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The somatic marker affectingdecisional processes in obsessive-compulsive disorderPaolo Cavedini a , Claudia Zorzi a , Clementina Baraldi a , SaraPatrini a , Giuliana Salomoni a , Laura Bellodi b , Rafael C.Freire c & Giampaolo Perna aa Department of Clinical Neurosciences, Villa San BenedettoHospital, Hermanas Hospitalarias, Albese con Cassano, Italyb Department of Clinical Neurosciences, San Raffaele ScientificInstitute & Vita-Salute San Raffaele University, School ofPsychology, Milan, Italyc Laboratory of Panic and Respiration, Institute of Psychiatry,Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

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To cite this article: Paolo Cavedini, Claudia Zorzi, Clementina Baraldi, Sara Patrini, GiulianaSalomoni, Laura Bellodi, Rafael C. Freire & Giampaolo Perna (2011): The somatic markeraffecting decisional processes in obsessive-compulsive disorder, Cognitive Neuropsychiatry,DOI:10.1080/13546805.2011.614152

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The somatic marker affecting decisional processes in

obsessive-compulsive disorder

Paolo Cavedini1, Claudia Zorzi1, Clementina Baraldi1,Sara Patrini1, Giuliana Salomoni1, Laura Bellodi2,Rafael C. Freire3, and Giampaolo Perna1

1Department of Clinical Neurosciences, Villa San Benedetto Hospital,

Hermanas Hospitalarias, Albese con Cassano, Italy2Department of Clinical Neurosciences, San Raffaele Scientific

Institute & Vita-Salute San Raffaele University, School of Psychology,

Milan, Italy3Laboratory of Panic and Respiration, Institute of Psychiatry, Federal

University of Rio de Janeiro, Rio de Janeiro, Brazil

Introduction. Patients with obsessive-compulsive disorder (OCD) demonstrateimpairment in decisional processes in which both cognition and emotion play acrucial role.Methods. We investigated the connection between decision-making performancesand choice-related skin conductance responses (SCRs), to identify a somaticmarker impairment affecting decisional processes in these patients. We exploredSCRs during the Iowa Gambling Task in 20 OCD and 18 control, measuringanticipatory and posticipatory psychophysiological reactions according to cardchoices and to the outcomes of each selection.Results. Most patients exhibited weaker SCRs compared to HC, although thereweren’t substantial differences in magnitude between the two groups. In contrastwith HC, patients with OCD showed no significant differences of SCRs activationaccording to card selections; they chose cards from neither favourable norunfavourable decks.Conclusions. The main finding of the study were the evidence of a dysfunctionalbiological marker in OCD subjects, affecting decision-making process. Dysfunc-tional patterns of SCRs could partially explain OCDs’ impairment in this ability.Decision-making deficits in OCDs could be influenced in part by the lack ofsomatic differences in discriminating between advantageous and disadvantageousbehaviour. These findings could lead to a more complete understanding of OCD.

Correspondence should be addressed to Paolo Cavedini, Department of Clinical

Neuroscience, Villa San Benedetto Hospital, Via Roma, 16-22032 Albese con Cassano, Italy.

Email: p.cavedini@paolocavedini.com

COGNITIVE NEUROPSYCHIATRY

2011, 1�14, iFirst

# 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

http://www.psypress.com/cogneuropsychiatry http://dx.doi.org/10.1080/13546805.2011.614152

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Keywords: Decision making; Obsessive-compulsive disorder; Skin conductance

response; Somatic marker.

INTRODUCTION

Many studies demonstrated impairment in executive functions in obsessive-

compulsive disorder (OCD; Olley, Malhi, & Sachev, 2007). Although

memory functioning may be affected in OCDs, these deficits appear

secondary to an executive failure of organisational strategies during

encoding (Kim, Park, Shin, & Kwon, 2002). On tasks of set shifting,

functioning OCD patients showed increased response latencies, persevera-

tion of responses, and difficulties utilising feedback to adapt to change

(Aycicegi, Dinn, Harris, & Erkmen, 2003). Data in literature also

suggest deficit in planning and problem-solving functions in these patients

(Cavallaro et al., 2003). Recent studies on OCD and related spectrum

disorders (i.e., anorexia nervosa and pathological gambling) highlighted an

impairment in decision-making tasks, suggesting that these patients were

guided by short-term rewards in spite of possible negative consequences that

may occur in the future (Cavedini, Bassi, Ubbiali, et al., 2004; Cavedini,

Riboldi, Keller, D’Annucci, & Bellodi, 2002). With the increasing interest in

the neurobiology of decision making, many researchers suggest that

considering OCD as a disorder of decision making will lead to new research

approaches and novel strategies for drug and behavioural treatments

(Cavedini, Gorini, & Bellodi, 2006).

It is well known that according to the Somatic Marker Hypothesis

(Damasio, 1994), a somatic marker guides human behaviour towards

advantageous decisions. In particular, in decision-making processes, the

activation of a somatic state previously paired with complex stimuli from

the environment, engages preferential signals that mark the different possible

options with different values, thus guiding the subject towards the correct

decision. Thus, this somatic marker curtails the decision-making process,

which would otherwise depend on a slow and demanding cost�benefit

analysis of the various possible choices that could override processing skills

and not allow for a quick and appropriate decision. Data from neuropsy-

chology and neuroimaging studies have shown that the ability to make

advantageous real-life decisions involving choices between actions leading to

uncertain outcomes and the ability to calibrate between reward and

punishment depends upon the integrity of the ventromedial prefrontal

cortex and its interconnected circuits, including the basal ganglia, thalamus,

and amygdala (Bechara, Damasio, Tranel, & Anderson, 1998; Bechara &

Martin, 2004; Bechara, Tranel, & Damasio, 2000; Chamberlain, Blackwell,

Fineberg, Robbins, & Sahakian, 2005; van den Heuvel et al., 2005).

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Moreover, previous research on neurologic patients with lesions in the

ventromedial prefrontal cortex has linked decision-making deficits to the

somatic state of these subjects (Bechara, Damasio, Damasio, & Lee, 1999;

Bechara & Martin, 2004) showing that a severe impairment in the somatic

marker was responsible for decision-making deficits. Risk taking in decision-making tests, such as the Iowa Gambling Task (IGT; Bechara, Damasio,

Damasio, & Anderson, 1994) has been accompanied by a reduced ability to

generate skin conductance responses (SCR) prior to choosing a card from

high-risk decks or in response to punishment (Bechara, Tranel, & Damasio,

2002; Suzuki, Hirota, Takasawa, & Shigemasu, 2003), thus supporting the

hypothesis that automatic signals provide useful information to guide

decision making. More recently, an association between impaired decision-

making ability and a decreased autonomic response was also found inpsychiatric patients (Tchanturia et al., 2007).

A recent study investigated the performance and the SCR in OCD

patients and healthy controls during two cognitive tasks, investigating risk

and ambiguous decisions (Starcke, Tuschen-Caffier, Markowitsch, & Brand,

2009). In the first one (Game of Dice Task*GDT; Brand et al., 2004), there

were no differences in the performance of OCD and healthy subjects; in the

second one (IGT), OCD patients performed poorly, compared to healthy

subjects. In the GDT there were no significant differences in the SCRbetween the two groups, whereas in the IGT the normal controls had higher

SCR compared to OCD patients (Starcke et al., 2009). Consequently, it is

reasonable to hypothesise the existence of a relationship between decision-

making impairment in OCD patients and their somatic state at the moment

of ambiguous decisions (i.e., skin conductance responses), since the brain

structures involved in decision making are also involved in the pathogenesis

of OCD (Mataix-Cols et al., 2004).

The aim of this study was to investigate if the somatic marker is impairedin OCD patients and if it affects the decisional processes in a cognitive task

such as IGT. Specifically, we hypothesise deficits in decision making function

in OCDs compared to healthy controls, confirming data from previous OCD

studies (Cavedini, Riboldi, D’Annucci, et al., 2002); then we expect that

these deficits could be in part explained by different patterns of SCRs

activation in the samples.

METHODS

Sample

The sample consisted of 38 subjects divided into 20 patients with OCD

(13 males, seven females, mean age 36.05911.05 years) and 18 healthy

control subjects (HC) (13 males, five females, mean age 2794.73 years). Two

THE SOMATIC MARKER IN OCD 3

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subjects recruited for the HC group were excluded for technical problems

during SCR recording.

Patients with OCD were recruited consecutively among those referred to

the Centre for Obsessive-Compulsive Spectrum Disorders at the Department

of Clinical Neuroscience, San Raffaele Hospital, Milan. The HC group wasrecruited among the administrative and worker staff of the Hospital and by

local advertisements for college students. The inclusion criteria in the patient

group was the diagnosis of OCD according to the DSM IV-TR (American

Psychiatric Association, 2000) without other lifetime Axis I diagnosis. HC

who met DSM-IV criteria for any lifetime psychiatric diagnosis were not

included in this study. In addition, subjects with history of substance abuse/

dependency or neurological diseases such as intellectual impairment,

dementia or brain injury were not included also. OCD patients were drugfree for at least 1 month.

This study was approved by an appropriate ethical committee and was

carried out in accordance with ethical principles for the medical community

regarding human experimentation, reported in the latest version of the

Declaration of Helsinki. All subjects provided written informed consent to

the study after the nature of the procedures were accurately explained.

Clinical assessment

Consensus diagnoses were obtained by two senior psychiatrists who

independently assessed the subjects by clinical interview and the MINI

International Neuropsychiatry Interview�Plus (Sheehan et al., 1998). To

evaluate OCD symptoms severity, the Yale-Brown Obsessive-Compulsive

Scale (Y-BOCS; Goodman et al., 1989) was administered.

Neuropsychological assessment

OCD patients and HC were assessed with the Iowa Gambling Task (IGT)

administered by a trained psychologist in a single session. All participants

completed the test without any cooperation or weariness problems. In the

IGT the subject must make 100 card selections from four decks (‘‘A’’, ‘‘B’’,

‘‘C’’, and ‘‘D’’) and the objective is the maximum profit. At the beginning ofthe test the subjects receive a loan of play-money. After turning over each

card, subjects are either given money or asked to pay a penalty according to

a programmed schedule of reward and punishment. Gains and losses are

different for each deck. Decks A and B (‘‘disadvantageous’’ decks) are high

paying but disadvantageous in the long run, because the penalties are even

higher. Decks C and D (‘‘advantageous’’ decks), on the other hand, are low

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paying but advantageous because the penalties are lower, resulting in an

overall gain in the long run.

Neurophysiologic data recording

The participants performed the IGT computerised version, sitting in front

of a computer screen in a quiet and comfortable room. During the test,

subjects had to push a button on a four-button platform in order to choose

a card while their SCRs were registered continuously by two electrodes

attached to the tenar and hypotenar areas on their palms of nondominant

hand. Every time the subject selected a card by clicking a button, a mark

appeared in the wave of SCRs, so that was possible to identify the specific

card picked up from a specific deck and the associated SCRs generated

before and after the selection. We extrapolated from the SCR polygram the

following situations:

. Anticipatory SCRs, characterised by a time window of 5 s before the

selection of each card. In the analysis this SCRs were divided intoadvantageous and disadvantageous SCRs according to card selections

from C and D decks and A and B decks, respectively.

. Posticipatory SCRs, characterised by a time window of 5 s after the card

selection and also divided into advantageous and disadvantageous

SCRs with the same criterion.

. Reward SCRs and punishment SCRs were also subdivided, as char-

acterised by a time window of 5 s after selecting a card giving only a

reward (without penalty) and after selecting a card with a gain followedby a loss.

The intertrial interval was set in 10 s, so that was impossible for the

subject to choose a new card during the refractory period. The data was

collected with a MP150WS system (BIOPAC System) and then analysed by

software able to quantify the SCRs’ variations with mathematical transfor-

mations (AcqKnowledge III). The first step in data analysis was the

calculation of the ‘‘difference’’, a mathematical transformation necessary

to eliminate the down drift in the SCR wave. This function works out the

difference in amplitude of two sample points separated by 100 samples. The

second step is represented by the measurement of the ‘‘area under the curve’’

of the temporal window. This measurement is similar to an integral, except

for the baseline that in this case is drawn between the endpoints of the

selected area. The unit of measurement of the ‘‘area under the curve’’ is

expressed by ms/s.

THE SOMATIC MARKER IN OCD 5

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Statistical analysis

Due to the nonnormal distribution of variables, nonparametric tests were

also used to analyse the data.

Data from the IGT performance was examined first by comparing the

differences between the total number of advantageous cards minus the total

number of disadvantageous cards selected (net score) by the two groups

(HC vs. OCD) and, second, by analysing the net score in successive blocks of

20 cards each (Bechara, Damasio, Damasio, & Lee, 1999).

One-way analysis of variance (ANOVA) was used to compare age and

education differences between HC and OCD, and the Chi-square test was

used to investigate differences in gender between the two groups.

The Mann�Whitney U-Test was used to compare the intergroup

difference in the amplitude of anticipatory and posticipatory SCRs, before

and after advantageous and disadvantageous decks, between OCD and HC.

The same analysis was used to compare the intergroup difference in the

amplitude of posticipatory SCRs after the choice from decks yielding a

reward (win) or a reward followed by a punishment (win plus loss) between

OCD and HC.

Finally, the Spearman Test was used to find potential correlations

between age and IGT performance between groups.

RESULTS

Decision-making performance

Decision-making performance showed that the net score (total number of

advantageous cards minus the total number of disadvantageous cards

selected) was significantly higher for the HC (�28.55929.16) group than

for OCD (�12.6920.24) patients, Z� �3.88, p�.0001. Means and

standard deviations of card selection in successive blocks of 20 are presented

in Table 1.

TABLE 1IGT performance (total number of advantageous minus disadvantageous cards

selected) in OCD and HC during the five consecutive stages of the task

Stages OCD (M9SD) HC (M9SD) p-level Z

Block 1�20 �1,797.6 �6.196.3 .122 �1544

Block 21�40 �2.197.1 4.89�9.3 .038 2073

Block 41�60 �1.398.9 8.699.4 .006 2711

Block 61�80 �3.299.1 1098.3 .0001 3826

Block 81�100 �1.8910.5 11.497.7 .0001 3733

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A significantly different pattern of choices between the two groups was

found from the second block on, with increasing significant differences

between OCD and HC in decision-making strategy during the task.

SCRs analysis

Anticipatory SCRs. Means and standard deviations for anticipatory

SCRs in advantageous and disadvantageous cards selection between OCD

and HC are presented in Table 2. Analyses revealed no difference in the

amplitude of anticipatory SCRs before advantageous, Z�0.248, p�.803,

and disadvantageous, Z� �0.13, p�.895, decks between OCD and HC.

On the other hand, the amplitude of the SCRs was significantly higher

before choosing from disadvantageous decks than from advantageous decks

in the HC group, Z�2.351, p�.018. This difference was not found in the

OCD group, Z�1.502, p�.132. Results are presented in Figure 1.

Posticipatory SCRs. Means and standard deviations for posticipatory

SCRs in advantageous and disadvantageous cards selection between OCD

and HC are presented in Table 2. The HC group and the OCD group did not

significantly differ in the amplitude of activation after advantageous,

Z�0.263, p�.792, and disadvantageous decks, Z�0.628, p�.529. In the

HC group, a significantly higher activation was found after choosing from

disadvantageous than from advantageous decks, Z�3.337, p�.0001. These

differences were not found in the OCD group, where activation after

advantageous, compared with activation after disadvantageous decks, was

not significantly different, Z�1.017, p�.309. Results are presented in

Figure 2.

TABLE 2Means and standard deviations for anticipatory and posticipatory SCRs in

advantageous and disadvantageous cards selection: Comparison between OCDand HC

OCD HC

Adv. decks

(M9SD)

Disadv. decks

(M9SD)

Adv. decks

(M9SD)

Disadv. decks

(M9SD)

Anticipatory

SCRs

0.29090.117 0.30690.114 0.28190.112 0.30490.123

Posticipatory

SCRs

0.27490.112 0.27890.114 0.28790.119 0.30690.123

THE SOMATIC MARKER IN OCD 7

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Reward and punishment. HC subjects patients show differences in levels

of activation (magnitude of the SCRs) related to receiving rewards or

rewards followed by punishments, Z�2.911, p�.003, but this was not

evident in OCD patients, Z�0.579, p�.563.

Demographics and effect on performance

In OCD patients age at onset was 18.799.3 years, and OCD mean

Y-BOCS total score was 28.395.3. As regard to demographic character-

istics between HC and OCD, we found a significant difference in age,

Z� �3.055, p�.002, but not in years of education (p�.391) and sex

(p�.63). Although there was a significant difference in age between OCD

patients and HC, age was unrelated to IGT performance, T� �0.495,

p�.624

OCDHCGroups

0,20

0,22

0,24

0,26

0,28

0,30

0,32

0,34

0,36

0,38

SC

Rs

(µs/

sec)

Disadv. decks Adv. decks

Figure 1. Anticipatory SCRs in OCD and HC for advantageous and disadvantageous card selection

(error bars represent 5% error).

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DISCUSSION

The main finding of the study was the evidence of a dysfunctional biological

marker in OCD subjects, affecting the decision-making process. Dysfunc-

tional patterns of SCRs could partially explain OCDs impairment in this

ability. In fact, decision-making deficits in OCDs could be influenced in part

by the lack of somatic differences in discriminating between advantageous

and disadvantageous behaviour. In contrast with HC, in fact, OCDs showed

no significant difference of SCRs activation in discriminating advantageous

and disadvantageous behaviours during a decision-making task.

Given the involvement of orbitofrontal cortex functioning in the

pathogenesis of OCD, patients affected by this disorder showed impairment

in decisional processes, as confirmed by many research data (Cavedini, Bassi,

Zorzi, & Bellodi, 2004; Cavedini, Gorini, & Bellodi, 2006; Cavedini, Zorzi,

et al., 2006). Deficit in decision-making function is considered an endophe-

notype marker of OCD, differently from other anxiety disorders (Cavedini,

Riboldi, D’Annucci, et al., 2002).

OCDHC

Groups

0,20

0,22

0,24

0,26

0,28

0,30

0,32

0,34

0,36

0,38

SC

Rs

(µs/

sec)

Disadv. decks Adv. decks

Figure 2. Posticipatory SCRs in OCD and HC for advantageous and disadvantageous card selection

(error bars represent 5% error).

THE SOMATIC MARKER IN OCD 9

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Then, clinical observation also suggests the presence of decision-making

deficit in OCDs, as well evidenced, for example, in pathological doubting.

Compulsive behaviour can be seen as an alternative way of managing reward

and punishment; these patients in fact seem to prefer short-term rewards

such as compulsions or avoiding behaviours (that momentarily reduce

anxiety and the persistence of obsessions), in spite of actual punishment (i.e.,

increasing of anxiety state caused by obsessions). These pathological

behaviours cause negative consequences in the long run, increasing OCD

symptoms and worsening quality of life.

The IGT, like many real-life situations, represents a complex decisional

situation where a choice must be made in the face of uncertainty and variable

outcomes. A complete and reliable analysis of the various options and of

their consequences would be complicated and effortful; thus, these patients

may tend to make a choice offering immediate and high rewards. In the

context of decision making, the activation of a somatic state that was

previously paired with environmental stimuli engages preferential signals

that mark the different options with different values and thus guides the

subject towards the correct decision. In the current study, patients appeared

to be compromised in decision making, failing to develop any strategy in

their IGT card selection. These data confirmed results of previous studies,

investigating decision making impairment in OCD and in other spectrum

disorders (Cavedini, Bassi, Zorzi, & Bellodi, 2004; Cavedini, Gorini, &

Bellodi, 2006; Cavedini, Zorzi, et al., 2006; Starcke et al., 2009). From a

therapeutic point of view, it is well known that the IGT has been shown to be

sensitive to biological as well as to cognitive aspects of decisional processes

in obsessive-compulsive spectrum disorders. In fact, previous studies have

stressed the role of decision-making functioning in predicting both

antiobsessive treatment outcome with serotonin reuptake inhibitors in

patients with OCD (Cavedini, Bassi, Zorzi, & Bellodi, 2004), and a cognitive

behavioural approach in patients with anorexia nervosa (Cavedini, Zorzi,

et al., 2006).

Starcke’s work evidenced significant differences in SCR activations during

IGT between OCD and HC groups, with a higher activation in the second

one (Starcke et al., 2009). More specifically, in our study, analysing SCR

activation during the decision-making process, an association between

defective decision making and a pattern of both anticipatory- and

posticipatory-reduced SCRs reactivity was demonstrated. However, results

from the intergroup comparison on the amplitude of the somatic activation

reveal that there are no substantial differences in magnitude between HC and

OCD patients, independent of the strategy used or test performance. In

particular, analysis of the anticipatory SCRs revealed a differentiated rate of

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activation according to card selection in the HC, with greater activation

before they chose cards from a disadvantageous deck and weaker activation

before they chose from an advantageous one. OCD patients’ activation

instead did not change significantly whether they choose a card from the

favourable or unfavourable decks. Regarding posticipatory SCRs, our

findings are consistent with previous research in finding a relation between

SCRs and the affective value of stimuli (Bechara et al., 1999; Suzuki et al.,

2003). In the HC group, galvanic response is more elevated after a selection

from a disadvantageous deck and a win, whereas OCD subjects showed no

modulation in their posticipatory responses.

The lack of suitable somatic responses deprives OCD patients of a

mechanism of bypassing a cognitive analysis and guiding them towards

appropriate choices. Without this mechanism, they have more difficulty in

recognising a convenient strategy, and probably they perform the task

answering to short-term contingencies and consequently they fail more often

than healthy controls.

It should be noted that results from this study demonstrate differences

between OCD and HC. Thus, we cannot exclude impaired SCRs not also

being typical for other anxiety disorders, caused by an overall higher level of

anxiety. Anyway, given the present study results, some interesting considera-

tions should be made about clinical and treatment implications for OCD.

The lack of any somatic differences in discriminating between advantageous

versus disadvantageous behaviour as observed in experimental conditions

could help to provide an understanding of pathological behaviour exhibited

by OCD patients. Specifically, a lack of behavioural flexibility (continuous

repetition of the same noxious behaviour), search for an immediate reward

(relief of anxiety from compulsions), and blindness to negative future

consequences (compromised life quality), that are characteristic traits of this

disorder, may be effects of the somatic marker dysfunction in OCD patients.

It’s well known that many studies have conceptualised OCD as a complex

disorder; OCD heterogeneity is evidenced in clinical manifestations,

neurobiological functioning, and different treatment outcomes (de Mathis

et al., 2006; Mataix-Cols, Rosario-Campos, & Leckman, 2005). Moreover,

even if OCD studies highlighted an impairment in decision-making tasks

(Cavallaro et al., 2003; Cavedini, Riboldi, Keller, et al., 2002), a behavioural

heterogeneity was evidenced; a considerable portion of OCD patients in fact

performs decision making in the same way as normal subjects do. Recent

research showed how this heterogeneity divides subjects into different

populations in terms of symptom dimensions (Lawrence et al., 2006) or

treatment response (Cavedini, Bassi, Zorzi, & Bellodi, 2004; Cavedini, Zorzi,

et al., 2006), with bad treatment outcome when decision-making impairment

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is present. Further, the presence of heterogeneous pathogenic mechanisms in

OCD (de Mathis et al., 2006; Mataix-Cols et al., 2005) calls for closer

examination of cognitive and emotional functioning, with research into

decision making as a possible first step. Then, OCD heterogeneity must be

considered for a better understanding of our results, given neurophysiolo-

gical dysfunction in the somatic marker as specific trait of an OCD

subgroup, showing dysfunctional behavioural patterns.

The main limitations of this study were the relatively small sample size

and the nonpaired recruitment of subjects. The age did not interfere in the

IGT scores and probably the differences between the two groups had a small

effect in the current study. Another limit of the work was the lack of state

depression and anxiety measures in evaluating clinical variables of the

samples.

The present study indicated that OCD patients (or an OCD subgroup)

may have a dysfunctional biological marker, and accordingly have an

impaired performance in cognitive tasks. The cause of the biological marker

dysfunction, as well as the determinant of the heterogeneity in OCD patients,

is still unclear and more research is needed in this field.

Manuscript received 28 October 2010

Revised manuscript received 31 May 2011

First published online 13 October 2011

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