (1998) who did not find any difference in GT performance between schizophrenic patients and controls. Is Decision-Making Impairment in OCD a Trait Condition or an Anxiety-Induced Characteristic? The decision-making impairment observed in OCD patients seems to be a trait condition instead of an anxietyinduced characteristic. To confirm this hypothesis, Cavedini et al. (2000) compared the decision-making performance in OCD and depressed patients, who report some degree of mental ruminations similar to thoughts or 8 P. Cavedini, A. Gorini, and L. Bellodi Table 1. The Gambling Task in Decision-Making Studies: A Review in Psychiatric Disorders Authors Wilder et al. Year Samples 1998 12 schizophrenic (SCZ) Bechara et al. 30 healthy control (HC) 2000 30 drug abusers (DA) 24 healthy control (HC) 2001a 41 substance dependent (SD) Clark et al. 5 ventromedial lesion (VM) 40 healthy control (HC) 2001 15 manic Grant et al. Performance at the Gambling Task SCZ = HC SCZ = HC at California Verbal Learning Test, Letter Number Span, Wisconsin Card Sorting Test DA < HC DA = HC at Wisconsin Card Sorting Test SD = VM SD = VM = HC at Wais-III, Benton Visual Retention Test and Rey Auditory Verbal Learning Test SD = VM at Stroop and Tower of Hanoi SD < VM and HC at Wisconsin Card Sorting Test Manic = HC at Tower of London, Spatial Working Memory, Intradimensional/extradimensional attentional shift and Stroop Color Tests Manic < HC at Rapid visual information processing tasks and Word Test IED < HC at Facial Emotion Recognition Test and Odor Identification Test IED = HC at Working Memory Tests PG = HC at Weigl’s Sorting Test and Wisconsin Card Sorting Test SD < HC Manic = HC 30 healthy control (HC) Best et al. Cavedini et al. 2002 24 intermittent explosive IED < HC disorder (IED) 22 healthy control (HC) 2002 20 pathological gamblers (PG) PG < HC Mitchell et al. 40 healthy control (HC) 2002 20 psychopathic (Psyc) Psyc < HC 20 healthy control (HC) Nielen et al. Cavallaro et al. Bechara and Martin Ritter et al. Cavedini et al. 2002 27 obsessive–compulsive disorder (OCD) 26 healthy control (HC) 2003 110 schizophrenic (SCZ) 67 obsessive-compulsive disorder (OCD) 56 healthy control (HC) 2004 substance dependence (SD) healthy control (HC) 2004 20 schizophrenic (SCZ) 15 healthy control (HC) 2004 59 anorexic (AN) Performance at Other Neuropsychological Tests Psyc = HC at Raven’ s Advanced Progressive Matrices and Intradimensional/extradimensional shift task (attentional set-shifting) Psyc < HC Intradimensional/extradimensional shift task (response reversal) OCD = HC OCD < HC OCD < SCZ SCZ < OCD and HC at Wisconsin Card Sorting Test SCZ and OCD < HC at Torre di Hanoi SD < HC SD < HC at Delayed nonmatching to sample task SKZ < HC SKZ = HC (poor performace) at Wisconsin Card Sorting Test AN < HC AN = HC at Wisconsin Card Sorting Test, Weigl’s Sorting Test and Object Alternation Test 82 healthy control (HC) Source: NLM-PubMed. mental compulsions that characterize OCD. Both samples were tested using the GT and compared with a control group. Both OCD and depressed patients appeared to be compromised in decision-making abilities when compared with the control group, but a deeper analysis showed some important differences between the two groups. In fact, considering their neuropsychological performances and the severity of symptoms, analysis of covariance showed a significant effect of symptom severity on the number of disadvantageous cards selected in affective patients, but not in OCD. The conclusions were that, although poor performance seems to be a specific trait of OCD unrelated to the severity of illness, the decision-making profile of depressed patients correlates with severity of depressive symptoms and may be considered a state instead of a trait. Opposite results has been achieved in OCD in a preliminary study by Nielen et al. (2002), who did not find any difference between decision-making performance of 27 OCD patients and a group of healthy volunteers. They found that the ability to adjust choices was independently associated with both anxiety and OCD severity, suggesting a relationship between symptoms and risk adjustment: Decision-Making in Obsessive–Compulsive Disorder Fig. 3. Strategy of Gambling Task performance of control subjects versus OCD patients, calculated as total number of “advantageous” minus “disadvantageous” cards selected in each block of 20 cards. (Modified from Cavedini et al., Neuropsychologia, 40 (2002) 205–211). patients with high OCD severity tended to take more risks than patients with moderate OCD. A reasonable explanation for this was that individuals with high trait anxiety are more reactive to punishment, leading to increased expectancies of punishment (Zinbarg and Mohlman, 1998). Decision-Making Impairments in the Obsessive–Compulsive Spectrum The GT has also been used to assess neuropsychological similarities between OCD and other psychiatric disorders belonging to the so-called “obsessive-compulsive spectrum” (Hollander, 1998). In an early study, Cavedini et al. (2002b) tested the GT in a sample of pathological gamblers, finding that their performance was very similar to that of OCD patients. In fact, they deliberately chose disadvantageous decks to obtain an immediate reward, careless about the long-term negative effects of their choices, such as disruptive behavior in gambling and daily life. Even if limited data are available about the validity of the diagnosis of pathological gambling and about the etiology of this disorder, these neuropsychological findings support the hypothesis that pathological gambling belongs to the OCD spectrum, lying at the impulsive extreme on the compulsive–impulsive dimension. In a second study, the GT was administered to a sample of patients with anorexia nervosa (Cavedini et al., 2004) and showed that the supposed impairment in decision making did not appear to be related to some measure of illness severity or to gender and age, suggesting the absence of any relationship between nutritional 9 status, severity of symptoms, and general cognitive impairment in these subjects. However, differently to from OCD, anorexic patients chose cards randomly, showing a lack of strategy that could be an expression of their inability to maximize immediate reward or to program a postponed reward. The psychopathological and behavioral consequences of their decision-making deficiency could be found in the pathological eating behavior that patients with anorexia nervosa exhibit. In fact, to obtain an immediate reward, consisting in the relief of anxiety elicited by food phobia, and to neutralize the fear of gaining weight, they chose to avoid taking in calories, ignoring long-term negative consequences of their choices characterized by the progressive and severe inevitable decline of their physical condition. A review of the literature on neuropsychological deficits in eating disorders and the relationship between cognitive deficits and psychosocial development has proposed a significant association between the presence of neuropsychological deficits and the development of these disorders (Lena et al., 2004). Further research is necessary to assess the role of executive functions, in general, and decision making, in particular, in the etiology of eating disorders. Even if preliminary, these neuropsychological studies support the hypothesis that these disorders belong to the OCD spectrum, and could be helpful in the construction of a common neurofunctional model, in spite of a different phenomenological description of these disorders. NEURAL CORRELATES OF THE GAMBLING TASK PERFORMANCE The data mentioned in the previous sections highlight the contribution of neuropsychology to the localizatory hypothesis. In the case of the GT, the investigation started from specific deficits consequent to circumscribed cerebral lesions (ventromedial patients) helps us to derive some anatomical inferences about patients characterized by similar cognitive impairments. The next step will be to combine the use of neuropsychological investigation and neuroimaging techniques. At present, no imaging data are available for the GT in OCD, but there are some data regarding the correlation between cerebral activation and the GT performance in other neurological and psychiatric disorders. For example, Adinoff et al. (2003) observed that in cocainedependent subjects the anterior cingulate and left dorsolateral prefrontal cortex regional cerebral blood flow at rest were significantly correlated with the performance on the GT. Similarly, Bolla et al. (2003) observed, in a positron emission tomography (PET) study, that cocaine abusers 10 showed greater activation during the GT performance in the right OFC and less activation in the right dorsolateral prefrontal cortex and left medial prefrontal cortex compared to a control group, while better GT performance was associated with greater activation in the right OFC both in cocaine abusers and in the control group. Other significant results about the contribution of the frontal cortex in decision making come from Clark et al. (2003), who showed that, in the GT, patients with right frontal lesions preferred the risky decks differing from left frontal and control subjects. Moreover, within the right frontal group, the preference for the risky decks was correlated with the total lesion volume and the volume of damage outside of the ventromedial prefrontal region. BIOLOGICAL CONSIDERATIONS OF DECISION-MAKING IMPAIRMENT IN OCD The comprehension of neurobiological model of OCD has produced important advances also in clinical and therapeutical perspectives through the studies of neurotransmitters systems involved in its etiopathogenesis and the effects of specific drugs on its symptomatology. A large amount of evidence indicates that chronic administration of amphetamine can induce enduring reductions in monoamine levels, both dopamine in the striatum and serotonin (5-hydroxytryptamine, 5-HT) in the prefrontal cortex, as long as a kind of cognitive deficit, particularly in executive functions, is demonstrated in patients with focal lesions to these neural areas (Ersche et al., 2005). Clinical evidence has also indicated that drug abusers display many of the behavioral traits that are typical of patients with frontal lobe damage (Eslinger and Damasio, 1985) and emphasize the possible role of the ascending mesostriatal and mesocortical dopamine systems and the ascending serotonin projection systems in decision-making processes. In fact, patients with Parkinson’s disease (Bowen et al., 1975; Downes et al., 1989) as well as nonhuman primates (Brozoski et al., 1979; Sawaguchi and Goldman-Rakic, 1991), show that altered dopaminergic function is associated with some of the cognitive impairments typically seen after damage to the prefrontal cortex. These impairments can be ameliorated by pharmacological agents acting on the mesostriatal and mesocortical dopamine pathways (Arnsten, 1997; Lange et al., 1992;). Consistent with these observations, subjects with a history of chronic abuse of amphetamine and cocaine will themselves display decision-making deficits similar to those present in patients with prefrontal cortex or striatal damage. P. Cavedini, A. Gorini, and L. Bellodi Concerning the involvement of the ascending 5-HT projection systems, further data come from the observation that normal subjects with a reduced central 5-HT activity after consumption of a tryptophan-depleting amino acid drink, show decision-making deficits similar to those seen after focal damage to OFC (Rogers et al., 1999). A systematic analysis of the effects of neurochemical transmitters on GT performance has been provided by Bechara and colleagues (Bechara et al., 2001b). By manipulating dopamine and serotonin receptors, they observed that the blockade of both dopamine and serotonin interfered with the selection of advantageous decks. In particular, the dopamine effect seemed restricted to the earlier part of the GT, when decisions are still guided by covert knowledge (in this phase the subject is guided by physiological activation instead of a conscious decision to act) (Damasio, 1994), while the serotonin effect influenced only the latter part of the task when decisions are mainly guided by conscious knowledge of which choices are good or bad. As clearly expressed by Bechara (2003), these results suggested that covert biasing of decision might be dopaminergic, whereas overt biasing might be serotoninergic. The implication of serotonin in the pathophysiology of OCD justifies the interest in correlating decision-making with pharmacological effects of proserotoninergic drugs, analyzing the treatment outcome and the GT performance in different subgroups of OCD patients. It was observed that after 12 weeks of treatment with a standardized pro-serotonergic medication, patients could be subdivided into “Responders” and “NonResponders” on the basis of the presence or absence of a reduction of the Y-BOCS total score greater or equal to 40% (Cavedini et al., 2002a). It was also noticed that, before the beginning of the treatment, there were important individual differences in decision-making performance within the OCD group: responders played at the GT as well as controls did, whereas the nonresponder patients showed a compromised decision-making profile. The heterogeneity in decision-making profiles of OCD could be reasonably considered as a predictive factor of response to anti-obsessive pharmacological treatments and the GT performance may be considered a valid criterion for choosing pharmacological treatment in OCD starting from the observation that anti-obsessive treatment outcome is increased to 85% of responders choosing an appropriate drug strategy according to the GT performance (Cavedini et al., 2004). Another possible valid predictor of positive response to pro-serotoninergic treatment has been found in the analysis of genetic variations of 5-HT transporter gene Decision-Making in Obsessive–Compulsive Disorder expressions. Genetical studies have found in OCD three allelic variations (ll = wild, SS = reduced expression, ls = intermediate) and, in OCD patients without a co-diagnosis for tic disorder, a significant time per genotype interaction for the Yale-Brown ObsessiveCompulsive score was found: patients with ls genotype showed a greater reduction of obsessive–compulsive symptoms severity (Di Bella et al., 2002). Additional studies are needed to assess a possible common role of these two predictive factors (performance at the GT and genotype) to better understand treatment response mechanisms in OCD (Cavedini et al., 2002c). The Somatic Marker Hypothesis As mentioned earlier, several studies have stressed the role of the OFC in reward mechanisms (Rahman et al., 1999). Studying conditioned learning processes and the ability to modify or suppress responses initially linked to reward, Rolls (2000) concluded that the OFC plays a crucial role in the association between external stimuli and internal reward mechanisms. The link between external stimuli and internal states and the possible functions of the prefrontal cortex have been assessed by the “somatic marker hypothesis” (Damasio, 1996; Damasio et al., 1991), which hypothesize that when an individual faces a decision, each alternative elicits a physiological state that corresponds to an emotional reaction. This “marker” signals act at multiple levels of operation: some occur overtly (consciously) and some occur covertly (nonconsciously). The marker signals arise in bioregulatory processes that are related to emotions and feelings but also to the physiological state structure and regulation. The somatic marker hypothesis provides an account of deficits in decision-making, positing that they are the result of defective activation of somatic markers that normally function as covert or overt signposts for helping to make advantageous choices. The somatic marker hypothesis has been repeatedly tested by Bechara et al. (1996, 2000) using measures of skin conductance responses (SCRs). They observed that during the administration of the GT, normal subjects begin to avoid the decks with high immediate gains (disadvantageous decks). They also start to produce anticipatory SCRs before their selection of a disadvantageous response. In contrast,, ventromedial patients continue to select more cards from the disadvantageous decks, failing to produce any anticipatory SCRs. The insensitivity to punishment seems to be associated with lower 11 than normal punishment SCRs, while the hypersensitivity to reward would be associated with the generation of reward SCRs with a magnitude higher that normal. The anticipatory SCR appears to be a component of a warning to subjects that they are about to make a risky choice. Starting from the “somatic marker hypothesis,” Bechara et al. (1996) showed that the absence of anticipatory skin conductance response in patients with prefrontal damage is correlated with their insensitivity to future outcomes, positive or negative, suggesting that these subjects fail to generate somatic signals that would serve as physiological markers in the distinction between advantageous and disadvantageous choices and are guided primarily by immediate prospects. Considering this evidences, the somatic state during the GT performance was also assessed in OCD (Cavedini et al., 2003). Psychophysiological parameters such as respiration effort, heart frequency, and muscle tension were recorded at rest and during the task in 10 OCD patients and 10 healthy controls. Analysis of these physiological parameters showed that all mean values were significantly higher in OCD than in healthy subjects at the rest, probably of because of anxiety that characterizes the psychopathological profile of OCD; nevertheless, data from the somatic variations recorded during the task showed that, while all physiological mean values in control subjects started from a lower level at rest and increased during the decision-making task, in OCD this modulation was absent. In a recent study (Zorzi, 2004) the authors also investigated the SCR activation in a sample of 23 OCD compared to 18 control subjects during the GT. The main finding revealed that control subjects show an increase in the SCR before and after a disadvantageous choice, while the OCD patients show a lack of SCR modulation either during the selection of advantageous or disadvantageous decks. The absence of a somatic modulatory function in OCD could be a valid explanation for their deficit in decisionmaking. Even if these are preliminary results, they encourage further investigation into the somatic marker hypothesis in OCD and, in a larger view, the modulation of emotions in this psychiatric disorder. In fact, clinical and experimental evidences suggested that the OFC, presumably through its rich interconnections with limbic cortices and other neural stations deeply implicated in processes of incentive motivation and reinforcement, represents an important contact between emotional and affective information and mechanisms of action selection. Nevertheless, clinical observation of patients with anxiety disorders also suggests the presence of heterogeneous 12 mechanisms of emotional processing, such as different patterns of avoidance behavior or ability to decondition from phobic stimuli. These considerations will address future pathways of neuropsychological and neurophysiological research in psychiatric disorders, particularly in OCD. CONCLUSIONS This article describes the state of the art concerning the neuropsychological aspects and clinical implications of decision-making in OCD. Unlike in other areas of neuropsychology, literature on decision-making in psychiatric disorders is scarce, but there are sufficient data to support the hypothesis that deeper investigations in this area could provide a better understanding of the pathophysiology of OCD and related disorders. Mental disorders are considered to arise in the brain and the new goal of “scientific psychopathology” (Andreasen, 1997) is to identify the neural mechanisms of normal cognitive processes and to understand how they are injured in mental illnesses. Besides the classical psychiatric classifications based on convergence of signs, symptoms, outcome, and patterns of familial aggregation, integration between neuropsychology, neuroanatomy, and neurobiology allows the development of sophisticated and powerful models that explain the cognitive dysfunction of psychiatric patients based on knowledge of normal brain/mind function. Use of multiple neuroscience techniques, such as neuropsychological measures in conjunction with psychophysiological and functional neuroradiological ones, indicates that the neural mechanisms of mental illness can be understood as a dysfunction in specific neural circuits and that their functions and dysfunctions can be influenced or altered by a variety of internal and external states. With regard to OCD, the combined use of different techniques has shown that the decision-making impairment is specifically related to the functioning of the ventromedial prefrontal cortex. Similarly, neuroimaging and pharmacological studies have suggested the role of serotonin and dopamine systems in the expression of OCD symptoms as well as in decision-making performance. Combined use of different lines of investigation is aimed to dissect the phenotypic heterogeneity of OCD that risks to reduce the power and to obscure the findings coming from experimental and clinical investigations and that is underestimated by most of the current models of OCD. The presence of different symptoms, from intrusive thoughts to checkers or washer rituals, the differences observed in the level of patients’ insights and P. Cavedini, A. Gorini, and L. Bellodi the different responses to anti-obsessive pharmacological treatment suggest the existence of different biological subtypes of OCD. Studies on the neuropsychology of decision-making processes and related neurophysiological substrates could be a helpful approach to characterize possible sources of homogeneity between different patterns of disease, according to the direction proposed by Mataix-Cols et al. (2004, 2005) of a multidimensional model that may extend beyond the traditional nosological boundaries of OCD and closely related phenotypes. Moreover, a deeper investigation of the role of the somatic state modulation in OCD patients during the GT could be useful in formulating a model for the role of anxiety in this disorder. The main point that remains unclear is if the anxiety that characterizes OCD is responsible for the impairment in decision-making or if the decision-making impairment is one of the traits specific for this pathology. This point could be assessed by studying in depth the role of the somatic changes during the administration of specific decision-making tests other than the gambling task. The use of different decision-making tasks, such as, for example, the gambling tasks proposed by Rogers (1999), in which subjects choose between contingencies that are presented in a readily comprehensive format, could facilitate the interpretation of how an individual patient’s pattern of choices might change across a range of welldefined and clearly presented contingencies, instead of condition in which the underlying contingencies relating actions to relevant outcomes remain hidden. It is important to realize that these types of investigations go beyond merely interesting research and are very useful for a calibration of innovative behavioral and clinical approaches that can bring relief from obsessive– compulsive symptoms. ACKNOWLEDGMENTS The authors wish to thank Clementina Baraldi, PsyD, Tommaso Bassi, MD, Monica Piccinni PsyD and Claudia Zorzi, MD, at our University, for their hard work on decision-making studies of obsessive–compulsive spectrum disorders and for their invaluable cooperation in discussing this review. REFERENCES Abbruzzese, M., Bellodi, L., Ferri, S., and Scarone, S. (1995a). Frontal lobe dysfunction in schizophrenia and obsessive-compulsive disorder: A neuropsychological study. Brain Cogn. 27(2): 202–212. Abbruzzese, M., Ferri, S., and Scarone, S. (1995b). Wisconsin Card Sorting Test performance in obsessive-compulsive disorder: no Decision-Making in Obsessive–Compulsive Disorder evidence for involvement of dorsolateral prefrontal cortex. Psychiatry Res. 58(1): 37–43. Adinoff, B., Devous, M. D., Sr., Cooper, D. B., Best, S. E., Chandler, P., Harris, T., Cervin, C. A., and Cullum, C. M. (2003). Resting regional cerebral blood flow and gambling task performance in cocaine-dependent subjects and healthy comparison subjects. Am. J. Psychiatry 160(10): 1892–1894. Alexander, G. E., DeLong, M. R., and Strick, P. L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 9: 357–381. American Psychiatric Association (2000). DSM-IV-TR. Diagnostic and Statistical Manual of Mental Disorders. (4th ed.) Text Revision APA, Washington, DC. Andreasen, N. C. (1997). Linking mind and brain in the study of mental illnesses: a project for a scientific psychopathology. Science 275(5306): 1586–1593. Arnsten, A. F. (1997). Catecholamine regulation of the prefrontal cortex. J. Psychopharmacol. 11(2): 151–162. Bannon, S., Gonsalvez, C. J., Croft, R. J., and Boyce, P. M. (2002). Response inhibition deficits in obsessive-compulsive disorder. Psychiatry Res. 110(2): 165–174. Baxter, L. R., Jr., Phelps, M. E., Mazziotta, J. C., Guze, B. H., Schwartz, J. M., and Selin, C. E. (1987). Local cerebral glucose metabolic rates in obsessive-compulsive disorder. A comparison with rates in unipolar depression and in normal controls. Arch. Gen. Psychiatry 44(3): 211–218. Baxter, L. R., Jr., Schwartz, J. M., Bergman, K. S., Szuba, M. P., Guze, B. H., Mazziotta, J. C., et al. (1992). Caudate glucose metabolic rate changes with both drug and behavior therapy for obsessivecompulsive disorder. Arch. Gen. Psychiatry 49(9): 681–689. Bechara, A. (2003). Risky business: Emotion, decision-making, and addiction. J. Gambl. Stud. 19(1): 23–51. Bechara, A., Damasio, H., and Damasio, A. R. (2001b). Manipulation of dopamine and serotonin caused differents on covert and overt decision-making. Society for Neuroscience Abstract, 27. Bechara, A., Damasio, A. R., Damasio, H., and Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50(1–3): 7–15. Bechara, A., Damasio, H., Damasio, A. R., and Lee, G. P. (1999). Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. J. Neurosci. 19(13): 5473– 5481. Bechara, A., Damasio, H., Tranel, D., and Anderson, S. W. (1998). Dissociation of working memory from decision making within the human prefrontal cortex. J. Neurosci. 18(1): 428–437. Bechara, A., Dolan, S., Denburg, N., Hindes, A., Anderson, S. W., and Nathan, P. E. (2001a). Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia 39(4): 376–389. Bechara, A., and Martin, E. M. (2004). Impaired decision making related to working memory deficits in individuals with substance addictions. Neuropsychology 18(1): 152–162. Bechara, A., Tranel, D., and Damasio, H. (2000). Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain 123(Pt 11): 2189–2202. Bechara, A., Tranel, D., Damasio, H., and Damasio, A. R. (1996). Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cereb. Cortex. 6(2): 215–225. Benkelfat, C., Nordahl, T. E., Semple, W. E., King, A. C., Murphy, D. L., and Cohen, R. M. (1990). Local cerebral glucose metabolic rates in obsessive-compulsive disorder. Patients treated with clomipramine. Arch. Gen. Psychiatry 47(9): 840–848. Best, M., Williams, J. M., and Coccaro, E. F. (2002). Evidence for a dysfunctional prefrontal circuit in patients with an impulsive aggressive disorder. Proc. Natl. Acad. Sci. USA 99(12): 8448–8453. Bolla, K. I., Eldreth, D. A., London, E. D., Kiehl, K. A., Mouratidis, M., Contoreggi, C., et al. (2003). Orbitofrontal cortex dysfunction in abstinent cocaine abusers performing a decision-making task. Neuroimage 19(3): 1085–1094. 13 Bowen, F. P., Kamienny, R. S., Burns, M. M., and Yahr, M. (1975). Parkinsonism: Effects of levodopa treatment on concept formation. Neurology 25(8): 701–704. Brozoski, T. J., Brown, R. M., Rosvold, H. E., and Goldman, P. S. (1979). Cognitive deficit caused by regional depletion of dopamine in prefrontal cortex of rhesus monkey. Science 205(4409): 929–932. Cavallaro, R., Cavedini, P., Mistretta, P., Bassi, T., Angelone, S. M., Ubbiali, A., et al. (2003). Basal-corticofrontal circuits in schizophrenia and obsessive-compulsive disorder: A controlled, double dissociation study. Biol. Psychiatry 54(4): 437–443. Cavedini, P., Bassi, T., Ubbiali, A., Casolari, A., Giordani, S., and Zorzi, C., et al. (in press). Neuropsychological investigation of decisionmaking in anorexia nervosa. Psychiatry Res 127(3): 259–266. Cavedini, P., Bassi, T., Zorzi, C., and Bellodi, L. (2004). The advantages of choosing antiobsessive therapy according to decision-making functioning. J. Clin. Psychopharmacol. 24(6): 628–631. Cavedini, P., Cisima, M., Riboldi, G., D’Annucci, A., and Bellodi, L. (2001). A neuropsychological study of dissociation in cortical and subcortical functioning in obsessive-compulsive disorder by Tower of Hanoi task. Brain Cogn. 46(3): 357–363. Cavedini, P., D’Annucci, A., Riboldi, G., Cisima, M., and Bellodi, L. (2000). Neuropsychology of obsessive-compulsive disorder: relationship to response. Paper presented at the 1st ECNP Workshop, Nizza (France). Cavedini, P., Ferri, S., Scarone, S., and Bellodi, L. (1998). Frontal lobe dysfunction in obsessive-compulsive disorder and major depression: A clinical-neuropsychological study. Psychiatry Res. 78(1-2): 21–28. Cavedini, P., Riboldi, G., D’Annucci, A., Belotti, P., Cisima, M., and Bellodi, L. (2002a). Decision-making heterogeneity in obsessivecompulsive disorder: Ventromedial prefrontal cortex function predicts different treatment outcomes. Neuropsychologia 40(2): 205– 211. Cavedini, P., Riboldi, G., Keller, R., D’Annucci, A., and Bellodi, L. (2002b). Frontal lobe dysfunction in pathological gambling patients. Biol. Psychiatry 51(4): 334–341. Cavedini, P., Zorzi, C., Giordani, S., D’Annucci, A., Bassi, T., and Di Bella, D. (2002c). The role of HT-5 carrier genotype in decisionmaking impairment of OCD patients. Am. J. Med. Genet. 114(7): 224. Cavedini, P., Zorzi, C., Ubbiali, A., Gorini, A., D’Annucci, A., Bassi, T., et al. (2003). The neurophysiology of decision-making in obsessivecompulsive disorder. Brain Cogn. 51(2): 236–237. Chamberlin, S. R., Blackwell, A. D., Fineberg, N. A., Robbins, T. W., and Sahakian, B. J. (2005). The neuropsychology of obsessive compulsive disorder: the inhibition as candidate endophenotypic markers importance of failures in cognitive and behavioural. Neurosci. Behav. Reviews 29(3): 399–419. Clark, L., Lversen, S. D., and Goodwin, G. M. (2001). A neuropsychological investigation of prefrontal cortex involvement in acute mania. Am. J. Psychiatry. 158(10): 1605–1611. Clark, L., Manes, F., Antoun, N., Sahakian, B. J., and Robbins, T. W. (2003). The contributions of lesion laterality and lesion volume to decision-making impairment following frontal lobe damage. Neuropsychologia 41(11): 1474–1483. Damasio, A. R. (1994). Descartes’ Error : Emotion, Reason, and the Human Brain, New York: G.P. Putnam’ s Sons. Damasio, A. R. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 351(1346): 1413–1420. Damasio, A. R., Tranel, D., and Damasio, H. (1991). Somatic markers and the guidance of behavior: Theory and preliminary testing. In Levin, H. S., Eisemberg, H. M., and Benton A. L. (eds.), Frontal Lobe Function and Dysfunction. Oxford University Press, New York. Denys, D., van der Wee, N., Janssen, J., De Geus, F, and Westenberg, H. G. (2004). Low level of dopaminergic D2 receptor binding in obsessive-compulsive disorder. Biol. Psychiatry 55(10): 1041–1045. Di Bella, D., Erzegovesi, S., Cavallini, M. C., and Bellodi, L. (2002). Obsessive-compulsive disorder, 5-HTTLPR polymorphism and treatment response. Pharmacogenomics J. 2(3): 176–181. 14 Di Russo, F., Zaccara, G., Ragazzoni, A., and Pallanti, S. (2000). Abnormal visual event-related potentials in obsessive-compulsive disorder without panic disorder or depression comorbidity. J. Psychiatr Res. 34(1): 75–82. Downes, J. J., Roberts, A. C., Sahakian, B. J., Evenden, J. L., Morris, R. G., and Robbins, T. W. (1989). Impaired extra-dimensional shift performance in medicated and unmedicated Parkinson’s disease: evidence for a specific attentional dysfunction. Neuropsychologia 27(1112): 1329–1343. El-Sayegh, S., Bea, S., and Agelopoulos, A. (2003). Obsessivecompulsive disorder: unearthing a hidden problem. Cleve. Clin. J. Med. 70(10): 824–825, 829–830, 832–823, passim. Ersche, K. D., Fletcher, P. C., Lewis, S. J., Clark L., Stocks-Gee G., London M., Deakin J. B., Robbins T. W., and Sahakian B. J. (2005). Abnormal frontal activations related to decision-making in current and former amphetamine and opiate dependent individuals. Psychofarmacology 180(4): 612–623. Eslinger, P. J., and Damasio, A. R. (1985). Severe disturbance of higher cognition after bilateral frontal lobe ablation: Patient EVR. Neurology 35(12): 1731–1741. Fernandez, A., Pino Alonso, M., Mataix-Cols, D., Roca, M., Vallejo, J., Puchal, R., et al. (2003). Neuroactivation of the Tower of Hanoi in patients with obsessive-compulsive disorder and healthy volunteers. Rev. Esp. Med. Nucl. 22(6): 376–385. Grant, S., Contoreggi, C., and London, E. D. (2000). Drug abusers show impaired performance in a laboratory test of decision making. Neuropsychologia 38(8): 1180–1187. Greisberg, S., and McKay, D. (2003). Neuropsychology of obsessivecompulsive disorder: A review and treatment implications. Clin. Psychol. Rev.. 23(1): 95–117. Gross-Isseroff, R., Sasson, Y., Voet, H., Hendler, T., Luca-Haimovici, K., Kandel-Sussman, H., et al. (1996). Alternation learning in obsessivecompulsive disorder. Biol. Psychiatry 39(8): 733–738. Hollander, E. (1998). Treatment of obsessive-compulsive spectrum disorders with SSRIs. Br. J. Psychiatry Suppl. (35): 7–12. Hollander, E., Prohovnik, I., and Stein, D. J. (1995). Increased cerebral blood flow during m-CPP exacerbation of obsessive-compulsive disorder. J. Neuropsychiatry Clin. Neurosci. 7(4): 485–490. Hommer, D., Andreasen, P., Rio, D., Williams, W., Ruttimann, U., Momenan, R., et al. (1997). Effects of m-chlorophenylpiperazine on regional brain glucose utilization: A positron emission tomographic comparison of alcoholic and control subjects. J. Neurosci. 17(8): 2796–2806. Jenike, M. A., Breiter, H. C., Baer, L., Kennedy, D. N., Savage, C. R., Olivares, M. J., et al. (1996). Cerebral structural abnormalities in obsessivecompulsive disorder. A quantitative morphometric magnetic resonance imaging study. Arch. Gen. Psychiatry 53(7): 625– 632. Kim, J. J., Lee, M. C., Kim, J., Kim, I. Y., Kim, S. I., Han, M., et al. (2001). Grey matter abnormalities in obsessive-compulsive disorder: Statistical parametric mapping of segmented magnetic resonance images. Br. J. Psychiatry 179: 330–334. Kuelz, A. K., Hohagen, F., and Voderholzer, U. (2004). Neuropsychological performance in obsessive-compulsive disorder: A critical review. Biol. Psychol. 65(3): 185–236. Kwon, J. S., Kim, J. J., Lee, D. W., Lee, J. S., Lee, D. S., Kim, M. S., et al. (2003). Neural correlates of clinical symptoms and cognitive dysfunctions in obsessive-compulsive disorder. Psychiatry Res. 122(1): 37–47. Lacerda, A. L., Dalgalarrondo, P., Caetano, D., Haas, G. L., Camargo, E. E., and Keshavan, M. S. (2003). Neuropsychological performance and regional cerebral blood flow in obsessive-compulsive disorder. Prog. Neuropsychopharmacol Biol. Psychiatry 27(4): 657–665. Lange, K. W., Robbins, T. W., Marsden, C. D., James, M., Owen, A. M., and Paul, G. M. (1992). L-dopa withdrawal in Parkinson’s disease selectively impairs cognitive performance in tests sensitive to frontal lobe dysfunction. Psychopharmacology (Berl) 107(2-3): 394–404. Lena, S., Fiocco, A., and Leynaar, J. (2004). The role of cognitive deficits in the development of eating disorders. Neuropsychol Rev. 14(2): 99–113. P. Cavedini, A. Gorini, and L. Bellodi Leocani, L., Locatelli, M., Bellodi, L., Fornara, C., Henin, M., Magnani, G., et al. (2001). Abnormal pattern of cortical activation associated with voluntary movement in obsessive-compulsive disorder: An EEG study. Am. J. Psychiatry 158(1): 140–142. Machlin, S. R., Harris, G. J., Pearlson, G. D., Hoehn-Saric, R., Jeffery, P., and Camargo, E. E. (1991). Elevated medial-frontal cerebral blood flow in obsessive-compulsive patients: a SPECT study. Am. J. Psychiatry 148(9): 1240–1242. Mataix-Cols, D., Junque, C., Sanchez-Turet, M., Vallejo, J., Verger, K., and Barrios, M. (1999). Neuropsychological functioning in a subclinical obsessive-compulsive sample. Biol. Psychiatry 45(7): 898–904. Mataix-Cols, D., Rosario-Campos, M. C., and Leckman, J. F. (2005). A multidimensional model of obsessive-compulsive disorder. Am. J. Psychiatry 162(2): 228–238. Mataix-Cols, D., Wooderson, S., Lawrence, N., Brammer, M. J., Speckens, A., and Phillips, M. L. (2004). Distinct neural correlates of washing, checking, and hoarding symptom dimensions in obsessivecompulsive disorder. Arch. Gen. Psychiatry 61(6): 564–576. Metz, C., and Kronman, H. (1987). Statistical significance test for the binomial ROC curves. J. Math Psychol. 22: 218–243. Mitchell, D. G., Colledge, E., Leonard, A., and Blair, R. J. (2002). Risky decisions and response reversal: is there evidence of orbitofrontal cortex dysfunction in psychopathic individuals? Neuropsychologia 40(12): 2013–2022. Mora, F., Avrith, D. B., Phillips, A. G., and Rolls, E. T. (1979). Effects of satiety on self-stimulation of the orbitofrontal cortex in the rhesus monkey. Neurosci. Lett. 13(2): 141–145. Mora, F., and Cobo, M. (1990). The neurobiological basis of prefrontal cortex self-stimulation: a review and an integrative hypothesis. Prog. Brain Res. 85: 419–431. Murray, C. J., and Lopez, A. D. (1996). Global burden of disease: a comprehensive assessment of mortality and morbidity from diseases, injuries and risk factors in 1990 and projected to 2020 (Vol. 1), WHO, Harvard. Nakano, Y., Oomura, Y., Nishino, H., Aou, S., Yamamoto, T., and Nemoto, S. (1984). Neuronal activity in the medial orbitofrontal cortex of the behaving monkey: Modulation by glucose and satiety. Brain Res. Bull. 12(4): 381–385. Nielen, M. M., Veltman, D. J., de Jong, R., Mulder, G., and den Boer, J. A. (2002). Decision making performance in obsessive compulsive disorder. J. Affect Disord. 69(1-3): 257–260. Perani, D., Colombo, C., Bressi, S., Bonfanti, A., Grassi, F., Scarone, S., et al. (1995). [18F]FDG PET study in obsessive-compulsive disorder. A clinical/metabolic correlation study after treatment. Br. J. Psychiatry 166(2): 244–250. Phillips, M. L., Marks, I. M., Senior, C., Lythgoe, D., O’Dwyer, A. M., Meehan, O., Williams, S. C., Brammer, M. J., Bullmore, E. T., and McGuire, P. K. (2000). A differential neural response in obsessivecompulsive disorder patient with washing compared checking symptoms to disgust. Psychological Medicine 30(5): 1037–1050. Phillips, A. G., Mora, F., and Rolls, E. T. (1979). Intracranial selfstimulation in orbitofrontal cortex and caudate nucleus of rhesus monkey: effects of apomorphine, pimozide, and spiroperidol. Psychopharmacology (Berl) 62(1): 79–82. Pitman, R. K. (1982). Neurological aetiology of obsessive-compulsive disorders? Am. J. Psychiatry 139(1): 139–140. Pogarell, O., Hamann, C., Popperl, G., Juckel, G., Chouker, M., Zaudig, M., et al. (2003). Elevated brain serotonin transporter availability in patients with obsessive-compulsive disorder. Biol. Psychiatry 54(12): 1406–1413. Rahman, S., Sahakian, B. J., Hodges, J. R., Rogers, R. D., and Robbins, T. W. (1999). Specific cognitive deficits in mild frontal variant frontotemporal dementia. Brain 122(Pt 8): 1469–1493. Rapoport, J. L., and Wise, S. P. (1988). Obsessive-compulsive disorder: evidence for basal ganglia dysfunction. Psychopharmacol Bull 24(3): 380–384. Rauch, S. L., Jenike, M. A., Alpert, N. M., Baer, L., Breiter, H. C., Savage, C. R., et al. (1994). Regional cerebral blood flow measured during symptom provocation in obsessive-compulsive disorder using Decision-Making in Obsessive–Compulsive Disorder oxygen 15-labeled carbon dioxide and positron emission tomography. Arch. Gen. Psychiatry 51(1): 62–70. Ritter, L. M., Meador-Woodruff, J. H., and Dalack, G. W. (2004). Neurocognitive measures of prefrontal cortical dysfunction in schizophrenia. Schizphr Res. 68(1): 65–73. Rogers, R. D., Everitt, B. J., Baldacchino, A., Blackshaw, A. J., Swainson, R., Wynne, K., et al. (1999). Dissociable deficits in the decision-making cognition of chronic amphetamine abusers, opiate abusers, patients with focal damage to prefrontal cortex, and tryptophan-depleted normal volunteers: Evidence for monoaminergic mechanisms. Neuropsychopharmacology 20(4): 322– 339. Rolls, E. T. (2000). The orbitofrontal cortex and reward. Cereb. Cortex. 10(3): 284–294. Rubin, R. T., Ananth, J., Villanueva-Meyer, J., Trajmar, P. G., and Mena, I. (1995). Regional 133-xenon cerebral blood flow and cerebral 99mTc-HMPAO uptake in patients with obsessive-compulsive disorder before and during treatment. Biol. Psychiatry 38(7): 429– 437. Sawaguchi, T., and Goldman-Rakic, P. S. (1991). D1 dopamine receptors in prefrontal cortex: Involvement in working memory. Science 251(4996): 947–950. Saxena, S., Brody, A. L., Maidment, K. M., Dunkin, J. J., Colgan, M., Alborzian, S., et al. (1999). Localized orbitofrontal and subcortical metabolic changes and predictors of response to paroxetine treatment in obsessive-compulsive disorder. Neuropsychopharmacology 21(6): 683-693. Saxena, S., Brody, A. L., Schwartz, J. M., and Baxter, L. R. (1998). Neuroimaging and frontal-subcortical circuitry in obsessive-compulsive disorder. Br. J. Psychiatry Suppl. (35): 26–37. Scarone, S., Colombo, C., Livian, S., Abbruzzese, M., Ronchi, P., Locatelli, M., et al. (1992). Increased right caudate nucleus size in obsessive-compulsive disorder: detection with magnetic resonance imaging. Psychiatry Res. 45(2): 115–121. Simpson, H. B., Lombardo, I., Slifstein, M., Huang, H. Y., Hwang, D. R., Abi-Dargham, A., et al. (2003). Serotonin transporters in obsessive-compulsive disorder: A positron emission tomography study with [(11)C]McN 5652. Biol. Psychiatry 54(12): 1414– 1421. View publication stats 15 Stein, D. J., Hollander, E., Chan, S., DeCaria, C. M., Hilal, S., Liebowitz, M. R., et al.(1993). Computed tomography and neurological soft signs in obsessive-compulsive disorder. Psychiatry Res. 50(3): 143– 150. Swedo, S. E., Schapiro, M. B., Grady, C. L., Cheslow, D. L., Leonard, H. L., Kumar, A., et al. (1989). Cerebral glucose metabolism in childhood-onset obsessive-compulsive disorder. Arch. Gen. Psychiatry 46(6): 518–523. Szeszko, P. R., McMillan, S., McMeniman, M., Chen, S., Baribault, K., Lim, K. O., Lvey, J., Rose, M., Banerjee, S. P., Bhandari, R., Moore, G. J., and Rosenberg, D. R. (2004). Brain structural abnormalities in psychotropic drugnaive pediatric patients with obsessive-compulsive disorder. Am. J. Psychiatry. 161(6): 1049–1056. Tataranni, P. A., Gautier, J. F., Chen, K., Uecker, A., Bandy, D., Salbe, A. D., et al. (1999). Neuroanatomical correlates of hunger and satiation in humans using positron emission tomography. Proc. Natl. Acad. Sci. USA 96(8): 4569–4574. van den Heuvel, O. A., Veltman, D. J., Groenewegen, H. J., Cath, D. C., van Balkom, A. J. L. M., van Hartskamp, J., et al. (2005). Frontalstriatal dysfunction during planning in obsessive-compulsive disorder. Arch. Gen. Psychiatry 62(3): 301–309. Volkow, N. D., and Fowler, J. S. (2000). Addiction, a disease of compulsion and drive: Involvement of the orbitofrontal cortex. Cereb. Cortex 10(3): 318–325. Volkow, N. D., Fowler, J. S., Wolf, A. P., Hitzemann, R., Dewey, S., Bendriem, B., et al. (1991). Changes in brain glucose metabolism in cocaine dependence and withdrawal. Am. J. Psychiatry 148(5): 621–626. Wilder, K. E., Weinberger, D. R., and Goldberg, T. E. (1998). Operant conditioning and the orbitofrontal cortex in schizophrenic patients: Unexpected evidence for intact functioning. Schizophr Res. 30(2): 169–174. Zinbarg, R. E., and Mohlman, J. (1998). Individual differences in the acquisition of affectively valenced associations. J. Pers. Soc. Psychol 74(4): 1024–1040. Zorzi, C. (2004). Neuropsychology of obsessive-compulsive disorder: Presented at “neuropsychological function in psychopathology” at The 8th Nordic Meeting in Neuropsychology, Turku, Finland, August 26–29.