Keywords: Obsessive-compulsive disorder, orbitofrontal cortex, dorsolateral prefrontal cortex, anterior cingulate cortex, subthalamic nucleus, cortico-striatal-thalamic loop, transcranial magnetic stimulation, deep brain stimulation, machine-learning, experimental psychology, metacognition RESUME Trouble obsessionnel compulsif, cortex orbitofrontal, cortex prefrontal dorsolateral, cortex cingulaire anterieur, noyau subthalamique, boucle cortico-striatothalamique, stimulation magnétique transcranienne, stimulation cérébrale profonde, machine-learning, psychologie expérimentale, metacognition

Brain mechanisms underlying obsessive-compulsive disorder: evidences from a multimodal approach

Obsessive compulsive disorder is a serious disorder, understudied and considered as the 4th cause of disability in the world by the World Health Organization. Treatments exist such as antidepressants and cognitive-behavioral psychotherapies, but a significant number of patients do not respond to these usual treatments.

Nowadays, great importance is given to personalized medicine and researchers are largely focusing their research in finding biomarkers in the field of psychiatry.

In this context, the objective of my thesis work was to identify the brain regions that may be involved in obsessive-compulsive symptomatology in order to develop precision medicine.

For this, after having carried out a synthesis of the neuroimaging data present in the literature, we looked for indirect evidences but also direct evidences with a strong biological causality in order to validate or invalidate pre-existing results.

Finally, on the strength of these discoveries, our team has developed a new paradigm of metacognition, freeing itself from the measurement of obsessive-compulsive symptoms (provocative tasks) or even cognitive functions.

This paradigm aims to go beyond the symptoms by capturing a cerebral signature in electroencephalography and the visual strategy adopted by each patient suffering from an obsessive-compulsive disorder.

INTRODUCTION

Obsessive-compulsive disorder (OCD) is characterized by recurrent intrusive thoughts, images, or urges (obsessions), or by behavioral acts (compulsions) that the individual feels driven to perform. The obsessions typically cause anxiety or distress while compulsions are often in response to the obsessions or according to rules that must be applied rigidly. Most individuals with OCD have both obsessions and compulsions.

OCD typically starts in childhood or adolescence, persists throughout a person's life, and produces substantial impairment in functioning due to the severe and chronic nature of the illness.

Epidemiology

The lifetime prevalence of OCD worldwide is estimated at 1.5 percent for women and 1.0 percent for men (1,2). Estimated lifetime prevalence among adults is slightly higher, at 2.3 percent. Females are affected at a slightly higher rate than males in adulthood, although males are more commonly affected in childhood (3,4).

OCD is comorbid with many different disorders. The presence of comorbid conditions such as depression, tic disorders, or obsessive-compulsive personality disorder are associated with a lower response rate to treatment. As mention above, psychiatric disorders that are more commonly seen in individuals with OCD than the general population include:

-Anxiety disorders. In epidemiologic samples, 76 percent of individuals have a comorbid anxiety disorder including panic disorder (13 to 56 percent), social anxiety disorder, generalized anxiety disorder (30 percent), and specific phobia (5).

-Mood disorders. In epidemiologic studies, 63 percent of individuals with OCD have a lifetime history of a mood disorder, most commonly major depressive disorder (41 percent). Bipolar disorder appears to be present in up to 22 percent of individuals with OCD.

-Obsessive-compulsive personality disorder. In clinical studies, up to 32 percent of individuals have comorbid obsessive-compulsive personality disorder.

-Tic disorders. In clinical studies, up to 29 percent of individuals with OCD have a comorbid tic disorder. This is most commonly seen in males with childhood onset of OCD.

-Body dysmorphic disorder, trichotillomania (hair pulling disorder), and excoriation (skin picking) disorder are more commonly seen in individuals with OCD than in the general population (6).

OCD appears to be more common in individuals with some psychiatric disorders than in the general population. When these disorders are diagnosed, we typically assess for OCD as well.

These include schizophrenia or schizoaffective disorders (12 percent with OCD) (7,8), bipolar disorder, Tourette disorder (30 to 50 percent), and eating disorders such as anorexia nervosa or bulimia nervosa (40 percent) Regarding neurologic disorders; OCD is described in individuals with basal ganglia dysfunction such as Huntington disease, Sydenham chorea, and Parkinson disease. It has also been described in temporal lobe epilepsy.

Clinical features

Although most individuals with OCD manifest both obsessions and compulsions; however, both are not necessary for a diagnosis (9,10).

Obsessions are intrusive or unwanted repetitive or persistent thoughts, images, or urges that cause marked distress or anxiety. Obsessions often involve content that is odd, irrational, or of a seemingly magical nature (e.g., harm will come if the closet is not arranged in a specific order). Individuals with OCD attempt to ignore, suppress, or neutralize these thoughts, often with another thought or behavior (compulsion).

Compulsions (or rituals), repetitive behaviors (e.g., washing, checking), or mental acts (e.g., counting, repeating words silently) are behaviors that an individual feels driven to perform to reduce the distress triggered by an obsession or according to rules that must be applied rigidly. While compulsions are often thematically related to an obsession (e.g., washing rituals occur with obsessive fears of contamination), they are often not connected in a realistic way to the feared event or are clearly excessive. Examples of this may be arranging items symmetrically to prevent harm to a loved one, or showering for several hours daily to avoid illness.

The content, frequency, and severity of the symptoms vary widely among individuals. Some individuals have mild to moderate symptoms (spending one to three hours per day obsessing or doing compulsions), whereas others have near constant obsessions or compulsions that can be incapacitating. Certain common themes or "symptom dimensions" are identified. These include cleaning, need for symmetry, counting compulsions, forbidden or taboo thoughts (aggressive, sexual, or religious obsessions and related compulsions) and harm (to self or others). Symptom dimensions provide critical information that is used to tailor cognitive-behavioral therapy treatment.

Individuals with OCD may experience a wide range of affective responses to their obsessions or compulsions. In some cases, the response to the symptom may lead to further psychosocial distress. As an example, some individuals may experience marked anxiety or recurrent panic attacks, Others may feel disgust at themself for their behavior. The distress may persist until the individual attains a sense of "completeness" or until things look, feel, or sound "just right."

OCD is Public Health concern with a critical rate of suicidal thoughts and behaviors in individuals. In a large collaborative survey including 3711 individuals with OCD, suicidal ideation in the past month was reported in 6 percent of individuals while a lifetime suicide attempt was reported in 9 percent (11). However, in a meta-analysis investigating the relationship between individuals with OCD and suicidality, lifetime rates of suicidal ideation were as high as 64 percent (across 18 studies), while lifetime rates of suicide attempt were as high as 46 percent (across 22 studies) (12). Additionally, worsening levels of suicidality in OCD patients are associated with comorbid axis I disorders, severity of symptoms, feelings of hopelessness, and past history of suicide attempts. Some individuals with OCD manifest intrusive fears of harming others (e.g., "harm" symptom dimension). There are no data suggesting that they are more likely to do so at a rate higher than the general population.

Avoidance behaviors are often pervasive and may severely restrict functioning. In some cases, individuals with OCD avoid people, places, or things that trigger obsessions and compulsions. For example, individuals with contamination concerns might avoid public places (e.g., restaurants, public restrooms) to reduce exposure to feared contaminants. Individuals with intrusive thoughts about causing harm to others may avoid social interactions. Dysfunctional beliefs may be present in individuals with OCD. (13). Examples of dysfunctional beliefs include:

-Inflated responsibility and the tendency to overestimate threat -Perfectionism and the intolerance of uncertainty -Overvaluing the importance of thoughts (e.g., believing that having a forbidden thought is as bad as acting on it) and the need to control thoughts These beliefs are present in individuals with other anxiety disorders as well. Individuals with OCD differ in the degree to which they believe that their obsessions and compulsions are excessive or unreasonable (10,14,15). Insight can vary within an individual over the course of the illness. Poor insight has been linked in some (but not all studies) to worse long-term outcomes (16). In a minority of people with OCD (≤4 percent) insight is absent such that their beliefs are delusional in nature. For example, an individual may be convinced that their thoughts can physically harm another person.

The presence of associated features, such as described above, may affect the level of psychosocial impairment. However, some of these features (e.g., dysfunctional beliefs, avoidance behaviors) may be potential targets for psychotherapy.

Assessment and diagnosis

We suspect a diagnosis of OCD in individuals with either intrusive, recurrent, or persistent thoughts, urges, or images, or in those with repetitive mental acts or repetitive behaviors. We also evaluate for other features that may suggest alternative or coexisting disorders.

When possible, we obtain history from family members or other reliable sources in addition to the patient.

We differentiate symptoms due to OCD from other occasional intrusive thoughts or repetitive behaviors that may be common in the general population, by establishing how much time is consumed by the symptoms and the amount of distress associated with them. In OCD, symptoms are time consuming (e.g., more than one hour spent per day with obsessions or compulsive behaviors) or cause significant distress in social or occupational functioning (17,18). The frequency, amount of time consumed, and extent to which obsessions/compulsions cause the patient distress or interfere with their life helps to distinguish OCD from occasional intrusive thoughts or repetitive behaviors that are common in the general population (e.g., double-checking that a door is locked) (17,19). Furthermore, we assess whether there is a link between the compulsive behavior and obsessional symptoms and what the consequences might be of not performing a ritual or compulsion. Compulsions that are done as an attempt to neutralize obsessional thoughts or impulses are common in OCD and may be a helpful diagnostic clue. Individuals with OCD may perform rituals to avoid perceived harm (e.g., showering repeatedly to avoid "contaminants" and subsequent illness).

Individuals with OCD may have symptoms commonly seen in other disorders. For example, individuals may manifest with severe anxiety and panic attacks (as in panic disorder), avoidance of social situations (as in social anxiety disorder), or difficulty discarding objects (as in hoarding disorder). In many cases comorbid diagnosis is present. We evaluate individuals with symptoms of obsession or compulsion for the presence of co-occurring psychiatric disorders. In cases where an individual meets criterion for both disorders, both are diagnosed.

Clinical course and complications

The mean age of onset of OCD is 19.5 years. Nearly 25 percent of cases begin by age 14 years.

Males tend have an earlier age of onset than females. Onset tends to be before age 10 in males and in adolescence in females (2). Onset after age 35 years is unusual (20). The onset of symptoms in OCD is typically gradual; however, acute onset has been reported, and has been associated with infectious etiology.

If untreated, the course of OCD is usually chronic, with waxing and waning symptoms while a minority have a deteriorating course (21,22). While many individuals with onset of OCD in childhood or adolescence will have lifetime symptoms, some individuals will remit by early adulthood (23). In a meta-analysis of 16 studies individuals with OCD were followed for up to 15.6 years (24). Forty percent of individuals (most treated with cognitive-behavioral therapy, pharmacologic management, or both) achieved remission (not meeting criteria for full or subthreshold OCD). Without treatment, rates of remission (usually defined as minimal to no symptoms) of OCD in adults are low (e.g., 20 percent in a 40-year follow-up study of 144 patients).

Remission rates in published research have varied based on comorbidity rates in the samples studied, treatment selection, how treatments were delivered, and how remission was defined.

As an example, a trial found that adults with OCD who received optimally delivered evidencebased treatment for 12 weeks (i.e., Selective serotonin reuptake inhibitor (SSRI), Exposure and Response Prevention (EX/RP), or SSRI+EX/RP) had remission rates ranging from 25 to 58 percent depending upon the specific treatment received. Remission was defined as no more than mild symptoms.

OCD is associated with impaired social and occupational functioning and reduced quality of life (25,26). When OCD starts in childhood or adolescence, individuals may experience developmental difficulties. As examples, adolescents may avoid socializing with peers. Young adults may struggle to leave home and live independently. Individuals with OCD may try to impose rules and prohibitions on family members or other caregivers because of their disorder. This may result in the accommodation of rituals or participation in rituals. High accommodation is often associated with high expressed emotion. Together, these can contribute to poor treatment response, high family or caregiver burden, and poorer quality of life among those who live with individuals with OCD.

Impairments may be related to specific symptoms. As examples, obsessions about harm can make relationships with family and friends feel hazardous and result in avoidance. Obsessions related to symmetry can derail the timely completion of school or work projects. Additionally, individuals with contamination concerns may avoid health care settings due to fear of exposure to germs or may develop dermatologic problems (e.g., skin lesions) due to excessive washing.

In some cases, symptoms of OCD can interfere with its own treatment (e.g., when medications are considered contaminated).

Pathogenesis

Studies suggest that genetic, neurobiological, infectious, and hormonal factors may contribute to the pathogenesis of OCD.

Genetic factors

Twin and family studies suggest that there is a genetic contribution to OCD with greater genetic influences in pediatric-onset OCD than in adult-onset OCD. The precise genes involved in OCD are not known, although work in this area is ongoing (27)(28)(29).

Infections

Pediatric autoimmune neuropsychiatric disorder associated with group A streptococcal infection (PANDAS) is associated with the onset or exacerbation of OCD in some children. In PANDAS, OCD symptoms are hypothesized to be triggered by an autoimmune reaction to group A beta-hemolytic streptococci that damages the basal ganglia. However, as other infectious agents may trigger a similar acute neuropsychiatric syndrome (30), a broader syndrome called both pediatric acute-onset neuropsychiatric syndrome and childhood acute neuropsychiatric symptoms has been proposed.

Hormones

Hormonal fluctuations may play a role in the development of OCD. New onset or exacerbation of OCD has been described in premenstrual and perinatal periods.

Stress/trauma

Stress may play a role in precipitating OCD. Acute OCD onset has been reported in adults following exposure to traumatic events.

Neuroimaging evidence obtained from MRI, fMRI and PET suggested that a dysfunctional CSTC circuitry contributes to the pathophysiology of OCD. This relatively specialized brain network is organized in parallel linking the basal ganglia to discrete areas of the frontal cortex forming loops. It comprises grey matter (GM) regions such as a lateral OFC to the head of the caudate and the ventral striatum, projecting to the mediodorsal thalamus via the internal pallidus and finally returning from the thalamus to the OFC. Lesions to these brain structures result in the inability to inhibit inappropriate contextual responses and to modulate impulsive behaviors.

Neurochemical abnormalities

Neurochemical abnormalities, including changes in serotonergic (31), dopaminergic (32), and/or glutamatergic (33)(34)(35) concentration are hypothesized to play a role in the pathophysiology of OCD. However, studies testing these hypotheses are inconclusive.

Neuroimaging

Neuroimaging research has provided information to better understand the neurobiology of OCD. Structural imaging studies in patients with OCD have reported neuroanatomical abnormalities in Cortico-Striato-Thalamo-Cortical (CSTC) circuits (36).

-Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) A 2014 mega-analysis of 412 adult OCD patients compared with 368 healthy controls (HC) also found abnormalities in the dorsomedial prefrontal cortex, the inferior frontal gyrus, and the cerebellum (37). Meta-and mega-analyses of data from OCD sites worldwide reported different patterns of subcortical abnormalities in adult versus pediatric OCD samples (e.g., abnormalities in the pallidum and hippocampus in adult subjects and thalamic abnormalities in pediatric samples) (38).

PET and fMRI have found abnormal activity in different nodes of the CSTC, including the orbitofrontal cortex (OFC), the anterior cingulate cortex (ACC), and the striatum, in OCD patients compared with HC. The abnormal activity was found to increase during symptom provocation, and to normalize with successful treatments. Other brain regions such as the insular cortex (involved in empathy, compassion and interpersonal relationships such as fairness and cooperation) and the right side of the ACC (associated with cognition such as attention, motivation, working memory, reward and error detection, problem-solving and action-planning) have also been reported to exhibit reduced glucose metabolism in patients suffering from OCD compared to healthy controls. This implies that OCD is not only subtended by disfunction of the prefrontal cortex, but it also involves other brain regions, explaining the complexity of this syndrome (39)(40)(41).

-Magnetic resonance spectroscopy (MRS) MRS is a non-invasive neuroimaging technique that can provide insight into the biochemical profile of the brain (or any body tissue). Primary metabolites of interest commonly detected quantitatively in vivo in a proton MRS spectrum are composed of N-acetylaspartate (NAA), N-acetylasparatateglutamate (NAAG), lactate, glutamate (Glu), glutamine (Gln), gammaaminobutyric acid (GABA), creatine (and phosphocreatine or total Cr), choline-containing compounds (total Cho), myo-inositol (mI), glutathione (GSH), and mobile lipids. The concentration of brain metabolites is critical for the proper functioning of neurons and the maintenance of cellular homeostasis. NAA is a biomarker of neuronal viability, Cr (and phosphocreatine) is an index of high-energy metabolic pathways, Cho is associated with turnover of cellular membrane, mI is a glial marker, mobile lipids are indicative of disordered metabolism, Glu and NAAG are excitatory neurotransmitters, while GABA is an inhibitory neurotransmitter. An imbalance in the amount of these neurometabolites results in a variety of neurological diseases, psychiatric disorders, depression, inflammation, and cognitive impairment (39). 40 peer-reviewed original papers have applied of MRS to characterize OCD. A recent 3T MRS study conducted on OCD patients compared to healthy controls indicated an increase in the amount of choline in three regions of interest (ROI), namely, the pregenual anterior cingulate cortex (pACC), the striatum and the thalamus, considered to be involved in the CSTC circuitry in OCD (42), while the amount of NAA vary depending on the ROI. Increased choline concentration in OCD could be due to an increased membrane turnover signaling a greater demand for membrane renewal caused by alteration/destruction, or membrane proliferation. No significant correlations were observed between metabolite alterations and the OCD severity based on Y-BOCS score. NAA, which is a marker of neuronal integrity and synaptic abundance, was shown to normalize after behavioral therapy(43) in a 1.5T MRI scanner. Another study also in 1.5T MRI scanner magnetic field indicated a decrease in NAA/Cr ratios in the ACC of unmedicated OCD participants compared to healthy controls, whereas the ratios were negatively-correlated with the Y-BOCS score (44).

The concentration of the ubiquitous excitatory neurotransmitter glutamate which can be determined by MRS and alterations of Glu (or Glx) levels in the brain have been linked to dysregulation of glutamate signaling involved in the CSTC circuitry in OCD (33,34). A review of OCD MRS literature from 1997-2013 in the fronto-striatal region of glutamatergic compounds summarized 11 studies comparing OCD patients versus healthy controls, and 9 studies evaluating Glu variations in OCD post-treatment (45). Unfortunately, from this review of the existing literature, no definite conclusion could be drawn since glutamate levels varied among groups. Furthermore, regarding two 1.5T MRS studies of pediatric OCD patients, one reported reduced ACC Glx levels after four weeks of daily cognitive behavioral therapy (CBT) (46), while another (44) concluded no changes in Glx levels after CBT or SSRIs. Many of the investigations reported in this review paper were pilot exploratory studies, and taken together provided inconsistent results, caused by the application of relatively new MRS methods in OCD. Other discrepancies originated from poor MRSS spectral resolution (when MRI of less than 3T were used), the use of different quantification methods (absolute values or ratios), limited sample size, age difference, comorbidity, illness severity, and medications.

In addition to regionally-specific features of the neurometabolites, accurate measurement of the absolute concentrations of metabolites in the human brain using MRS is fraught with difficulty due to their low concentrations (0.4-0.8 mmol/kg) (47) and overlapping signals requiring long scan times to obtain sufficient signal-to-noise ratio to detect multiple metabolites from several brain locations. Furthermore, challenges of MRS studies in OCD participants also include recruiting medication-free cases since most patients are typically on SSRIs medication which can affect concentrations of brain metabolites, and the presence of comorbidity (anxiety and depression) which can cause sample heterogeneity.

Abnormalities in other brain regions have also been reported and the model for OCD now includes abnormalities in multiple brain circuits, not just CSTC circuits (9). Indeed, a few studies support evidence in favor of an increasingly recognized role of caudal brain regions in OCD pathogenesis, by reporting white matter (WM) abnormalities in temporoparietal-occipital regions and in long-range cortico-cortical bundles connecting the frontal, parietal, temporal and occipital lobes. Accordingly, the anatomical circuitry model for OCD has been modified to include the hippocampus, the anterior cingulate and basolateral amygdala, all of which are connected to the OFC, due to functional implication of these limbic regions in affective states such as depression and in emotional as well as motivational aspects of behavior as developed above (refer to hormones and stress/trauma sections). Furthermore, case reports show that neurosurgical alteration to CSTC circuits can reduce symptoms of OCD and new onset of OCD can occur after neurologic lesions such as ischemic stroke or traumatic brain injury (48)(49)(50)(51).

To summarize, structural and functional imaging studies have found abnormalities in CSTC circuits in patients with OCD (36,52). While there are inconsistencies among studies, the most commonly reported abnormalities occur in the OFC, prefrontal cortex, the ACC, striatum, hippocampus and the pallidum (53,54).

The objective of my PhD work was then threefold:

-Highlight results from the literature in terms of brain regions involved in OCD -Taking into account the previous results, we will aim to replicate those results using

INTRODUCTION

Obsessive compulsive disorder (OCD) is a widespread, chronic and long-term neuropsychiatric disorder characterized by uncontrollable, recurrent, and distressing thoughts (obsessions) and/or repetitive behaviors (compulsions) [1].

Obsessions are incessant, intrusive and upsetting thoughts driven by non-substantiated contents about contamination (i.e., touching contaminated objects or being infected by hands-shaking) which will cause the individual to wash his hands or shower repeatedly during the day, or to harbor ongoing doubts leading to preventive safety chores to be accomplished (i.e. locking and unlocking doors, or turning off the gas stove or iron), compelling the person to check the act over and over. Other common pathological obsessions can include perfectionism, losing control, forbidden perverse sexual thoughts, or fear of harming others.

Compulsions are repetitive behaviors or mental acts the individual feels driven to perform to alleviate the distress provoked by the obsession. The repetitive action is undoubtedly excessive or is not obviously associated with the anxiety patients try to relieve or neutralize, a fact that they usually recognize as illogical (e.g., ordering and arranging household items; counting forward and backward to prevent harm to loved ones). While compulsions effectively reduce momentary distress, paradoxically, they worsen the former, aggravating associated obsessions and compulsions, consequences which are time-consuming, cause considerable distress, and significantly obstruct normal daily functioning.

People suffering from OCD, indeed, spend more than an hour a day on thoughts and rituals.

They realize that such repeated behaviors do not make sense, and fail to bring pleasure and gratification.

EPIDEMIOLOGY

OCD ranks as the fourth most common mental disorder in developed countries (after depression, substance abuse and phobias), and globally is considered the tenth leading cause of disability due to its high prevalence and debilitating nature. It typically begins in childhood or adolescence, persists throughout a person's life, and produces substantial impairment in functioning due to the severe and chronic nature of the illness. OCD has an estimated 12-month prevalence of 1.2 percent and an estimated lifetime prevalence of 2.3 percent [2,3] among adults in the United States of North-America. Females are affected at a slightly higher rate than males in adulthood, although males are more commonly affected in childhood [4]. Furthermore, approximately one half (50.6%) of adults with OCD, had serious impairment whereas 34.8% had moderate impairment, and 14.6% showed mild impairment determined by the Sheehan Disability Scale. OCD affects people of all races and socioeconomic backgrounds.

ETIOLOGY

Despite numerous research projects being conducted into OCD, the exact nature causing the disorder has yet to be identified. OCD can be triggered by a combination of genetic, behavioral, cognitive, neurological, autoimmune, and environmental factors. OCD is considered a hereditary disorder that can span generations.

Genetic factors account for heritability of OCD as shown in twin studies of adults on OCD indicating genetic influence in the range of 45-65% of variance [5], and first-degree relatives show increased rates of 10-22.5% compared to a healthy population risk of 2-3% [6].

In humans, although no single gene has been identified to cause OCD, serotonin transporter (hSERT) and neuronal glutamate transporter (SLC1A1) genes have been proposed as factors playing a role in OCD development [7,8]. hSERT absorbs surplus serotonin in the synapse after transmission of a nerve signal to the next nerve cell. Accordingly, abnormalities in serotonin regulation and mutations in hSERT, either through increased or decreased serotonin levels, have been observed in OCD individuals.

In rodents, increased anxiety and compulsive grooming behavior has been observed upon deletion of the gene encoding for the synapse-associated protein 90/postsynaptic density protein95-associated protein 3 (SAPAP3) [9,10].

Behavioral theories suggest that OCD patients associate certain objects or situations with fear and either learn to avoid them or execute rituals to alleviate that feeling. Cognitive theories suggest that people with OCD misinterpret their thoughts, and the importance of these invasive thoughts are amplified [11].

Neurological causes of OCD originate have involved the dysfunction of brain circuitry regulating behavior such as aggression, sexuality and body excretions. Key areas of the brain associated with OCD include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), striatum, thalamus, anterior cingulate gyrus, caudate nucleus and basal ganglia [12].

Repetitive behavioral symptoms associated with OCD result from an imbalance of specific neurotransmitters (serotonin, dopamine and glutamate) [6,[13][14][15] affecting neuronal communication associated to judgment and body movements.

Rapid onset of OCD in children has been found to be associated with pediatric autoimmune neuropsychiatric disorders linked to streptococcal infections (PANDAS) or to pediatric acuteonset neuropsychiatric syndrome (PANS) consequence of infection and inflammation in the basal ganglia by Group A streptococcal bacterial strain and other pathogens responsible for Lyme disease, or H1N1 virus [16].

Last but not least, a recent review [17] proposed that episodic OCD is a consequence of alterations in gut microbiota or gut dysbiosis caused by prophylactic antibiotics to treat infections.

Additionally, potential environmental factors that can stimulate OCD symptoms include abuse, changes in living or work conditions, illness, traumatic life events, and relationship problems.

DIAGNOSIS

The Yale-Brown obsessive-compulsive scale (Y-BOCS), designed in 1989 by Wayne K.

Goodman and his colleagues, is used extensively as a gold standard in research and clinical practice to determine severity of OCD and to monitor improvement during treatment [18]. This scale, which measures obsessions separately from compulsions, specifically measures the severity of OCD symptoms without biases such as the content of obsessions or the type of compulsions present [19,20]. Scale items depend on the patient's report and the final rating is based on the clinical judgment of the interviewer. Additional information provided by family members allow a better evaluation of symptoms. In a second edition of the Y-BOCS, named the Y-BOCS II elaborated in 2010 by Goodman and colleagues, changes were made to the Severity Scale item content and scoring framework. Avoidance was integrated into the scoring of Severity Scale items, and the Symptom Checklist content and format was modified [21]. A clinician-report questionnaire designed to assess symptoms of OCD from childhood through early adolescence, called the Children's Yale-Brown Obsessive Compulsive Scales (CY-BOCS) has also been established [19].

PATHOPHYSIOLOGY

Neuroimaging Neuroimaging research has provided information to better understand the neurobiology of OCD. Structural imaging studies in patients with OCD have reported neuroanatomical abnormalities in Cortico-Striato-Thalamo-Cortical (CSTC) circuits [22]. While there are inconsistencies among specific studies and even among meta-analyses, many authors concur in reporting abnormalities in the OFC, the ACC, and the striatum. A 2014 mega-analysis of 412 adult OCD patients compared with 368 healthy controls (HC) also found abnormalities in the dorsomedial prefrontal cortex, the inferior frontal gyrus, and the cerebellum [23]. Meta-and mega-analyses of data from OCD sites worldwide reported different patterns of subcortical abnormalities in adult versus pediatric OCD samples (e.g., abnormalities in the pallidum and hippocampus in adult subjects and thalamic abnormalities in pediatric samples) [24].

Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have found abnormal activity in different nodes of the CSTC, including the OFC, the ACC, and the striatum, in OCD patients compared with HC. The abnormal activity was found to increase during symptom provocation, and to normalize with successful treatments. Other brain regions such as the insular cortex (involved in empathy, compassion and interpersonal relationships such as fairness and cooperation) and the right side of the ACC (associated with cognition such as attention, motivation, working memory, reward and error detection, problem-solving and action-planning) have also been reported to exhibit reduced glucose metabolism in patients suffering from OCD compared to healthy controls. This implies that OCD is not only subtended by disfunction of the prefrontal cortex, but it also involves other brain regions, explaining the complexity of the this syndrome [25][26][27].

Magnetic resonance spectroscopy (MRS) is a non-invasive neuroimaging technique that can provide insight into the biochemical profile of the brain (or any body tissue). Primary metabolites of interest commonly detected quantitatively in vivo in a proton MRS spectrum are composed of N-acetylaspartate (NAA), N-acetylasparatateglutamate (NAAG), lactate, glutamate (Glu), glutamine (Gln), gamma-aminobutyric acid (GABA), creatine (and phosphocreatine or total Cr), choline-containing compounds (total Cho), myo-inositol (mI), glutathione (GSH), and mobile lipids. The concentration of brain metabolites is critical for the proper functioning of neurons and the maintenance of cellular homeostasis. NAA is a biomarker of neuronal viability, Cr (and phosphocreatine) is an index of high-energy metabolic pathways, Cho is associated with turnover of cellular membrane, mI is a glial marker, mobile lipids are indicative of disordered metabolism, Glu and NAAG are excitatory neurotransmitters, while GABA is an inhibitory neurotransmitter. An imbalance in the amount of these neurometabolites results in a variety of neurological diseases, psychiatric disorders, depression, inflammation, and cognitive impairment [25].

One of the earliest 1 H-MRS study of OCD patients was performed more than 20 years ago showing the utility of the technique as a means to get a glimpse of the intricacies of the brain and to better understand the neuropathophysiology of OCD. It reported evidence of neuronal loss in the anterior cingulate gyrus and the right striatum as shown by lower NAA levels correlated with Y-BOCS scores of illness severity [26,27]. Since then, approximately 40 peerreviewed original papers have applied of MRS to characterize OCD. A recent 3T MRS study conducted on OCD patients compared to healthy controls indicated an increase in the amount of choline in three regions of interest (ROI), namely, the pregenual anterior cingulate cortex (pACC), the striatum and the thalamus, considered to be involved in the CSTC circuitry in OCD [28], while the amount of NAA vary depending on the ROI. Increased choline concentration in OCD could be due to an increased membrane turnover signaling a greater demand for membrane renewal caused by alteration/destruction, or membrane proliferation. No significant correlations were observed between metabolite alterations and the OCD severity based on Y-BOCS score. NAA, which is a marker of neuronal integrity and synaptic abundance, was shown to normalize after behavioral therapy [29] in a 1.5T MRI scanner. Another study also in 1.5T MRI scanner magnetic field indicated a decrease in NAA/Cr ratios in the ACC of unmedicated OCD participants compared to healthy controls, whereas the ratios were negatively-correlated with the Y-BOCS score [30].

The concentration of the ubiquitous excitatory neurotransmitter glutamate which can be determined by MRS and alterations of Glu (or Glx) levels in the brain have been linked to dysregulation of glutamate signaling involved in the CSTC circuitry in OCD [6,15]. A review of OCD MRS literature from 1997-2013 in the fronto-striatal region of glutamatergic compounds summarized 11 studies comparing OCD patients versus healthy controls, and 9 studies evaluating Glu variations in OCD post-treatment [31]. Unfortunately, from this review of the existing literature, no definite conclusion could be drawn since glutamate levels varied among groups. Furthermore, regarding two 1.5T MRS studies of pediatric OCD patients, one reported reduced ACC Glx levels after four weeks of daily cognitive behavioral therapy (CBT) [32], while another [30] concluded no changes in Glx levels after CBT or SSRIs. Many of the investigations reported in this review paper were pilot exploratory studies, and taken together provided inconsistent results, caused by the application of relatively new MRS methods in OCD. Other discrepancies originated from poor MRSS spectral resolution (when MRI of less than 3T were used), the use of different quantification methods (absolute values or ratios), limited sample size, age difference, comorbidity, illness severity, and medications.

Since then, another MRS study in a 3T MRI scanner using single-voxel water-suppressed point resolved spectroscopy (PRESS) showed elevation of Glx (Glu+Gln) in the pACC, a brain region linked with anxiety, mood disturbance and other negative emotions in OCD [33].

Decreased glutamate level in the thalamus and in the medial prefrontal cortex (mPFC) was reported in a 3T PRESS-MRS study of unmedicated OCD patients [34]. Another 3T 1 H-MRS study reported a reduced Gln/Glu, but an enhanced mI concentration in the DLPFC of OCD patients compared to HCs, and no difference in NAA, Cho, lactate and lipid between the two groups [35].

In addition to regionally-specific features of the neurometabolites, accurate measurement of the absolute concentrations of metabolites in the human brain using MRS is fraught with difficulty due to their low concentrations (0.4-0.8 mmol/kg) [36] and overlapping signals requiring long scan times to obtain sufficient signal-to-noise ratio to detect multiple metabolites from several brain locations. Furthermore, challenges of MRS studies in OCD participants also include recruiting medication-free cases since most patients are typically on SSRIs medication which can affect concentrations of brain metabolites, and the presence of comorbidity (anxiety and depression) which can cause sample heterogeneity.

Biomarkers

Biomarkers are characteristic biological components or features (such as specific molecules, cells, genes or gene products, enzymes, or hormones) able to predict the presence, magnitude or the prognosis of a disease. Sample material containing biomarkers for diagnostic purposes must be easy to extract, as for example, from saliva, blood or urine. In contrast to physical illness such as hepatitis, cancer or diabetes, no available laboratory tests nor imaging methods exist yet to diagnose OCD. Previous studies on OCD patients compared with healthy controls suggested elevated levels of glutamate and glycine (a co-agonist of glutamate in NMDA receptor sites) in the cerebrospinal fluid (CSF) based on the measurement of auto-antibodies against the basal ganglia, and thalamus, hence suggesting glutamate signaling dysfunction within the CSTC circuitry in OCD.

Glutamate is the main neurotransmitter present in cortico-striatal-thalamic circuits among a majority of axon terminals in the striatum being glutamatergic. Evidence from in vivo proton magnetic resonance spectroscopy (MRS) studies in psychotropic-naïve pediatric OCD patients also showed increased glutamate concentrations in the left caudate (located in dorsal striatum responsible for reward functioning) implicating that glutamate neurotransmission within the CTSC circuits is disrupted in OCD [6,15].

Neurocircuitry

Neuroimaging evidence obtained from MRI, fMRI and PET suggested that a dysfunctional CSTC circuitry contributes to the pathophysiology of OCD. This relatively specialized brain network is organized in parallel linking the basal ganglia to discrete areas of the frontal cortex forming loops [25]. It comprises grey matter (GM) regions such as a lateral OFC to the head of the caudate and the ventral striatum, projecting to the mediodorsal thalamus via the internal pallidus and finally returning from the thalamus to the OFC (Figure 2). Lesions to these brain structures result in the inability to inhibit inappropriate contextual responses and to modulate impulsive behaviors.

Other studies support evidence in favor of an increasingly recognized role of caudal brain regions in OCD pathogenesis, by reporting white matter (WM) abnormalities in temporoparietal-occipital regions and in long-range cortico-cortical bundles connecting the frontal, parietal, temporal and occipital lobes. Accordingly, the anatomical circuitry model for OCD has been modified to include the hippocampus, the anterior cingulate and basolateral amygdala, all of which are connected to the OFC, due to functional implication of these limbic regions in affective states and in emotional as well as motivational aspects of behavior.

Theoretical of OCD behaviors

In in 2014, David L. Pauls et al. [37] presented a theoretical model to explain obsessivecompulsive behavior in OCD. According to these authors, exaggerated concerns about danger, hygiene or harm suffered by OCD patients, results in a persistent conscious attention to the perceived threat; in other words, they develop obsessions. In response to the distress associated with these obsessions, the patient acts (i.e. performs a behavior) to neutralize the distress, a response that provides temporary relief from distress associated with the obsession. However, this same relief leads to reinforcement of the behaviors, leading to repetitive, compulsive behavior when obsessions recur.

Such an apparently satisfactory explanatory model for OCD symptoms can only partially

account for an explanatory model on how this same system might work in healthy participants. This is important, since we all have to deal with concerns about danger, hygiene or harm, without having to perform repetitive behaviors to deal with such fears. Indeed, a concern, no matter how relevant, can be put away simply by the thought, the conviction or the obsession that we are going to take charge of it. In other words, for a concern related to dirt, a patient suffering from OCD will experience a haunting ideation and significant distress. To resist this distress, the patient will clean himself in accordance with ritualized behaviors. Instead, the same concern in a healthy individual may also lead to a haunting idea of cleaning associated with distress. However, to postpone the cleaning task a few hours or days later will be enough to remove the distress (Figure 1).

Treatments

If untreated, OCD becomes a chronic condition with a 20% remission rate. However, about 40% of patients who develop OCD in childhood will experience remission during early adulthood. First-line treatments, include medication using inhibiting presynaptic reuptake of serotonin (SSRIs) and cognitive behavioral therapy (CBT).

Psychotherapy

CBT for OCD involves assisting patients to change their ideas or patterns related to obsessive thoughts and compulsions. CBT is a set of techniques which are used to help people with psychological disorders modify maladaptive patterns of thinking and acting to alleviate emotional symptoms. Components of CBT for OCD include: education, cognitive therapy techniques, exposure therapy and response prevention (ExRP).

ExRP is an adequate therapy where the patient is deliberately and repeatedly exposed to obsessions-triggering, hence distressing situations and when it increases the urge to engage in compulsions. Indeed, repeated exposure to aversive stimuli, while not acting on compulsions leads to a habituation, gradually decreasing distress intensity. The response refers to the learning portion of the treatment wherein the patient resists the compulsion to perform rituals to enable him/her to stop repetitious actions. The therapist helps the patient deal with the generated distress while encouraging the patient to resist the compulsion (i.e. excessive washing). The goal is for the individual to reach the point where encountered obsessional trigger will not cause ritualistic behavior. Patients work toward elimination of compulsive behavior by identifying and re-assessing their beliefs about the consequences of acting out or not acting out the compulsive behavior. This treatment has been associated with a 75% improvement rate, depending on the individual's tolerance to anxiety and resistance to compulsions.

Pharmacotherapy

OCD medications are composed of tricyclic antidepressants (TCA), selective serotonin reuptake inhibitors (SSRIs), and serotonin-norepinephrine reuptake inhibitors (SNRIs) [20].

Clomipramine is the only TCA used for OCD. Available SSRIs include fluoxetine, fluvoxamine, paroxetine and sertraline. SSRIs are usually preferred over clomipramine for OCD treatment since adverse effects of SSRIs are less pronounced and TCAs have higher risk of cardiac arrhythmia, an adverse effect to take seriously in account for patients with high risk of suicide. SSRIs slow down the collection (reuptake) of serotonin by transporters such as hSERT impairing effective interneuronal communication. Alternative to SSRIs are SNRIs, which are as effective as SSRIs due to their anti-obsessional properties. SNRIs such as venlafaxine and duloxetine are sometimes preferred over SSRIs for patients with certain types of treatment-resistant OCD or those with specific comorbid conditions indicating the heterogeneous nature of OCD.

Only 40-60% of patients show no-or just partial symptom improvement after this firstline pharmacological treatment. Successful SSRI treatment should be maintained at the optimal effective dose for at least 12 months. In routine practice, it is challenging to predict which patients will respond effectively to a pharmacological treatment and which ones will not.

Treatment of OCD patients refractory to serotonergic antidepressants include dose increase, intravenous clomipramine, switching to other first-line drugs or combination of first-line drugs, augmentation with antipsychotics (i.e. haloperidol, risperidone, quetiapine, aripiprazole, or olanzapine), augmentation with CBT, and trial with other drugs such as memantine or amantadine (both N-methyl-D-aspartate or NMDA receptor antagonists), N-acetylcysteine (glutamate modulator), D-cycloserine (glutamatergic agent and NMDA receptor agonist), mirtazapine (serotonin receptor antagonist), or benzodiazepine. Thus, despite advances in pharmacotherapy, clinical or psychopathological parameters cannot predict successful response to medication.

Neurosurgery and deep brain stimulation

The treatment resistant OCD patients are potential candidates for neurosurgery with lesion procedures (cingulotomy or capsulotomy) or deep brain stimulation.

Cingulotomy and capsulotomy are surgical procedures involving drilling through the cranium (craniotomy) or skull and using thermal (heated) probe to ablate the ACC and the anterior limb of the internal capsule, respectively [38]. Recently, the use of a "gamma knife" [39] has allowed capsulotomy without drilling through the skull, wherein multiple gamma rays introduced through the skull can induce an ablation of the targeted region. About 60% of implanted patients operated upon appear to respond to this procedure.

The Deep brain stimulation (DBS) procedure involves the implantation of intracranial electrodes delivering trains of electrical pulses on specific brain locations as the subthalamic nucleus (STN) or the ventral striatum / ventral capsule (VS/VC) [40][41][42]. This technique causes no major brain damage, but postoperatively it requires intensive adjustments and lifelong maintenance of the stimulation hardware, particularly battery replacement. Although effective to treat several disorders such as Parkinson disease [43], Dystonia [44], Tourette syndrome [45] or OCD [46] the action mechanisms of DBS remain unknown whereas the optimal brain target for implanted electrodes and the detailed stimulation parameters (frequency, amplitude and number of pulses) are still debated. The activity of the electrode can be programmed externally with a portable appliance communicating with the pulse generator through telemetry.

Adjustments can be made to the frequency, intensity, pulse width, and location of neurostimulation. Location is adjusted by selecting the pass of electrical current through one or several combinations of electrode contacts within implanted lead or leads (bilateral implantations). Each contact (usually four per lead) can be stimulated separately [47]. This adjustment phase takes in average three to six months, but may require up to 12 months in some OCD patients. It is only when adjustments appear to result in clinically relevant responses, that stimulation is maintained continuously at fixed parameters. Typical stimulation parameters for DBS in OCD can vary within the following ranges [48]: Frequency between 130 and 185 Hertz; Current power between 1 and 10 Volts; Pulse widths between 60 and 150 microseconds.

Response rates for DBS are about 61.5% of implanted patients [33], hence slightly higher than brain lesion procedures. Nonetheless, the number of patients treated with DBS remains very low compared to other therapeutic procedures.

ANIMALS AS A MODEL TO MOVE FORWARD

Animal models in psychiatry can accurately replicate the clinical pathology of the human disorder. They have been proven important for understanding the cellular and molecular mechanisms of psychiatric diseases and exploring preclinical evidence on therapeutic effects [49]. Animal models mimicking OCD-like behavior have been generated for the past 30 years to study the pathophysiology of the disorder. Nonetheless, establishing an accurate replica of a human OCD in animal models remains challenging. OCD, which is composed of obsessions and compulsions pose difficulty to be recreated in animal models since these symptoms are dependent on written or verbal communications or cues. On the other hand, compulsions or ritualistic acts are observable through behavioral manifestations. While OCD animal model studies emulate compulsions representing repetitive actions, they still offer means to check causality and test hypothesis, thus, providing extremely important information regarding OCD brain circuitry.

In any case, OCD-like stereotypies of purposeless repetitive motor routines include nestbuilding behavior characterized by rapid and repeated movements of the front legs, using paws and mouth to pull in cotton through metal bars, over-grooming, non-nutritive chewing, or shifting/digging in bedding as in the marble burying test. Potential usefulness of a given model must satisfy at least one of the following criteria: face validity (behaviors resembling human responses), construct validity (share biological features as humans), and predictive validity (analogous response to therapeutic agents prescribed to human population) [50].

Review papers comparing different animal models are available [51]. In general, these models are divided into several types, namely, genetic, immunological, pharmacological, behavioral, and optogenetic attributes. An established genetic model of pseudo-OCD behavior is the Sapap3-KO mice. Sapap3, a post-synaptic scaffolding protein, is highly expressed in the cortico-striatal glutamatergic synapses, and deletion of the gene produced the first genetic animal model satisfying face, construct, and predictive validity for OCD mouse model. Sapap3-KO mice exhibit increased anxiety, self-inflicted grooming to the point of facial hair loss and skin lesions, aberrant glutamatergic neurotransmission at the cortico-striatal synapses, and enhanced spontaneous medium spiny neuron firing activity at the centro-medial striatum.

Repeated administration of fluoxetine, as prescribed for human OCD [52], to Sapap3-KO mice alleviated the symptoms of excessive grooming and anxiety as evaluated by the open field, elevated zero maze and dark light emergence tests [53]. Other genetic mouse models have been developed since then including the deletions of the gene for Slitrk5 (protein involved in neurite outgrowth and expressed in hippocampus and striatum), Hoxb8 (expressed in bone-marrow microglial cells migrating into OFC, cingulate cortex and limbic system), and Slc1a1/Eaac1 (abundant in human cortex, striatum, and thalamus), all of which shows OCD-relevant behavioral phenotype of self-injurious grooming, although Eaac1-KO mice demonstrated modest OCD-like activities [54].

An animal model to mimic the streptococcal infections to cause OCD behavior and tics among children and to simulate PANDAS showed mixed results. One immunological model is to infect rodents with beta-homolytic Streptococcus pyogenes and this rat model exhibited increased marble-burying activity, although the construct validity is somewhat challenging to assess given the lack of pathogenicity of Streptococcus in rodents [50]. A behavioral OCD animal model is a deer mouse (Peromyscus maniculatus), which can be utilized as a platform for behavior and drug discovery. Deer mouse is a natural OCD model exhibiting dual topographies of stereotypy: pattern running and vertical stereotypy manifested as backward somersaulting and repetitive jumping, which can be reduced by chronic fluoxetine administration. The purposeless feature of such behavior that develops spontaneously and provides face validity for OCD implies a genetic connection to human OCD. High stereotypic animals in a deer mouse population showed frontal cortical glutathione redox imbalance, and decreased striatal serotonin transporter (SERT) density which is associated with enhanced OCD symptom severity. Since SERT is the primary target for SSRIs, deer mouse pathological stereotypy can be useful in understanding the genetics and neurobiological basis of OCD, and may provide better interpretation of treatment variability and treatment resistance in OCD.

The quinpirole (QNP) rat sensitization is an example of a pharmacological animal model wherein a dose of dopamine agonist quinpirole (0.5 mg/kg) is injected for 3-4 days to induce locomotor sensitization in Y-maze or open field chamber, and compulsive checking is manifested by excessive preoccupation of one location into which the animal returns repeatedly. DBS stimulation of the subthalamic nucleus reduces compulsivity in QNP rats suggesting a link of the indirect pathway of the CSTC circuitry to compulsion, and that multiple QNP administration is thought to provoke dopaminergic hyperactivity [55]. Abnormal grooming behavior was reversed upon treatment with SSRI fluoxetine. This experiment demonstrated that hyperactivation of neuronal circuits associated with human OCD can lead to the development of pathologic grooming pattern in wild-type mice [56].

Animal models can only replicate certain aspects of what is being modeled, and OCD animal models of various species using mice, monkeys, rabbits, birds, cats, and horses [57] cannot reproduce the entire human cognitive and behavioral phenotype associated with OCD-relevant symptoms, obviously due to neuroanatomical differences across species. Nevertheless, a wellvalidated convincing animal model should offer new understanding to pursue novel areas of investigations in OCD research and to provide development of new treatment strategies, thereby translating findings from animal work into the clinics.

Conclusions

OCD is a highly prevalent and disabling psychiatric disorder. Advances made by integrative research in animal OCD models with integrated genetic, neurochemical and behavioral assays and also human OCD patients using MRI based neuroimaging and deep brain stimulation have greatly contributed to improve therapeutic options for these patients. Regardless, accurate diagnosis and characterization remains paramount because OCD is commonly misdiagnosed as anxiety or depression. Therapeutically speaking, while first-line of therapy includes exposure and response prevention combined with abstinence from compulsive behaviors and SSRIs, more effective novel pharmacological approaches inspired by OCD research in animal models will surely be developed in the future. The discovery of relations between additional genes that directly contribute to OCD pathology will allow a deeper understanding of the neurobiology and pathophysiology of this disorder and provide predictive biomarkers for diagnostic, prognostic purposes or to anticipate therapeutic outcomes. Most importantly an individualized approach to OCD therapy remains key since every patient stepping into a clinic or a consultation presents a unique case, with an exclusive set of personality features, family dynamics, and parental characteristics which contribute to the severity of this illness and may influence therapeutic response. It is hence vital once a diagnosis is made that the clinician provide accurate information to the patient, so that these understand the nature of their illness and the predicted mechanisms for the prescribed treatments. All in all, evidence-based patient customized therapeutic approaches by educating patients well is a responsibility of the clinician and has the potential to enhance therapeutic compliance and outcomes.

Introduction

Obsessive Compulsive Disorder (OCD) is a leading cause of disability worldwide (2). Many epidemiologic studies have rated the lifetime prevalence of OCD ranging between 1.9% and 3.0% (55). It is a chronic neuropsychiatric disorder marked by intrusive and disturbing thoughts, images or impulses (obsessions) and repetitive, ritualized behaviors (compulsions) that the patient feels driven to perform. Most of the OCD patients complain, firstly from checking symptoms (feeling compelled to check the doors are locked -the gas is off), secondly from washing symptoms (cleaning, hand-washing compulsions, and contamination) and finally from other symptoms such as the taboo thoughts or the need for symmetry (56). Over time, compulsions can become so time consuming (>1 hour /day) or onerous that they engender anxiety themselves. These symptoms produce profound distress and most frequently interfere heavily with daily functioning.

Approximately 70% of patients experience significant symptomatic relief with appropriate pharmacotherapy (57). Selective serotonin reuptake inhibitors (SSRIs) are the main pharmacological treatment. The combination of medication with Cognitive and Behavioral Therapies (CBT) is often used. However, treating patients suffering from OCD disorders remains a critical clinical challenge.

Today, preclinical literature strongly suggests that OCD can be characterized by abnormalities in fronto-striatal circuits involved in learning and habitual control (58). The focus on such abnormalities has led practitioners to develop links with neurosurgeons in order to use high frequency Deep Brain Stimulation (DBS) for the most severe treatment-resistant OCD patients, as well as non-invasive techniques such as repetitive transcranial magnetic stimulation (rTMS).

Nowadays, the improvement of these stimulation procedures allows to stimulate deeper thanks to the development of new specific coils and more accurately thanks to neuronavigation device.

That is why, the more accurate we manage to be in determining the brain regions involved in OCD, the better we would be able to treat the patients' resistant to pharmacotherapy.

In order to specify a neuroanatomical target of non-invasive therapeutic stimulations and neurosurgery within the fronto-striatal circuits, research has suggested that a focus on the orbitofrontal cortex (OFC) which belongs to the prefrontal cortex (PFC) and occupies the central part of the frontal lobe, may be highly relevant. Baxter et al. (59), using neuroimaging to compare a group of patients suffering from OCD with a sample of healthy controls (HC), have first demonstrated a bilateral hyperactivity of the OFC in patients compared to controls.

Since then, several functional neuroimaging have replicated these findings, reporting either leftsided, right-sided, or bilateral PFC hyperactivation or hypermetabolism in OCD (60). Finally, Rotge et al. (61) showed that altered left lateral OFC activity may not only be a crucial marker of OCD symptomatology but could also play a role in its genesis.

Researchers have also been looking for a biomarker able to reflect the response to a therapeutic and that stimulating this region may benefit patients suffering from OCD. Considered together, these results strongly suggest that altered OFC activity is a functional biomarker of OCD and a potential predictor of response to treatment.

Regarding its function, the OFC has been widely implicated in reinforcement processing, both in animals and humans, which appeared to be deficient in patients suffering from OCD. It is also clear that there is a functional heterogeneity within this region and recent fMRI studies in humans have suggested distinct roles in reinforcement processing for different subregions of the OFC (67)(68)(69)(70). As revealed by a large meta-analysis, one of the most reliable distinctions made is the trend for medial regions of the OFC (mOFC) to be more associated with positive reinforcement, whereas lateral regions (lOFC) seem to be more often associated with negative reinforcement, which is characteristics of OCD (Figure 1). Moreover, it has been hypothesized that the results obtained in lesion studies may reflect a critical role of the lOFC in inhibiting previously established responses which cease to be appropriate (71,72).

The distinction between lOFC and mOFC dysfunction in OCD was suggested by an early PET study reporting that OCD symptoms were positively correlated with the metabolism in the anterolateral OFC and were negatively correlated with the metabolism in the posteromedial OFC regions (73).

Subsequent fMRI studies reported positive correlations between hyperactivation of the lOFC and OCD symptoms severity during the performance of the serial reaction time (SRT) task (74) and during symptoms provocation (75,76). Studies of OCD treatment response have shown that lOFC hyperactivity prior to therapy predicts the subsequent response to serotonergic reuptake inhibitors; the less the magnitude of OFC hyperactivity, the better the response to treatment [START_REF] Rauch | Predictors of Fluvoxamine Response in Contamination-related Obsessive Compulsive Disorder A PET Symptom Provocation Study[END_REF]. Based on this literature review, our hypothesis is that the lOFC is involved in OCD and can be a relevant target to treat this disorder using non-invasive (rTMS) and invasive (deep brain stimulation) techniques. We believe that both the treatments of OCD and the monitoring of the efficiency of these treatments, especially DBS, rTMS, and the pharmacological ones, can be improved using a task that would be performed differently by OCD patients and HC and targeting a superficial brain area such as the lOFC.

This behavioral task should present the following characteristics: simple and short, with results easy to assess and involving the lOFC.

No study has found any difference between OCD patients and HC in terms of correct answers to a specific cognitive task. Millet et al [START_REF] Millet | Obsessive Compulsive Disorder Networks: Positron Emission Tomography and Neuropsychology Provide New Insights. Soriano-Mas C, éditeur[END_REF] in 2013 have compared OCD patients and HC using several neuropsychological tests such as Hopkins test, word fluency, rey complex figure copy, trail making test, tower of London, Stroop test and object alternation task. They only found statistical difference between OCD patients and HC in terms of response time; They did not find any difference concerning the number of correct answers.

In a study of Elliott D. F et al. (71) which demonstrated that the lOFC is more activated in the Delayed Non Matching to Sample (DNMS) task than in the Delayed Matching to Sample (DMS) task, we decided to focus on the DNMS. To our knowledge, the DNMS task has never been tested in OCD patients. However only two studies have already studied the DMS task in OCD patients versus HC without showing any significant statistical difference in terms of correct answers [START_REF] Ciesielski | Increased MEG activation in OCD reflects a compensatory mechanism specific to the phase of a visual working memory task[END_REF]82).

In this study, our primary objective is firstly to compare performances of OCD patients versus HC on the DNMS task, secondly on the DMS task and lastly compare the performances of OCD patients on the DNMS task versus DMS task in terms of correct answers and reaction time. Our hypothesis is that OCD patients are more impaired in the DNMS task than in the DMS task.

Methods

Participants

Patients with OCD, from 18 to 65 years old, were recruited prospectively over 4 months from the adult psychiatry department of La Pitié Salpêtrière Hospital, in Paris (France). The diagnosis of OCD has been made by senior psychiatrists according to the DSM-5 (American Psychiatric Association, 2013). All patients were considered OCD treatment-resistant because they did not respond to at least 2 different SSRIs and to a CBT. Axis-1 screening was performed with the Mini-International Neuropsychiatric Interview (MINI), symptoms and severity of OCD were measured using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and the depressive symptoms were assessed with a Hamilton Depressive Rate Scale (HDRS). The exclusion criteria were: psychotic spectrum disorders, bipolar disorder, severe depression (HDRS>18).

Comorbid mild and moderate depression as well as anxious disorders are common in OCD patients, and we chose not to exclude those patients. For each patient, the age of onset, the time lapse before beginning an antidepressant or a psychotherapy, the pharmacological treatment history and the number of rTMS sessions received before the assessment were gathered.

Healthy controls (HC) were recruited from the general population. They were screened by a senior psychiatrist to exclude current or past psychiatric disorders using the MINI and the HDRS. Controls were matched with OCD patients for age (+/-5 years), gender and years of education.

This study was conducted in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans and was approved by the Committee for the protection of patients ("Comité de Protection des Personnes": CPP) of La Pitié Salpêtrière Hospital on March 2016. All patients signed a written consent to participate in this study after they have been given a complete description of the study.

Instruments

The patients performed the DNMS task and the DMS task using the PEBL software(83). In order to counteract an eventual order effect, the sequence of the two tests was systematically alternatively changed. Consequently, half of the subjects performed the tests in the following order: DNMS/DMS and the other half in the reverse order DMS/DNMS.

As far as the DNMS and DMS tests are concerned, we used the methodology of Elliott et al (71) that studied OFC activity in healthy subjects performing the DNMS and the DMS tasks. In both tasks, subjects were initially shown during one second a matrix filled with 16 red and yellow squares characterized as a complex and abstract visual stimulus. Then after a delay of 5 seconds, they were presented with two different matrices, one of which was the sample stimulus, identical to the first matrix presented. In the DNMS task, the subject was asked to choose the novel stimulus while in the DMS the subject was asked to choose the familiar stimulus (Figure 2). The subject had no time limit for choosing the correct stimulus related to the task. This task was repeated 30 times for every subject. For each subject, we have measured two main parameters; the number of correct answers and the response time during each trial. The subject had no time limit to answer questions. Before starting the recorded session, a test of five trials was done for every subject to check the understanding to the task

Statistical analysis

First, we measured parametric correlation (Pearson test) on sociodemographic data to compare continuous variables between OCD patients and HC. Then, Student's t tests were performed to compare the results to the DNMS and the DMS tasks between OCD patients and HC using two parameters: the number of correct answers and the response time. Subsequently, in order to find out the most specific task for OCD patients, we determined which task amongst DNMS and DMS appeared to be the most difficult for OCD patients. Finally, a bootstrapping method was used to confirm the previous results from the Student's t test. The bootstrapping method relies on random sampling with replacement. It is an appropriate way to control and check the robustness of the results on a sample size with less than 40 subjects(84).

We have performed the statistical analysis tests using RStudio software in its 3.5.0 version.

The threshold for statistical significance was set at p< 0.05.

Results

A total of 42 subjects entered the study. The final sample for analysis consisted of 40 subjects (95.24%) as one patient, severely depressed, was excluded (HDRS=22) and a healthy control (HC), treated by psychotropic medication for anxious and depressive symptoms, was also excluded. We included 20 OCD patients (mean age = 41 ± 8,9 years old; range = 27-59 years; mean education = 14 ± 2,5 years; mean age at onset = 17 ± 8,9 years old; mean YBOCS score = 29 ± 5,3) and 20 HC (mean age = 40 ± 9,1 years old; range = 29-56 years; mean education = 15 ± 3,8 years). Table 1 shows the demographic characteristics of both groups and the results of the correlation tests comparing OCD patients and HC. The OCD sample did not differ significantly from the control sample with respect to age (p=0,4) and education (p=0,4) as we can see in the Table 1.

In the OCD group, 13 patients had no comorbidities and only 5 of them had depressive symptoms at the HDRS. Most of the OCD patients have presented checking symptoms (feeling compelled to check -such as checking doors are locked or the gas is off) as the first dimension and washing symptoms (cleaning or hand-washing compulsions) as the second dimension, which is concordant with the literature cited in the introduction section. Except two patients, all the others have taken at least one antidepressant. In addition to an antidepressant, four patients have taken a benzodiazepine and seven have taken antipsychotic at the moment of assessment (Table 2).

The comparative analysis of performance in the DNMS the DMS tasks between OCD patients and HC using a Student t-test has proven to be statistically significant. As expected, OCD patients perform worse than HC for the DNMS task (t = -2.687, p = 0.010***) and for the DMS task (t = -2.089, p = 0.043*) in terms of correct answers. Otherwise we can observe that this difference between OCD patients and HC seems statistically stronger for the DNMS task than for the DMS task (Cohen's d 0.85 vs 0.66). Furthermore, the response time for OCD patients is greater than the response time for HC performing the DNMS task (t = 2.519, p = 0.016***,) and the DMS task (t = 2.332, p = 0.025**). Regarding the OCD patients only, there is a trend showing that they perform worse for the DNMS task than for the DMS task (Table 3).

We then decided to confirm this trend using a bootstrapping method with 100 permutations and replacement. The results for the bootstrap (mean DNMS task correct answers = 25.881, mean DMS task correct answers = 26.324, t = -4.593, df = 19) show that the trend becomes significant with a larger sample.

Finally, a multivariate linear regression was calculated to predict the OCD severity at the YBOCS based on the reaction time and the correct answers at the DNMS task. We found a negative correlation between the OCD severity at the YBOCS and the correct answers at the DNMS task (β = -1.56; p = 0.027*; SE = 0.65). No correlation was found between the OCD severity at the YBOCS and the reaction time at the DNMS task.

Our results are consistent with our hypothesis saying that OCD patients would be more impaired performing the DNMS task that the DMS task. We have also shown that the more severe a patient is at the YBOCS the less he will perform at the DNMS task.

Discussion

In this study, we compared the performances of OCD patients versus HC performing two neuropsychological tasks: the DNMS and DMS tasks. Our focus laid mainly on the performances for the DNMS task. This task was chosen for two main reasons ; 1. because previous studies, such as the one of Elliott et al. (18), have demonstrated that performing this task involves the lOFC and 2. because a dysfunction of the lOFC is associated with OCD. Our goal in this study was then twofold; first bringing some new evidence that lOFC activity is a biomarker of OCD and second, highlighting the DNMS could be a relevant task for studying OCD patients and monitoring the efficiency of treatments, particularly the ones involving noninvasive and invasive brain stimulation and pharmacological treatments, as they directly impact the OFC. First of all, our results confirm that OCD patients perform statistically worse than HC for the DNMS and the DMS tasks considering the number of correct answers and the response time. Then, using a t-test confirmed with a bootstrapping, we proved that OCD patients seem to be more impaired for the DNMS task than for the DMS task. Finally, we have also shown that the more severe a patient is at the YBOCS the less he will perform at the DNMS task. We then demonstrated that OCD patients take significantly more time to perform the tasks but they not only take significantly more time than HC, they also make more mistakes.

The two tasks tested, non-matching (DNMS) and matching (DMS) involve short-term memory processes and the execution of a choice response. In a previous neuroimaging study from Elliot et al. (71) the medial activation associated with the matching condition was explained in terms of a need to monitor the familiarity and associated reward value of stimuli. The lateral activation associated with non-matching, however, could be explained in terms of a crucial difference between the tasks at the choice stage. In adult humans, unlike children and animals, matching is a more natural process than non-matching(85); the instinctive response at the choice stage is to the familiar rather than the novel stimulus. Thus, making the choice in non-matching involves inhibiting an instinctively preferred response in order to make a correct one. Inhibition can be seen as a particular feature of making choices, especially in circumstances where an established or salient response may not always be appropriate. Such a role for lOFC is consistent with previous studies implicating the OFC in response inhibition tasks, such as the classic go-no-go tasks(86-88). Recently, the role of lOFC in response inhibition has been suggested in few animal studies examining neural correlates at the single-unit level(89). Considering the results of our study, we can conclude that OCD patients are characterized by a lack of inhibition, resulting from a dysfunction of the lOFC and leading them to have poorer performances in making the choice in non-matching comparing to healthy subjects. Our study then establishes DNMS as a relevant task to monitor the efficiency of OCD treatments.

However, other studies would be useful to support that these findings can be replicated or to assess whether our results are explained by the take of a psychotropic treatment in the OCD group. Indeed, one of the limitations of our study is that some of our patients were undergoing pharmacological treatment at the time of study. This is more representative of the general OCD population, but permits a possible confound when comparing with HC who are receiving no psychotropic medication, although treatment in our sample was heavily weighted toward SSRIs, found in the literature not to affect neurocognitive function(90). It could also be very interesting to replicate this study with a larger number of participants and a four-choices version of DNMS test, such as the one used in Martoni et al.'s study.

Method Data description

The research data in this paper is drawn from five main sources : Stimulation. We will use paired t-tests on SPM to replicate those results. Clusters of a minimum of 50 contiguous voxels, with a threshold of p < .005 were considered significantly different.

ORBITOC -rTMS ON versus rTMS OFF

In this pilot study, Nauczyciel et al. tried to assess the efficacy of low-frequency rTMS of the right OFC in OCD patients. The procedure was based on a randomized, double-blind, crossover design with two 1-week treatment periods (1 week of active stimulation and 1 week of sham stimulation), separated by a 1-month washout period. Statistical analysis between both groups was performed using the "compare-population one scan/subject" routine paired t-tests. Clusters of a minimum of 50 contiguous voxels, with a threshold of p < .005 were considered significantly different.

OCD Rennes versus HC Rennes

We also performed standard t-tests in OCD versus HC patients from Rennes hospital.

Machine learning

Machine learning algorithms were performed using Nilearn (version 0.8.1) to classify and predict the diagnosis of OCD. We merged the five cohorts PET acquisition to constitute a unique dataset with 78 OCD patients and 20 HC.

Then, we splitted it into a training and testing set, in a 70-30 ratio. Cross validation was performed on the training set to validate the model and tune the hyperparameters, using Random Search procedure. We chose to perform Stratified 10-Fold as the cross-validation procedure, Leave One Out (LOO) procedure having been highly debated, and even discouraged by G.

Varoquaux.

We As we have a huge number of features (p>>n), we also penalized our model, performing Ridge and LASSO logistic regression.

We used three performance metrics to evaluate our models: Receiver Operating Characteristic -Area Under Curve (ROC-AUC), F1-score and Cohen's Kappa. These metrics are particularly useful in binary classification with an imbalanced dataset, as they can correct the bias of overall accuracy.

Perhaps the most common metric in binary classification is ROC analysis and the associated use of the area under the ROC curve (AUC) to assess overall classification performance [Bradley, 1997]. AUC does not place more emphasis on one class over the other, so it is not biased against the minority class. In detail, ROC curve is a two-dimensional graph in which True Positive Rate (TPR) is plotted on the y-axis and False Positive Rate (FPR) is plotted on the x-axis.

The F1 score is the harmonic mean of the precision and recall. This metric is more interesting than accuracy in the case of imbalanced datasets as is not influenced by the True Negative Rate.

We want to minimize the False Negative Rate (better miscategorize 'OCD' in 'HC' group than the contrary).

Cohen's Kappa is often used as a measure of reliability between two raters for categorical items. In supervised machine learning, one "rater" reflects ground truth (the actual values of each instance to be classified), obtained from labeled data, and the other "rater" is the machine learning classifier used to perform the classification. Cohen's Kappa is a more robust measure than simple percent agreement calculation, as it takes into account the possibility of the agreement occurring by chance.

Results

Statistical Analysis

ORBITOC -DBS ON versus OFF Nauczyciel et al. found a decrease in the metabolism of the bilateral orbitofrontal lobes, with a more extensive decrease in the right side [citer]. However, in contrast to earlier findings, after re-analyzing data with the same statistical significance (p<.005), no evidence of hypermetabolism was detected.

STOC -rTMS ON versus OFF

We also tried to replicate the results found in Le Jeune et al.

[citer], but no increase in brain metabolism in OCD patients compared with HC was found. Thus, a clear benefit of DBS in the treatment of OCD symptoms could not be identified in this analysis.

Rennes OCD versus HC

No significant difference was found between OCD patients and HC.

Machine learning

As we have an imbalanced dataset (~ 80% of OCD patients), a naive classifier based on the most-frequent class will predict 8 times out of 10 'OCD'. The Dummy classifier we built has a ROC-AUC score of xxx and a F1-Score of 0.76.

Interestingly, the SVC-L1 model was found to perform the best in the prediction of OCD (ROC-AUC: F1-Score: 0.92, Cohen's Kappa: 0.60). Least absolute shrinkage and selection operator (LASSO) performs feature selection and regularization in order to enhance the prediction accuracy and interpretability of the resulting statistical model.

The results, as shown in Figure 1, indicate that SVC-L1 and Logistic Regression perform the best among all models according to ROC-AUC and F1-Score.

Discussion

After

Psychotherapy and Pharmacotherapy in OCD

If untreated, OCD becomes a chronic condition with a 20% remission rate. However, about 40% of patients who develop OCD in childhood will experience remission during early adulthood. First-line treatments, include medication using inhibiting presynaptic reuptake of serotonin (SSRIs) and cognitive behavioural therapy (CBT)(94).

Psychotherapy

CBT for OCD involves assisting patients to change their ideas or patterns related to obsessive thoughts and compulsions. CBT is a set of techniques that are used to help people with psychological disorders modify maladaptive patterns of thinking and acting to alleviate emotional symptoms(95). Components of CBT for OCD include: education, cognitive therapy techniques, exposure therapy and response prevention (EXRP)(96).

Pharmacotherapy

OCD medications are composed of tricyclic antidepressants (TCA), selective serotonin reuptake inhibitors (SSRIs), and serotonin-norepinephrine reuptake inhibitors (SNRIs)(97).

Clomipramine is the only TCA used for OCD(98).

Available SSRIs include fluoxetine, fluvoxamine, paroxetine and sertraline. For routine practice, it is challenging to predict which patients will respond effectively to a pharmacological treatment and which will not.

Neuroimaging markers of OCD

Neuroimaging studies have provided crucial information for a better understanding of the neurobiology of OCD. Structural imaging studies have reported neuroanatomical abnormalities in cortico-subcortico-thalamic circuits (CSTC) in these patients (36)

Contribution of OFC and ACC to pathophysiology and symptoms of OCD patients

The ACC and the OFC are now considered among the potential therapeutic targets in OCD. Frequently studied in animal models and humans, these two targets have been attributed multiple roles in cognition and behaviour, however their precise function remains to be understood. A fact for which there is agreement is that the OFC is an important node of the decision-making network(117). More specifically, this region would encode the estimated and expected value of different alternatives in a choice, impacting motivation processes and brain systems involved in decision-making. Furthermore, a fMRI study in healthy volunteers suggests that the OFC encodes subjective the personal preferences that guide our choices(118). Value attribution that represents the potential benefits and costs of a choice is intimately linked to reward prediction(119). The brain systems involving decision, uncertainty, motivation, reward and punishment are strongly linked and interact profusely. Interestingly, such cognitive processes have been found impaired in OCD, a condition that is ultimately being considered to target the decision-making cognitive processes and their anatomo-functional correlates. Indeed, OCD patients tend to show inappropriate preferences for unreasonable or undesired choices.

Additionally, they make cognitive and behavioural choices even if the attribute value to the act is not optimal, or the price to pay is too costly.

Since they experience the costs of alternative behaviours as exaggerated, OCD patients overestimate both, their risk, and their own responsibility when making/taking a decision. In accordance with this cognitive bias for the prediction of potential negative values, they consistently try to avoid unsubstantial dangers a process that has been shown associated to ACC activity(120). An important idea is that like for presumed obsession and compulsion reinforcers, brain valuation is subjective and its acquisition strongly depends on social context, education and beliefs. Functional MRI studies on OCD patients during performance of cognitive tasks show abnormal recruitment of CSTC circuits arguing functional and anatomical abnormalities in OCD pathophysiology. The OFC sustains an important functional connectivity with ACC impacting limbic CSTC loops. Consistent with brain valuation and decision-making system, the ACC plays a role in effort representation, defined as the potential cost of a given choice, modulating emotional and sensory information.

OCD patients also experiment premonitory urges for action before having their symptoms sensing an uncomfortable feeling of distress, and an internal impression of wrongness. This symptom could further strengthen links with the ACC, which has been found involved in pain processing and performance-error monitoring(121). A neuroimaging study by Agam and colleagues interested in neural responses to errors in OCD diagnosed population, they examined post-error changes in default mode network activity and showed that patients had an increase of the activation of the default network while controls had a decline(122). The ACC region is particularly coupled to the insula, which is also known to represent subjective interception sensations(123). Converging evidence from imaging studies points to these same two structures concerning the 'urge-for-action' and their specific activation just before letting go a tic in Tourette syndrome (TS) patients(124). Moreover, a comprehensive Activation Likelihood Estimation (ALE) meta-analysis in search of circuits involved in an urge to yawn, swallow, cough and urinate, identified these same two regions(125).

It could be incurred into the risk to simplify the anatomical basis of complex decision processes by arguing that the OFC encodes positive estimations, while the ACC encodes negative ones. Nonetheless, non-human primate studies, argue that ACC-neurons signal both Here, it is hypothesized that in OCD, the dysregulation of the ACC results in an inability to adequately assign control to the appropriate brain system, responsible for ambivalent preferences and action selection, causing overload and discomfort. For this reason, showing a lack of behavioural flexibility, OCD patients would sustain, stereotyped repetitive behaviour, despite its overt negative consequences. In regard to this, lesion studies in non-human primates with OFC and ACC damage showed unable to adapt to modified instructions whereas likewise, human fMRI studies highlighted an important role for the OFC in rapid reversal learning(129).

A recent study reported the activation of common brain areas while inhibiting an ongoing or an intended action(130), suggesting that behavioural inflexibility and decisional inflexibility, both displayed by OCD patients, go hand in hand. When a change occurs, the valuation network reviews the competing values of the different alternatives, a process impaired in this pathology.

On the other hand, perseveration in unreasonable choices can drive plastic brain changes during postnatal development or in adulthood strengthening abnormal connectivity patterns and reinforcing dysfunctional circuits. As it is, the case for Tourette Syndrome, patients, reorganization processes could be facilitated with the release of activity-dependent dopamine(131). Connections underlying unwanted thoughts and actions can be strengthened via habit learning, via the basal ganglia, setting into motion a vicious circle. OCD patients repeat and learn abnormal decision-making schemes and derived behaviours, the same way a musician learns to play a music score or a golfer learns to adjusts his/her gestures. Furthermore, obsession generates anxiety and anxiety drives compulsion, and the compulsion is the repetition leading OCD symptoms to increase in frequency and duration.

Conclusion

Invasive and non-invasive brain stimulation have greatly contributed to a better understanding of the neural mechanisms subtending OCD and more recently have emphasized a role for the OFC and the ACC. From a larger perspective, we here suggest that all cortical targets probed with different neurostimulation modalities (STN, DLPFC, Pre-SMA, ACC and OFC) are part of wider complex network subtending some of the cognitive and behavioural abnormalities shown by OCD patients and in particular, decision making abilities. These targets, organized in cortico-subcortical loops linking prefrontal cortical areas and subcortical structures via the basal ganglia are defined by the local and interregional functional interactions contributing to abnormal decision making in a task dependent manner. They reinforce the hypothesis of a dysfunction of the orbital-subcortical loop in OCD. The described structures are surely not the only regions implicated in involuntary thoughts and actions. Premotor and parietal cortices participate to awareness of the intention to act and guide preparatory processes(132). However, it remains unclear if OCD is characterized by an abnormal hypoexcitable or hyper-excitable ACC and OFC targets, questioning the rational for using low frequency rTMS in such condition. The idea of excitatory (high frequency) vs. inhibitory (low frequency) rTMS stimulation might be oversimplified. High frequency stimulation may also disrupt neural activity, and has occasionally shown as even be more effective to induce longterm clinical effects(133).

Animal and neuropsychological studies have indicated that OFC and ACC are involved in cognitive processes such as decision-making, reinforcement learning and action-selection, main cognitive functions that are altered in patients with OCD. Here, it is postulated, that a dysfunction of these areas could explain for many of the clinical symptoms presented by patients, beyond classical obsessions and compulsions. Indeed, following the alleviation of obsessions, many patients report residual symptoms such as a feeling of persistent indecision and incompleteness described by Janet as "psychasthenia"(134). Moreover, cognitive difficulties in OCD could be related to a lack of motivation caused by a dysfunctional ACC. On that basis, we could speculate that stimulating the ACC may improve well characterized OCD symptoms such as slowness and retardation to act, dimensions which are not frequently taken into account in OCD treatment. On the other hand, targeting the OFC using low frequency could alleviate obsessive thoughts and involuntary thoughts. Both approaches might prove complementary and contribute jointly to improve clinical manifestations in OCD.

In this context, effectively treating such a complex condition, requires to identify and probe via neurostimulation approaches the most anatomically accessible and functionally malleable node or nodes within the decision-making network that could help up set up the system in physiological balance, allowing sound cognitive processing and adaptive behaviour.

Importantly, the heterogeneity of symptom dimensions already stressed in previous studies(135) subserved by distinct anatomical nodes and networks, needs to be taken into account. In spite of sharing symptoms that allows them to be classified as suffering the same condition, not all OCD patients, will show dysfunctional activity patterns in the same frontal lobe nodes, hence require different neuromodulation strategies (technologies, targets, montages, stimulation parameters). In this regard, OCD patients might differ either qualitatively (which network nodes are impaired and which ones spared) and quantitatively (which magnitude of dysfunction operates on each node). Diagnostic individualization and therapeutic customization might be required to achieve meaningful clinical success. Being able to define subtypes of patients, as 'biotypes' like recently done for other conditions like depression(136) might be a first step to fine-tune the 'where' or 'wheres' of future neuromodulation therapeutic strategies.

Plain language summary

Deep brain stimulation (DBS) is an approved effective therapy for patients suffering from treatment resistant obsessive-compulsive disorder (OCD). Here, we report the case of a middleaged man with nearly a decade long history of treatment refractory OCD who in the context of a double-blind randomized study underwent bilateral implantation of DBS leads in the ventral striatum/ventral capsule (VS/VC) region. After 3 months of DBS stimulation, the patient showed a dramatic drop of OCD severity score and became stable and asymptomatic. Yet, investigators found out the battery of the stimulator had emptied completely, and brain stimulation had inadvertently turned off. Importantly the patient remained symptom-free for an additional year, in absence of any effective DBS treatment.

Background

Obsessive-compulsive disorder (OCD) is a widespread chronic neuropsychiatric disease characterized by recurrent intrusive thoughts, images, or urges (obsessions) that typically cause anxiety or distress. It is also associated with repetitive mental or behavioral acts (compulsions) that patients feel an urge to perform. OCD is considered the 4th most common mental disorder in developed countries and according to the World Health Organization (WHO) represents the 10 th leading cause of disability (3). Effective treatments for OCD include cognitive behavioral therapy (CBT) and serotonin reuptake inhibitors. Even when optimal treatment is provided, 10% of patients remain severely affected with treatment-resistant OCD (110). For the latter, deep brain stimulation (DBS) is the last available therapeutic option. Although the number of severe OCD treatment-resistant patients treated with DBS is still low, and optimal targeting and stimulation parameters are still under debate, most studies (50) confirm that DBS constitutes an adequate treatment, with an acceptable profile of adverse effects and a global percentage of Y-BOCS reduction estimated at 45% and a global percentage of responders of 60%. The circuits connecting the orbitofrontal cortex (OFC) (65,66), the medial prefrontal cortex (mPFC), the basal ganglia and the thalamus are thought to be central to the pathophysiology and therapeutic response in OCD [START_REF] Millet | Obsessive Compulsive Disorder Networks: Positron Emission Tomography and Neuropsychology Provide New Insights. Soriano-Mas C, éditeur[END_REF]143). A widely accepted hypothesis is that the symptoms characterizing this condition are caused by an abnormally high-degree of hyperactivity in a cortico-striato-pallidal-thalamo-cortical (CSPTC) network (144,145), which could be plausibly inhibited or functionally overridden with high-frequency DBS electrical patterns (65,146,147). To achieve the latter goal, DBS systems include 3 main components: An Implanted Pulse Generator (IPG), an intracranially implanted multielectrode lead with several contacts (or electrodes) along its bottom end, and a connection/extension cable linking the latter to the former. Electrical impulses are generated by the IPG, which is supplied in electricity by an-embedded battery. This device is surgically implanted in the patient's chest subcutaneously.

Deep brain stimulation

An extension cable running under the skin of the neck and the scalp, from the IPG through a burr hole in the skull, connects to the lead which is implanted neuro-surgically in a specific brain subcortical structure, such as the subthalamic nucleus (STN) or the ventral striatum/ventral capsule (VS/VC) region (see Figure 1

Case-report

In 2007, a middle-aged man employed as a boilermaker was admitted into the hospital (Hôpital Pitié-Salpêtrière, Psychiatry Department, in Paris, France) following a work-related accident. His jacket caught fire whilst he was welding a metal piece. The patient was severely burned and underwent a skin grafting intervention. Following this accident, the patient developed typical OCD symptoms according to the DSM-IV, with washing rituals, repetitive verifications and fear of being contaminated. In 2011, his symptomatology started to increase in duration, impacting insidiously his life for ~7 hours a day. In an attempt to control his symptoms, the patient was treated serially with a monotherapy of fluoxetine (80 mg/day), then venlafaxine (375 mg/day) and ultimately clomipramine (225 mg/day). Nonetheless the pharmacological treatment failed to yield any sign of clinical improvement. During this period, cognitive-behavioral therapy was also carried out unsuccessfully.

In 2012, the patient attempted suicide by voluntary drug poisoning. This event was explained by occupational inactivity, a serious degradation of his quality of life caused by severe OCD symptoms and an increase in alcohol consumption. At this time, new pharmacological therapies were attempted with a lower dose of risperidone (3 mg/day), aripiprazole (15 mg/day) and quetiapine (400 mg/day), once more, without clinical success.

Subsequently, in 2015, a non-invasive transcranial brain neuromodulation treatment was also assayed via a regime of 20 daily sessions of repetitive Transcranial Magnetic Stimulation (rTMS), delivering low frequency patterns (1 Hz, intensity set at 120 % of his resting motor threshold, for 20 minutes, 1200 pulses per session) targeting the orbito-frontal cortex(150).

Nonetheless, no major improvement was noticed either. Indeed, it should be noted that in spite of the treatments applied from 2007 to 2016, the patient's Y-BOCS remained relatively stable at high severity scores between 21 and 28 (out of a total of 40 points), a fact that attests the enduring and long-lasting nature of his OCD symptoms.

In Prior to DBS onset, by the end of the period that followed lead implantation, the patient's Y-BOCS score remained severely affected (Y-BOCS score of 22). Nonetheless, 3 months after the theoretical onset of DBS using the final set of fixed parameters reported above, the patient no longer complained of OCD symptoms and his Y-BOCS fell down to a score of 3. Clinically, he seemed soothed and did not feel anymore the urge for washing rituals, neither reported experiencing an insidious sense of contamination risk. The patient was euthymic, his personal interactive relationship skills had greatly improved and he no longer consumed alcohol.

Attesting such dramatic improvements, the patient even planned to resume his professional activity. Consequently, follow up appointments were gradually spaced out and 9 months postlead implantation (hence after 6 months of DBS treatment), the patient was asymptomatic and stable, still with a low Y-BOCS score of 3. Nonetheless, at this time, during a routine check, the psychiatrist in charge of the study unexpectedly found out that the IPG was no longer operative because the battery had depleted completely long before. Unfortunately, we were unable to determine for how long the battery might have been depleted by interrogating the IPG unit. The study blind was lifted and investigators learned that the patient turned out to have been randomized to the VS/VC bilateral stimulation condition and treated with the last set of above-reported parameters. In absence of any specific complaint, and given the outstanding patient's recovery with consistent low Y-BOCS scores, in agreement with the patient, we decided not to replace the IPG. This decision was taken because it seemed unreasonable to operate the patient again considering: (1) the risk of infection or hemorrhage; (2) the risk of the anesthesia associated to the surgical procedure; (3) the risk of causing additional micro-lesions during implant removal; and (4) the risk of a recrudescence of OCD symptoms.

More regular medical consultations were however scheduled on a monthly basis, to follow the evolution of such an unexpected case. In January 2019, after a 12-months follow-up (Figure 3), the patient remained still stable and asymptomatic with a low Y-BOCS score of 7.

Discussion

To the best of our knowledge, this is the first reported clinical case presenting evidence Additionally, it suggests that DBS placebo effects as those here hypothesized, may have boosted the impact of a short-lasting DBS protocol, extending its effects over very long periods of time, once stimulation was inadvertently discontinued due to battery depletion.

We here conclude that placebo effects could play a role either inducing and/or ensuring the maintenance of attained recovery levels in treatment-refractory OCD patients.

On such basis, and as suggested by the outcomes of a meta-analysis by Schruers et al.

(156), it is paramount to rule out unexpected placebo improvements, when assessing the outcomes of randomized clinical DBS trials in OCD populations. It is however important to emphasize that several facts curtail our ability to fully confirm these explanatory hypotheses.

First, even if unlikely given the enduring and chronic nature of OCD symptoms in our patient, Certain common themes also called "symptom dimensions" have been described. These include cleaning, need for symmetry, counting compulsions, forbidden or taboo thoughts (aggressive, sexual, or religious obsessions and related compulsions) and harm (to self or others) [START_REF] Millet | Phenomenological and comorbid features associated in obsessive-compulsive disorder : Influence of age of onset[END_REF]. Over time, compulsions can become so time consuming (> 1 h/day) or onerous that they engender anxiety themselves. Indeed, these symptoms produce profound distress and most frequently interfere heavily with daily functioning.

70% of patients experience significant symptomatic relief with appropriate pharmacotherapy such as selective serotonin reuptake inhibitors (SSRIs) associated with cognitive and behavioral therapies (CBT), but it remains a critical clinical challenge for 30% of OCD patients (Insel et al., 1985).

Over the last decades, published papers have multiplied in the field of OCD in order to increase our understanding of clinical symptoms and brain regions involved in obsessive-compulsive symptoms.

Early cognitive psychology studies attempted to describe cognitive-behavioral models using neurocognitive tasks which assess specific cognitive processes. It has been reported an impairment in executive and selective functions, nonverbal memory, and visuospatial abilities [START_REF] Aycicegi | Neuropsychological function in obsessive-compulsive disorder : Effects of comorbid conditions on task performance[END_REF][START_REF] Kashyap | Neuropsychological functioning in obsessive-compulsive disorder : Are executive functions the key deficit?[END_REF]. The coupling of these tasks with neuroimaging showed functional alterations correlated to the affected cognitive functions. As an example, an inoperative response inhibition was evidenced by significant differences in the go/no-go task between OCD patients and healthy controls. It was therefore hypothesized that OCD may be characterized by a deficit in the suppressing motor output which would lead to more failed inhibitions on no-go trials. Furthermore, Buchsbaum et al. published in a meta-analysis that hyperactivity of the right inferior frontal gyrus has been consistently associated with no-go trials [START_REF] Buchsbaum | Meta-analysis of neuroimaging studies of the Wisconsin Card-Sorting task and component processes[END_REF]. In the same vein, Gruner and Pittenger have recently described an incapacity to switch properly between two different tasks in patients suffering from OCD [START_REF] Gruner | Cognitive inflexibility in Obsessive-Compulsive Disorder[END_REF]. This impairment in task switching is also observed when the reward/punishment contingencies are reversed. The authors suggest that this inflexibility could explain obsessions but also compulsions. This assumption is supported by neuroimaging data which shows a reduced recruitment of both dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC) regions when OCD patients switch cognitives sets, as well as when they reverse reward contingencies.

Subsequently authors aimed to investigate the relationship between clinical symptoms and brain activations in OCD patients. For this reason, they used provocation tasks to highlight neuroimaging and/or cognitive processes related to OCD symptoms [START_REF] Shapira | Brain activation by disgust-inducing pictures in obsessivecompulsive disorder[END_REF][START_REF] Toffolo | Check, check, double check : Investigating memory deterioration within multiple sessions of repeated checking[END_REF]. These provocation tasks consist in exposing the patient to stimuli related to their symptom dimensions in order to trigger brain obsessive-compulsive mechanisms. For example, in a study by Nakao et Based on these discoveries, new treatments and brain therapeutic targets have been proposed. The orbitofrontal cortex (OFC) has been described as a target for transcranial magnetic stimulation (TMS) (Nauczyciel et al., 2014) and the subthalamic nucleus a promising target in deep brain stimulation (DBS) (Mallet et al., 2008). Furthermore, since the cortico-striatal-thalamic loop (CSTS) plays a key role in OCD symptoms, low-dose of dopaminergic antagonists are used as an add-on of antidepressants. [START_REF] Denys | The role of dopamine in obsessive-compulsive disorder : Preclinical and clinical evidence[END_REF]. However, the effectiveness of OCD treatments remains partial and this can be explained by an inadequacy between brain therapeutic targets and brain regions involved in OCD patients. This could be explained by constraints in experimental designs developed so far by researchers. Whereas neurocognitive tasks explore specific cognitive processes, mainly cortical regions nonspecific of OCD patients [START_REF] Poldrack | Mapping Mental Function to Brain Structure : How Can Cognitive Neuroimaging Succeed[END_REF], [START_REF] Millan | Cognitive dysfunction in psychiatric disorders : Characteristics, causes and the quest for improved therapy[END_REF], provocation tasks measure only the symptom dimensions according to patients' complaints. One could also argue that MRI data suffers from a poor temporal resolution making it difficult to capture brain patterns underlying OCD [START_REF] Kim | Limitations of temporal resolution in functional MRI[END_REF].

Here, our team proposed a shifted paradigm using four metacognition tasks. Unlike cognitive and provocation tasks, these genuine tasks were not intended to measure OCD symptoms or cognitive impairment but explore "beyond" symptoms and cognitions as "meta" etymologically means.

The first objective was to compare the results of OCD patients and healthy control (HCs) performing four metacognition tasks in terms of number of good answers and reaction time.

The second objective was to compare visual strategies employed by OCD patients and HCs to decode the four metacognition tasks using an eye-tracking

The third objective was to compare electroencephalographic (EEG) signal in OCD patients and HCs during resting-state and the four metacognition tasks.

METHODS

Study design

This study is a single-blind, non-randomised, two-arm trial comparing the performance of An information leaflet and consent form were read and signed by the participants. The study population is divided into 2 arms: a control arm (healthy subjects) and an experimental arm (OCD patients). This is an observational study; no treatment is administered. It is an analytical study because it is an attempt to test a hypothesis and to establish causal relationships between the variables.

Population

All subjects were French native speakers, and they were asked if they liked chess, art, movies and if they spoke Tamil, Chinese, Russian or Arabic. Moreover, they were questioned about their laterality, their medication if there was and their visual abilities. It was ensured that no visual impairment would be the cause of the variations in results and that all subjects were righthanded. Participants had no medical history of neurological disorders. Plus, subjects were also asked about their psychiatric history and socio-demographic status. The diagnostic criteria of OCD is based on the DSM V criteria. Exclusion criteria for control subjects' group and OCD group included a history of other neurologic or major psychiatric disorders and systemic diseases that may affect cognitive functions. Control group includes participants without any psychiatric disorder. Therapies were not a cause for exclusion.

Prior to the experiment, all participants had to respond to an auto-questionnaire including a consent, medical history and treatments, in addition to a set of standardised questionnaires depending on their status (healthy, OCD, or other mental diseases). The questionnaire includes the Prodromal Questionnaire (PQ18), Yale-Brown Obsessive Compulsive Scale (Y-BOCS), the Mini International Neuropsychiatric Interview. (MINI), the Hospital Anxiety and Depression scale (HAD), the Brown Assessment of Beliefs Scale (BABS), the Clinical Global Impression (CGI), the EuroQuality of life-5 Dimensions-5 levels (EQ5D5L) and the Self-Esteem Rating Scale (SERS).

The local ethical committee (Comité de Protection des Personnes 'CPP Ile de France V', approval no) approved the study. All sections of the experiment were performed in accordance with relevant guidelines and regulations. All participants provided written informed consent.

Procedure

Patients with symptoms of obsessive-compulsive disorder, schizophrenia, bipolar disorder, depression, substance use disorder with a follow-up at the Pitié-salpêtrière hospital, as well as healthy subjects are informed about the study. After receiving a full explanation of the study, interested patients are asked to sign the informed consent form. The clinician then formally checks whether the conditions of the study are met and determines the patient's eligibility. All participants are first asked to fill in a redcap form, which provides information on the characteristics of the population. Subjects do not have their phones or any other electronic devices in the Faraday cage when the experiment starts.

General conditions for data acquisition

Participants sit in front of the screen and perform the tasks using a trackpad, at a distance of 65cm +/-5cm from the eyes to the screen, inside an electromagnetically ally shielded room (Faraday cage). The stimuli were presented on a black background on a 1920 x 1080-pixel wide screen. The temperature and brightness had to be the same for each participant.

All tasks were coded by the laboratory team, using PsychoPy® under Python 3.6.

PsychoPy® is an open-source software for conducting experiments in Python. PsychoPy® offers scientists a free and simple software for presenting and controlling stimuli. It is used by many laboratories around the world for psychophysics, cognitive neuroscience and experimental psychology.

Before each task, the instructions are explained to the subject. The tasks are performed in the following order: 7 differences, Lucifer, Where is Tockie? and Symmetry. All participants of the psychological experiment underwent an eye tracker recording during the tasks. The device was discretely set under the screen, not wearable, and the participant's head was not fixed.

Cognitive tasks

The 4 tasks we have designed are intended to exacerbate the filtering defect that probably exists in OCD subjects. They are indeed expected to perform better.

Seven differences

This is the seven differences task: two images that are identical at first sight are shown at the same time. The subject is asked to indicate via a trackpad whether he or she sees 0, 1, 2 or 3 or more differences.

At the end of the experiment, for each type of image, the question of the number of differences will be asked a total of 5 times. Each time the number of differences, between 0 and 6, changes.

Within the same type of image, the differences are never the same. There were 4 different types

B) Lucifer

The subject is presented with images of matches spread in an organised or random manner on a black background for a period of 2 seconds. There are 3 types of images: messy (Figure 2 In this task, a series of more or less complex images are presented to the subject for 3 seconds.

After each image, questions relative to the image are asked and two choices of answers are given. The questions concern the presence or absence of objects and their quantity in the image.

There is no time limit for answering. The particularity of this task is that it offers subjects the possibility of reviewing the image as many times as they wish and thus modifying their answers.

The task is not a directly provocative task, nor does it explore a specific cognitive function in a way that it is a simple and repeated task. In fact, the choice and the design of this task unfolds in two major steps. Firstly, the participant explores a visual stimulus and each information within the stimulus enters the consciousness of the participant with different weight. Secondly, the participant may or may not verify his answers. The verification is a common trait in OCD patients, and we expect that OCD group verify more than the healthy control consistently with the literature. Besides, we expect this step to give us valuable information regarding the process and the integration of a stimulus through eye tracker data.

Symmetry (Figure 4.a,b)

In this task, the visual stimulus is the appearance of two black bars on a white screen. The bars, placed randomly on the screen, are either parallel or not parallel. The subject is asked to press « True » is he thinks they are parallel and « False » otherwise. Again, no specific cognitive function is specifically triggered, the task is simple and the same question is asked. We expect the OCD group to perform better at distinguishing slight differences between bars in a neutral environment.

Statistical analysis

"First, we measured parametric correlation (Pearson test) on sociodemographic data to compare continuous variables between OCD patients and HC. Finally, a bootstrapping method was used to confirm the previous results from the student's t-test. [The bootstrapping method relies on random sampling with replacement. It is an appropriate way to control and check the robustness of the results on a sample size with <40 subjects]. We have performed statistical analysis tests using Python 3. The threshold for statistical significance was set at p < 0.05."

The independent variables observed or measured on the individuals of this statistical population are the success rate as well as the reaction time for each group (control subjects vs. OCD subjects) and for the 4 tasks and their subcategories: the shocking-non-shocking-calligraphychess blocks for 7 differences as well as straight-messy-special for lucifer.

For the 7 differences task, an additional independent variable is the difference between the response given by the subject and the expected response, for each group (control-OCT) and for each block of the task.

For the Where is Tockie? task, three additional independent variables are observed: the number of times each image is reviewed, the maximum number of times each image is reviewed, and the ratio of successes to the number of times an image is viewed on average.

The data collected will be used to describe the 2 cohorts: the control group and the OCD group.

Variables will include socio-demographic parameters, and OCD parameters such as duration, psychiatric comorbidities, pre-morbid disorders and co-prescriptions. Missing data are not replaced by imputation methods.

Initial basic analyses of these data, which follow a normal distribution, involve calculating the mean of these results for each group (control-OCD) and for each task.

Here, for each type of data, a comparison is made of two means from two normal distributions with equal and unknown variances. A Student's t test is therefore carried out for each measure between the two control-OCT groups to attest to their significance. The differences in means are considered significant for a p-value <0.05, the threshold at which the null hypothesis is rejected.

DISCUSSION

If the results obtained are consistent with those expected, this would constitute an argument in favour of a deficiency in information filtering.

Pilot subjects perform cognitive tasks without eye-tracker and without EEG headset. It might be interesting to compare their results with those of the study population to see if there is a difference in performance.

Concerning the picture counting, it is important to mention that the configuration of the task, from a logistical point of view, may lead to asking to review the picture. A lack of inhibition from the OCD group might provoke a high image counting, but some work has shown that this hypothesis is not valid.

We can wonder what kind of cognitive functions other than filtering information would be more relevant to study in the OCD patients.

The second hypothesis consists on the fact that by identifying common neural patterns involved in OCD using quantitative EEG (QEEG)during cognitive tasks, may not only shed light on our understanding of the physiopathological pathways behind this disorder, but one can also use these same biomarkers as an entry point for a wider therapeutic panel, such as neurofeedback therapy.

• "We believe that just like other psychiatric disorders, OCD faces one significant challenge which is to juggle between the concept of a standardized medicine that has proven its efficiency but has its flaws and is still subject to debate particularly in psychiatry; and a personalized medicine by finding biomarkers for several disorders using a variety of brain imaging techniques. In fact, it has been demonstrated that EEG biomarkers added to standard diagnostic procedures can increase the diagnostic accuracy in other psychiatric disorders (Snyder et al, 2015). All these elements should encourage researchers to rethink their way of apprehending this disorder. As a matter of fact, a less « DSM-dependent » and a more neurophysiological approach may be needed."

• "We believe that just like other psychiatric disorders, OCD faces one significant challenge which is to juggle between the concept of a standardized medicine that has proven its efficiency but has its flaws and is still subject to debate particularly in psychiatry; and a personalized medicine by finding biomarkers for several disorders using a variety of brain imaging techniques. In fact, it has been demonstrated that EEG biomarkers added to standard diagnostic procedures can increase the diagnostic accuracy in other psychiatric disorders (Snyder et al, 2015). All these elements should encourage researchers to rethink their way of apprehending this disorder. As a matter of fact, a less « DSM-dependant » and a more neurophysiological approach may be needed." The next steps of our research consists on identifying common neural patterns involved in OCD using quantitative EEG (QEEG) during these cognitive tasks, may not only shed light on our understanding of the physiopathological pathways behind this disorder, but one can also use these same biomarkers as an entry point for a wider therapeutic panels, such as neurofeedback therapy.

• the fact that standardised cognitive tests were not carried out beforehand might be a limit

• Symmetry : are OCD better at distinguishing slight differences between some meaningless angles as they would do in their own environment ?

• WIT : review image to "re-check" or because of dysfunctional short term memory

• Concerning the picture counting, it is important to mention that the configuration of the task, from a logistical point of view, may lead to asking to review the picture. A lack of inhibition from the OCD group might provoke a high image counting, but some work has shown that this hypothesis is not valid. (1)

GENERAL DISCUSSION

Overview of main results

Progress in the neurobiology of OCD

The current review presents a synthesis of the current knowledge and a curated selection of literature on the genetic, neurochemical, neuroanatomical and cognitive underpinnings characterizing the physiopathology of this neuropsychiatric condition in humans. A special emphasis is placed to summarize the most popular animal OCD models and to analyze their potential and limitation in enriching our understanding of this condition. On the latter basis we review the operational principles, mechanism of action, feasibility and success rate of current OCD therapies by means of pharmacology, psychotherapy and deep brain stimulation. We conclude that a combination of exploratory and therapeutic studies developed in animal OCD models and human OCD patients will be necessary to improve the diagnosis, prognosis and ultimately the care of OCD patients. We also advocate for patient-customized therapeutic solutions based on a rich palette of predictive biomarkers (for severity, prognosis, treatment efficacy) and also therapeutic solutions operating simultaneously on multiple correlates of mental function (neurochemistry, local and network hemodynamic and electrophysiological activity, cognition and behaviors).

DNMS task in OCD

In this study, we compared the performances of OCD patients versus HC performing two neuropsychological tasks: the DNMS and DMS tasks. Our goal in this study was then twofold; first bringing some new evidence that lOFC activity is a biomarker of OCD and second, highlighting the DNMS could be a relevant task for studying OCD patients and monitoring the efficiency of treatments, particularly the ones involving non-invasive and invasive brain stimulation and pharmacological treatments, as they directly impact the OFC. First of all, our results confirm that OCD patients perform statistically worse than HC for the DNMS and the DMS tasks considering the number of correct answers and the response time. Then, using a ttest confirmed with a bootstrapping, we proved that OCD patients seem to be more impaired for the DNMS task than for the DMS task. Finally, we have also shown that the more severe a patient is at the YBOCS the less he will perform at the DNMS task.

The two tasks tested, non-matching (DNMS) and matching (DMS) involve short-term memory processes and the execution of a choice response. The lateral activation associated with non-matching, however, could be explained in terms of a crucial difference between the tasks at the choice stage. In adult humans, unlike children and animals, matching is a more natural process than non-matching(85); the instinctive response at the choice stage is to the familiar rather than the novel stimulus. Thus, making the choice in non-matching involves inhibiting an instinctively preferred response in order to make a correct one. Inhibition can be seen as a particular feature of making choices, especially in circumstances where an established or salient response may not always be appropriate. Considering the results of our study, we can conclude that OCD patients are characterized by a lack of inhibition, resulting from a dysfunction of the lOFC and leading them to have poorer performances in making the choice in non-matching comparing to healthy subjects. Our study then establishes DNMS as a relevant task to monitor the efficiency of OCD treatments.

However, other studies would be useful to support that these findings can be replicated or to assess whether our results are explained by the take of a psychotropic treatment in the OCD group. Indeed, one of the limitations of our study is that some of our patients were undergoing pharmacological treatment at the time of study. This is more representative of the general OCD population, but permits a possible confound when comparing with HC who are receiving no psychotropic medication, although treatment in our sample was heavily weighted toward SSRIs, found in the literature not to affect neurocognitive function(90).

Machine learning applied to PET imaging in OCD

After reanalyzing the PET data published in Nauczyciel et al. and Le Jeune et al., we were unable to reproduce the results found by replicating the methods used. This therefore raises a more global problem. Are the old published results still valid today? The question arises today, with increasingly efficient statistical analysis algorithms, and demanding in terms of data quality but also with the advent of new analysis methods including machine and deep learning methods. More than 30, 000 papers have been published in PET brain imaging from various specialities (oncology, neurology, psychiatry). There are many sources of variability in PET data and unfortunately, the steps chosen in the preprocessing pipeline can be one of these variables. There isn't a consensus on which preprocessing strategy is the best to be applied to PET data. Therefore, if there isn't even a consensus on the preprocessing strategies used to preprocess PET data, how can we establish if PET is reliable or not? (Eklund et al. 2016, Aurich et al. 2015).

In this paper, we developed an open-source PET pipeline analysis in Python using machine learning techniques, which can be forked on GitHub. To do so, we chose Nilearn (version 0.8.) which implements scikit-learn algorithms so makes it easy to use many advanced machinelearning, pattern recognition and multivariate statistical techniques on neuroimaging data. This paper lays the foundation stone in the standardization of the PET image processing methodology.

Non-invasive stimulation technique in OCD

The use of invasive and non-invasive brain stimulation and neuromodulation technologies combined with neuroimaging approaches can help refine with causal evidence our physiopathological understanding of the obsessive-compulsive disorder (OCD). Two key structures, the Orbitofrontal Cortex (OFC) and the Anterior Cingulate Cortex (ACC) have been found dysfunctional in OCD compared to healthy volunteers and on such basis have been tested

as therapeutic targets for invasive and non-invasive neuromodulation therapy. Hereinafter, evidence addressing the cognitive processes subtended by to those two brain regions and their role in wider associated cortico-subcortical networks is reviewed. Most importantly, this article brings new insights bridging causal evidence on the structural and functional neuroanatomy subtending OCD and novel therapeutic perspectives based on focal brain stimulation.

Invasive stimulation technique in OCD

To our knowledge, this is the first report which provides an opportunity to discuss four

CONCLUSION

Altogether, our results do not allow us to conclude that a brain region is over-or underactivated in patients suffering from obsessive-compulsive disorder; nor do they demonstrate a dysfunctional functional network in those patients.

o

  Cutting-edge machine learning algorithms applied to neuro-imaging data comparing OCD patients and HC o Indirectly confirm or invalidate the role of the OFC using a DNMS task in patients suffering from OCD versus HC o Using causality thanks to non-invasive and invasive stimulation techniques for the same purpose -Based on the lessons of objectives 1 and 2, develop a new experimental paradigm combining a metacognition task with an eye tracker and an EEG recording

  Optogenetic technology was developed by Ahmari et al. in which mice were infected with a virus encoding a lightactivated excitatory ion channel rhodopsin into the medial orbitofrontal cortex leading to expression of a yellow fluorescent protein. Repeated hyper-stimulation of the OFC and ventromedial striatum led to progressive increase in repetitive grooming and triggered heightened locomotion, which can be terminated immediately upon light inactivation.

Figure 1 .

 1 Figure 1. The theoretical basis of obsessive-compulsive behavior. How healthy people deal with concerns as compared to OCD patients?

Figure 2 .

 2 Figure 2. Cortico-striato-thalamo-cortical circuitry. Brain section showing limbic network loops encompassing the prefrontal cortex, the basal ganglia and the thalamus. The dotted black line illustrates an indirect subcortical feedback to executive cortical prefrontal regions. The coronal brain section shows excitatory and inhibitory details in the indirect pathway of the basal ganglia. Cortical regions to OFC (dotted) (cortical region such as CCA, insula amygdala)

  intervention for OCD. Concordantly to the previously described research works on the implication of OFC in OCD, studies have shown a correlation between a decrease in OFC hypermetabolism in OCD patients with an effective treatment. First Rubin et al.(62) and then Nakao et al.(63) have confirmed that pharmacological treatments used for OCD patients (CBT and SSRIs) lead to a decrease in OFC hypermetabolism. Moreover, Nuttin et al.(64) have proved that treatment of OCD using brain simulation techniques leads to a decrease in OFC hypermetabolism. Next, Le Jeune et al.(65), in treatment-resistant OCD patients, have established a correlation between a decrease in scores on the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and a decrease in PFC metabolism during subthalamic nucleus (STN) stimulation, knowing that a small score at the Y-BOCS is a synonym of remission for OCD patients. Then, Nauczyciel et al.(66) have demonstrated that the OFC might be reached by a non-invasive brain stimulation such as repetitive transcranial magnetic stimulation (rTMS)

  In 2008, Chamberlain et al.[START_REF] Chamberlain | Orbitofrontal Dysfunction in Patients with Obsessive-Compulsive Disorder and Their Unaffected Relatives[END_REF] demonstrated that impaired probabilistic reversal learning in OCD is associated with hypofunction of bilateral lOFC, both in patients with OCD and in their unaffected relatives, suggesting that this abnormality could even represent an endophenotype of this disorder. Similarly, Remijnse et al.[START_REF] Remijnse | Cognitive Inflexibility in Obsessive-Compulsive Disorder and Major Depression Is Associated with Distinct Neural Correlates[END_REF] showed decreased lOFC activation in OCD during probabilistic reversal learning. In 2013, Burguière et al.(58) have also reinforced this idea by successfully suppressing compulsions in a mouse model after optogenetic stimulation of lateral orbitofronto-striatal pathway.

  Contrary to the results of Martoni et al. and Ciesielski et al.(81,82), our study states that OCD patients perform worse than HC for DMS task. However, this difference may be explained by a different methodology; first Ciesielski et al. followed 4 OCD patients only and, although Martoni et al. used a sample of 42 OCD patients, they chose not to monitor the response time.

Figure 1 .

 1 Figure 1. Location of the OFC region Red = the mOFC; blue = the lOFC

Figure 2 .

 2 Figure 2. Delayed Matching to Sample and Delayed Non Matching to Sample tasks

1 . 5 (

 15 FDG-PET data from the Rennes STOC consortium of patients with OCD (STOC, 10 patients) 2. FDG-PET data from the Rennes ORBITOC consortium of patients with OCD (ORBITOC, 10 patients) 3. FDG-PET data from Rennes hospital of patients with OCD (OCD_Rennes, 13 patients) 4. FDG-PET data from La Pitié-Salpêtrière hospital in Paris of patients with OCD (OCD_Paris, 25 patients) 5. FDG-PET data from Rennes of healthy subjects (HC, 20 patients) STOC, ORBITOC, and OCD_Rennes cohorts data have already been published in Nauczyciel et al. 2010 [citer] and Le Jeune et al. [citer] papers. The diagnosis of OCD has been made by senior psychiatrists according to the DSM-American Psychiatric Association, 2013). Table 1. shows socio-demographic characteristics for each cohort. All patients were considered OCD treatment-resistant because they did not respond to at least two different SSRIs and to a CBT. Informed consent was provided for all participants, and the Committee for the Protection of Patients ("Comité de Protection des Personnes": CPP) of La Pitié Salpêtrière Hospital approved the study. PET data acquisition and preprocessing STOC, ORBITOC, OCD_Rennes patients and healthy control subjects underwent PET scans at the same center in Rennes (Department of Nuclear Medicine, Eugène Marquis Center), while OCD_Paris underwent PET scans in the Pitié-Salpêtrière hospital in Paris (Department of Nuclear Medicine lead by Pr. Kas). The neuroradiologist was blind to the stimulation conditions of each patient. All OCD patients were studied using 18fluorodeoxyglucose (18FDG)-PET in a resting state with eyes open, having fasted for at least 6 hours. Patients from STOC and ORBITOC cohort underwent two scans at the end of each phase of randomization (M6 and M10 of the protocol). PET acquisition was performed using a Discovery ST PET scanner (GEMS, Milwaukee, Wisconsin) in 3D mode for Rennes patients and a Siemens for the Paris subjects. Preprocessing was performed using SPM12 (Wellcome Department of Cognitive Neurology, London, United Kingdom) implemented in Matlab, version 9.10 (MathWorks, Sherborn, Massachusetts). All subjects were registered in the MNI (Montreal Neurological Institute) space using a 12-parameter affine transformation. The subtle differences between the transformed image and the template were then removed by applying a nonlinear registration method. Dimension of the resulting voxels were 2x2x2 mm. Standardized data were then smoothed by a 12-mm full width at half maximum isotropic Gaussian filter. We replicated the preprocessing performed by Le Jeune et al. and Nauczyciel et al. Statistical Analysis T-tests 1. STOC -DBS ON versus DBS OFF This study aimed to assess the efficacy of DBS on the subthalamic nucleus (STN) in OCD, and try to highlight the neural substratum of this approach. One group of patients with refractory OCD and one healthy control (HC) group took part in the study. The patient group comprised a series of 10 patients with refractory OCD, all of whom had undergone bilateral STN DBS in the STOC study. Le Jeune et al. paper proved a significant decrease in cerebral metabolism in the left limbic lobe (cingulate gyrus, BA24 and 32) and left frontal lobe (medial gyrus, BA 6) in the On-

(

  rbf). C parameter was optimized using Random Search cross validation procedure. It allows control of the trade off between smooth decision boundary and classifying the training points correctly. We performed penalized L1 and L2 logistic regression, to shrink the coefficients of the less contributive variables toward zero. Logistic Regression Logistic regression models the probabilities for classification problems with two possible outcomes. It's an extension of the linear regression model for classification problems. A solution for classification is logistic regression. Instead of fitting a straight line or hyperplane, the logistic regression model uses the logistic function to squeeze the output of a linear equation between 0 and 1.

Only 40 -

 40 60% of patients show no-or just partial symptom improvement after this first-line pharmacological treatment. Treatment of OCD patients refractory to serotonergic antidepressants include dose increase, intravenous clomipramine, switching to other first-line drugs or combination of firstline drugs, augmentation with antipsychotics (i.e. haloperidol, risperidone, quetiapine, aripiprazole, or olanzapine), augmentation with CBT, and trial with other drugs such as memantine or amantadine(99) (both N-methyl-D-aspartate or NMDA receptor antagonists), Nacetylcysteine(100) (glutamate modulator), D-cycloserine (glutamatergic agent and NMDA receptor agonist), mirtazapine (serotonin receptor antagonist), or benzodiazepine.

OCD patients performed more than 20

 20 years ago hinted on the suitability of this technique to better understand the pathophysiology of OCD. It reported evidence of neuronal loss in the ACC and the right striatum of OCD patients shown by lower NAA (N-Acetylaspartic Acid)(41) levels that correlated with Y-BOCS scores assessing illness severity(43). Most importantly, NAA, which is a marker of neuronal integrity and synaptic density, normalized after behavioural therapy(46).Besides, these findings obtained in basal conditions, recent neuroimaging activation studies point as well the OFC region. The Delayed-Non-Mathinc-To-Sample task (DNMS), a learning task that combines positive emotional with reward conditioning, distinguished the lateral and medial portion of the OCD and allocated an essential role to lateral portion in patient symptoms(103). Finally, fMRI studies have shown that successful treatment with brain stimulation interventions such as repetitive Transcranial Magnetic Stimulation (rTMS) or Deep Brain Stimulation (DBS) appears to reduce the functional hyperconnectivity between prefrontal cortical regions and the ventral striatum/head of the caudate nucleus(104), thus providing evidence that the hyperconnectivity in these pathways is not merely epiphenomenal but may in fact have a causal role in perpetuating the illness.The Supplementary Motor Area (SMA) and the Presupplementary Motor Area (pre-SMA) have also been explored in OCD patients. Those two regions, the pre-SMA (BA32/BA8) and SMA (BA 6) form a part of the sensorimotor CSTC circuit, together with the motor (M1) and premotor cortices. These cortical regions project topographically to the putamen, which in turn projects by direct (via globus pallidus interna) and indirect (via globus pallidus externa) pathways via basal ganglia to the thalamus and cortex, forming a sensorimotor CSTC loop(105-107). De Wit et al. studied in 2012 the Pre-SMA hyperactivity during response inhibition(108). They have compared Forty-one OCD patients, 17 of their siblings, and 37 matched healthy comparison subjects in a stop-signal task during 3-T functional MRI. The stop-signal reaction time provided a behavioural measure of response inhibition. The neural correlates of response inhibition were assessed in a region-of-interest analysis that included the Pre-SMA, inferior frontal gyrus, subthalamic nucleus, and inferior parietal cortex. They demonstrated that patients with OCD had greater stop-signal reaction times relative to healthy comparison subjects. Both patients with OCD and their siblings showed greater activity in the left Pre-SMA during successful inhibition relative to comparison subjects. In patients and siblings, Pre-SMA activity correlated negatively with stop-signal reaction time. Grützmann et al. studied in 2016 have as well studied the Pre-SMA(109). They used concurrent EEG and fMRI data from 20 patients with OCD and 22 healthy control subjects during a flanker task. Patients with OCD showed significantly increased ERN amplitudes. Increased activation of the right amygdala and the subgenual anterior cingulate cortex following errors was observed in patients with OCD. Increased intraindividual correlation of the ERN and activity of the Pre-SMA was found in patients with OCD compared with healthy controls. Brain stimulation techniques to understand and treat OCD The use of invasive and non-invasive brain stimulation technologies combined with neuroimaging approaches such as FDG-PET is tightly linked to physio-pathological understanding of OCD. DBS, rTMS and very recently Transcranial Direct Current Stimulation (tDCS) have been probed as attempts to restore normal activity of dysfunctional OCD pathways, allowing to causally explore the neural basis of the disease. Their modulatory power has been tested in OCD relevant brain regions to pinpoint relevant nodes for OCD symptoms, such as the subthalamic nucleus (STN), the OFC, the prefrontal cortex (PFC), Pre-SMA and the ACC. High frequency DBS played a pioneer role in supporting a causal role for the basal ganglia and its connected prefrontal cortical structures in the pathophysiology of OCD. In the 2000s, two trends emerged thanks to the development of this invasive interventional technique in OCD. On the one hand, some teams (Nuttin and Cosyns in Belgium(64), Denys in the Netherlands(110), Greenberg in USA(111)) used high frequency DBS to targeted the anterior limbs of the internal capsules, disconnecting subcortical and cortical prefrontal structures. FDG-PET studies by Nuttin and colleagues reported increases in OFC metabolism combined with overall decreases of brain metabolism caused by the stimulation. On the other hand, given the tight connections between the STN and the PFC, the French Consortium leading the STOC study (OCD Stimulation study in French) designed by our team, tested successfully high frequency DBS stimulation on this subthalamic target in Parkinson patients with OCD comorbidity(112).Years thereafter, this project led to the first randomized crossover study showing the effectiveness of this therapeutic approach in highly resistant OCD patients. Consistently, an ancillary FDG-PET study in patients included in the STOC study(113) showed during STN stimulation decreases in the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) scores, which as hypothesized, proved significantly correlated with decreases in their OFC metabolism. Studies combining DBS with FDG-PET supported the notion that OCD could be related to the combined dysfunction of the basal ganglia and the PFC regions. Efficacy of high frequency DBS applied either on the internal capsule or the NST, suggested an effect potentially related to either reduced metabolism in the PFC or the OFC, both promising targets for non-invasive brain stimulation therapy. The latter evidence focused our team's attention on the PFC sites as potential target for OCD. In parallel, insights by other teams such as Mantovani and colleagues(114) provided support in favor of our idea and reported improvements in OCD after 1Hz inhibitory rTMS over the pre-SMA first in an open-label study, which was later on confirmed in a randomized, doubleblind clinical trial. These same results have been further replicated by Gomes et al, reporting long-lasting effect of low frequency rTMS treatment over 14 weeks. Owing to the difficulty of directly stimulating the OFC, which is deeply buried beneath the rostral scalp, the role and therapeutic potential of this structure has been poorly explored with rTMS. However, in a simple-blind, randomized study targeting the left OFC with 1 Hz inhibitory stimulation, Ruffini et al(115) observed clinical improvement compared to sham intervention. The efficacy of lowfrequency rTMS of the right OFC in OCD patients has been demonstrated in a double-blind study; and was further assessed in 2013 using a double-cone coil to achieve deeper penetrability and stimulate more efficiently a deeply located OFC(66). In a prospective multicentric randomized double blind study(116) high frequency deep TMS targeting the ACC and the medial PFC showed significant improvement of OCD symptoms. It should be kept in mind that rTMS and tDCS are brain stimulation procedures that are limited in reaching deep cortical areas such as ACC and that DBS is an invasive technique with risk of health complication. Targeted in therapeutic interventions and combined with neuroimaging these stimulation techniques are called to provide a unique window to better understand pathological brain activity and connectivity subtending OCD.

  reward and punishment prediction by displaying excitation(126). Another line of thought supports the notion that the ACC does not only encode values but plays out an integrative function in processing and solving cognitive conflicts, participating in the selection of competing tasks and allocating executive control. To this regard, very influential work by Brown and Alexander propose a model with both pro-active and reactive control, attributing to the ACC high influence on other brain networks(127). At difference, other authors integrate nearly all the presumed roles of ACC here reviewed, but assigned a more nuanced role in executive control allocation based on an evaluation of the expected value of control(128).

ARTICLE 5 :

 5 Sustained recovery in a treatment-refractory obsessivecompulsive disorder patient after Deep Brain Stimulation battery failure Word count of the manuscript text: 2920 words Abstract Obsessive-compulsive disorder (OCD) is a widespread chronic neuropsychiatric disorder characterized by recurrent intrusive thoughts, images, or urges (obsessions) that typically cause anxiety or distress. Even when optimal treatment is provided, 10% of patients remain severely affected chronically. In some countries, deep brain stimulation (DBS) is an approved and effective therapy for patients suffering from treatment-resistant OCD. Hereafter, we report the case of a middle-aged man with a long history of treatment-resistant OCD spanning nearly a decade with Y-BOCS scores oscillating between 21 and 28. The patient underwent bilateral implantation of ventral striatum/ventral capsule (VS/VC) DBS leads attached to a batteryoperated implanted pulse generator (IPG). After a 3 months post-implantation period the DBS protocol started. Three months after the onset of DBS treatment, the patient's Y-BOCS score had dropped to 3 and he became steadily asymptomatic. Yet inadvertently, at this time, it was found out that the IPG battery had discharged completely, interrupting brain stimulation. The medical team carried on with the original therapeutic and evaluation plan in absence of active DBS current. After 12 additional months under off-DBS, the patient remained at a Y-BOCS score of 7 and asymptomatic. To our knowledge, this is the first report which provides an opportunity to discuss four different hypotheses of long-term recovery induced by DBS in a treatment-refractory OCD patient, notably: (1) A placebo effect; (2) Paradoxical improvements induced by micro-lesions generated by DBS probe implantation procedures; (3) Unexpected late spontaneous improvements; (4) Recovery driven by a combination of active DBSinduction, the effects of medication and DBS-placebo effects.

  Deep brain stimulation (DBS) involves the implantation of intracranial multielectrode leads with several contacts (also referred as electrodes) used to deliver trains of electrical pulses to specific brain locations such as the Subthalamic Nucleus (STN) or the Ventral Striatum/Ventral Capsule (VS/VC) by means of an implanted pulse generator (IPG)(133,137,138). The implantation of DBS leads and the delivery of electrical current do not cause major neural damage, but require brief adjustments of stimulation parameters during the postoperative period and often lifelong maintenance involving battery replacement, the repair of hardware dysfunction, and medically, the prevention of infections. Although shown effective to treat several disorders such as Parkinson's disease (139), Dystonia (140), Tourette syndrome (141) and OCD (142), the underlying mechanisms leading to DBS-mediated improvements remain unknown. Moreover, the optimal locations where to implant electrodes and the best stimulation parameters (frequency, amplitude and number of pulses) are still debated.

  for details). The IPG used in DBS systems integrates a microchip, allowing neurostimulation parameters (current intensity, frequency and pulse width) to be programmed and fine-tuned via an external portable appliance communicating wirelessly with it. Once multielectrode leads are implanted, the site of DBS neurostimulation can be further adjusted in the close vicinity of the implanted area by conveying electrical pulses to different contacts along the lead, usually present in a number of 4, and activating them independently (148). After a quick initial coarse tuning of stimulation variables, further DBS parameter adjustment takes place on average between the first 3 to 6 months (see details in (65,142) guided by changes in symptom severity observed in patients and measured with clinical scores. Once established, DBS parameters remain effective for the following 12 months or for even longer periods of time. Accordingly, stimulation parameters inducing clinical benefit shown in OCD by decreases of Y-BOCS scores, are maintained until further notice, and kept unchanged until the end of a clinical trial follow-up period. Typical stimulation parameters for DBS in OCD may vary within the following ranges (149): Pulse frequency between 130-185 Hz, current power between 1-10 V, and biphasic pulse width between 60-150 milliseconds.

  2016, the patient was included in a prospective randomized double-blind DBS clinical trial. The design of the study included two arms; in one condition, two multielectrode leads were implanted bilaterally into the right and left Ventral Striatum/Ventral Capsule (VS/VC), whereas in the other arm of the clinical trial, leads were implanted also bilaterally into the subthalamic nucleus (STN). Implanted multi-electrodes were non-MRI compatible quadripolar stimulation leads (Model #3391, Medtronic, Minneapolis, Minn., USA) made of 4 contacts (4.0 mm spacing between four 3.0 mm long electrodes). Target regions were identified using a combination of T1 (without and with Gadolinium injection) and T2 MRI sequences and a validated 3D histological and deformable YeB atlas of the basal ganglia (151). Neurosurgical trajectories were planned and selected to allow contacts in both, the left and the right VS/VC regions. Implantations were performed using a Leksell frame (Elekta Instruments, Inc) assisted intra-operatively with real-time X-ray guidance and micro-electrode recordings (MER). Implantations in our patient, targeted the right and left VS/VC site with the following MNI coordinates: Right VS/VC: X=-8, Y=34, Z=4.5 (Leksell frame X=91.5, y= 118.5 Z=113 A=65, B=70) Left VS/VC: X=9.5 (Leksell frame Y=33, Z=4, X=109, Y=117, Z=112.5 A=120, B=78).The final location of the 4 contacts at the bottom end of each multi-electrode lead were semiautomatically detected on a postoperative O-Arm helical CT-scan linearly registered to the preoperative T1-weighted MRI, the YeB atlas was co-registered to (Figure2) (152). As usually done in prior protocols, electrodes were left to settle for 3 months. By the end of the 3 rd month, and following a short period of parameter adjustment well-detailed elsewhere (65,142), stimulation was set up at some fixed parameters (see below for details on stimulation parameters).By inclusion criteria, the patient had to attest maintaining the same pharmacological treatment during 6 months preceding lead implantation neurosurgery, and throughout his participation in the DBS trial, until the end of the follow-up. Hence 6 months prior and throughout his participation in the DBS clinical trial, our patient was on fluoxetine 60 mg/day, aripiprazole 10 mg/day and clomipramine 75 mg/day. No changes of medication were made during this period.After a post implantation 'off-stimulation' period of 3 months, stimulation with the IPG (Medtronic Activa TM PC non-rechargeable neurostimulator) started. A set of parameters were implemented in a first stimulation protocol targeting bilaterally the VS/VC (130 Hertz, 6 V, Pulse width at 90 milliseconds, delivered through lead contacts n° 3 and n° 11 for right and left stimulation, respectively). Following a short period devoted to parameter adaptation and guided by short-term clinical responses, the former protocol was modified by adding the bilateral stimulation of the associative portion of the caudate nucleus. This modified stimulation protocol was then applied continuously for 3 additional months (130 Hz frequency, 3 V and biphasic pulses of 120 ms width, delivered through lead contacts n° 2 and n° 10 for right and left stimulation, respectively).

  suggestive of DBS placebo recovery, in a patient with severe OCD scores in the context of a stimulation regime, halted inadvertently by battery depletion. Importantly, the patient had shown symptoms refractory to pharmacological and non-invasive brain stimulation treatments, spanning for nearly a decade. Hence it is very unlikely that the achieved recovery might have been triggered 'spontaneously' or could have occurred totally unrelated with the DBS procedures undergone as the ultimate therapeutic option.Interestingly, evidence from the NIH OCD DBS patient cohort addressing the clinical consequences of IPG battery depletion and/or DBS device failures instead of OCD improvements, reported increases in Y-BOCS scores and severe neuropsychiatric and mood symptoms, together with motor restless-like sensations, (153). On this basis, either a very effective induction of after-effects following a short period of DBS stimulation or a DBS mediated placebo impact should be considered as potential recovery factors in this single patient OCD case. These findings are potentially promising since they could allow psychiatrists treating medication-resistant OCD patients with DBS to design stimulation regimes which operate during restricted time periods instead of being delivered chronically, as it is most often the case. These alternative approaches could also contribute to significantly reduce the number of pulses and the duration of DBS regimes (hence the total current delivered on a given brain area) limiting battery consumption in IPG systems.The findings here reported are coherent with several clinical cases compiled in recent publications, reporting similar phenomena on other types of pharmaco-resistant disorders treated with DBS (152-154). More specifically, the case of a single patient with Tourette syndrome implanted bilaterally in the Centrals-Median-Parafascicular complex of the thalamus and in the limbic territory of the internal portion of the Globus Pallidus revealed decreases of tic severity and self-injurious behavior, following implantation surgery and before stimulation was ever applied (152). Moreover, a systematic review studied the frequency and magnitude of placebo effects in a sample of 126 Parkinson's disease patients treated with DBS (154).Outcomes showed that active DBS was more effective when preceded by a sham-DBS block than in the absence thereof, estimating the contributions of placebo-DBS as accounting for 39% of the total recovery driven by active-DBS. Finally, a study in tremor-dominant Parkinson's disease treated with DBS to the STN, showed that patient's expectations about stimulation therapy, modulated motor and cognitive dysfunction outcomes (155). Indeed, positive expectations enhanced the clinical impact of STN-DBS by further decreasing the magnitude of patient's tremor, whereas in contrast, negative expectations counteracted its therapeutic benefit and exacerbated some of its side-effects. Taken together, this evidence suggests that placebo effects and/or positive expectation tied to such may contribute to improve in DBS patients enduring symptoms of treatment-resistant diseases (e.g. Tourette syndrome and Parkinson's disease), in absence of effective stimulation. Our single case report extends now these intriguing observations to a well-characterized psychiatric condition also treated with DBS such as OCD.

  we cannot completely rule out late-acting spontaneous recovery triggered by uncontrolled behavioral factors the patient might have been exposed to but failed to report to clinicians.Second, we cannot totally discard either that a very short period of effective DBS stimulation during the brief time the IPG battery could have been operational may have driven enduring recovery, independently of a placebo influences over longer-term recovery maintenance. Third, we cannot completely rule out either the possibility of a synergistic interaction between ongoing medication at the time our patient integrated the study and a short period of DBS during a period time in which stimulation could have been effective (indeed, both factors insufficient to drive recovery per se, but boosting their individual effects when combined). Last, four pieces of information highlight the atypicality of the patient´s clinical history and may argue in favour of spontaneous recovery as the cause of clinical improvements: (1) An OCD condition which occurred in middle-age patient (the average onset age of symptoms in OCD patients included in DBS studies is ~15 years old), hence which may be potentially influenced by a higher loading of environmental and neurological influences (see Sharma et al. 2019 for details); (2) OCD symptoms which appeared after a traumatic event in relation to a work accident; (3) A halt in alcohol consumption (which was significantly increased since 2012), around the time of Y-BOCS recovery; (4) Finally, the very rapid fall of Y-BOCS scores (from 22 to 3) in only three months) during DBS treatment. Additionally, recovery from essential tremor in Parkinson's disease (157-159) prior to the onset of a systematic DBS regime has also been associated with structural micro-lesions in implanted grey matter sites along the trajectory of the multielectrode (160). Moreover, the existence of DBS microlesions has been questioned by a study in STN-stimulated Parkinsonian patients that failed to demonstrate lasting signs of micro-electrode damage in PET imaging (161). Unfortunately, in our current case, the lack of post implantation high resolution MRI (note that implanted leads contained paramagnetic materials) and the absence of a thorough search for collateral clinical symptoms, both essential to attest micro-damage, preclude confirming or ruling out any of these hypotheses. Similarly, we can only speculate on the potential mechanisms by which enduring severe OCD symptoms wore off persistently in our patient. These could be explained by self-training or self-learning processes and the long-term suppression of abnormally excited CSPTC loop activity induced by DBS. Nonetheless, none of these scenarios can be properly assessed, given the lack of direct measures (other than clinical assessments via Y-BOCS scores) able to follow structural and physiological changes subtending the recovery of our patient. Indeed, a large majority of EU certified DBS multielectrode leads approved for human use contain non-MRI-compatible components, preventing the recording of structural and functional MRI datasets of sufficient quality. Additionally, these leads are unsuited to record local electrical signals from stimulated regions.Optimizing multielectrode lead design would allow a better understanding DBS modulation of brain systems. In fact, in OCD, this therapeutic approach hypothesizes frequency-specific effects along a CSPTC network. These effects could be mediated via the modulation of local and network levels of activity and excitability and/or interregional synchrony. This are thus far difficult to be monitored jointly with high spatial and temporal resolution. The implantation of MRI compatible leads equipped with electrodes able to deliver current and also record intracranial EEG signals would enable a precise localization of implanted brain sites and the identification of areas of damage at several intervals during a follow-up. Moreover, coupling of the former with multimodal imaging (structural and functional MRI approaches, PET-MRI technologies and intracranial EEG/single unit recordings) will grant new opportunities for monitoring hemodynamic, metabolic, and neurophysiological changes across DBS regimes, and also to assess the impact of microlesions caused by implanted multielectrode leads. Future OCD case studies similar to the one here reported, and controlled clinical trials implementing a new generation of leads coupled to imaging methods, will be in a better position to disambiguate sham DBS placebo effects from long-lasting clinical improvements induced by short period of effective stimulation and/or sustained via placebo phenomena.

Figure 1 .

 1 Figure 1. Schematic drawing of a Deep Brain Stimulation (DBS) multielectrode implanted lead and an implanted pulse generator (IPG) on OCD patients. Patterns of electrical activity and customized parameters of frequency, intensity and pulse duration are delivered to improve the clinical symptoms of OCD. A multielectrode lead (Medtronic Model #3391) was inserted through the internal ventral capsule (VC) so that one of its contacts (3 mm long, 4 mm interelectrode distance), reach either the ventral striatum (VS) or the subthalamic nucleus (STN). VS: Ventral Striatum, GP: Globus Pallidus.

Figure 2 .

 2 Figure 2. Implanted multielectrode leads, were visualized using a combination of a preimplantation T1 MRI volume (without and with Gadolinium injection), a T2 MRI sequence, and a validated 3D histological and deformable YeB atlas of the basal ganglia. blue: Caudale Nucleus; dark green: Putamen; purple: Substantia Nigra. pink: Limbic Subthalamic Nucleus; green: Sensorimotor Subthalamic Nucleus.

  control subjects and OCD subjects on selected cognitive tasks. It is taking place at the Pitié-Salpêtrière Hospital. In order to improve external validity, this study protocol is implemented in the usual French healthcare system. The study protocol has been approved by the local ethics committee, and by the regulatory agencies (Commission nationale de l'informatique et des libertés #GPR1713292F and Agence nationale de sécurité du médicament. Inclusions are planned between May 2022 and December 2022. The Assistance Publique -Hôpitaux de Paris is the promoter of this research and by delegation the Délégation à la Recherche Clinique et à l'Innovation (DRCI) assures the missions, in accordance with article L.1121-1 of the public health code. A doctor or a "qualified" person (such as an intern) includes patients in this study.

  arouse certain uncomfortable memories or forbidden thoughts in patients. But they are not necessarily "shocking" in the literal sense of the word, i.e. they do not necessarily offend propriety. For example: dirty sink, girl in skirt, precipice, kitchen knife... This part of the task consists of 10 different images (different types), each of which is presented in 5 variations. There are therefore 50 trials. Non-shocking (Figure 1.b.) Images with no particular emotional value. This part of the task is composed of 10 different images (different types), each with 5 variations. There are therefore 50 trials. The 5 variations of the 10 shocking and 10 non-shocking images are presented in a completely random order, but the order is the same for all participants. The image pairs are presented for 7 seconds. Subjects have unlimited time to respond. Between this first part and the calligraphy part, participants have a 2-minute break. Calligraphy (Figure 1.c.)Words and characters that do not use the Latin alphabet, and which, in principle, have no semantic content for the patient (unless the patient masters the language in question). Thus, only the curves and lines of the characters count. Using different calligraphy allows one to free oneself from both the cultural bias and the figurative and semantic content that the images of the first subtask may present.Each language has 2 images, each image has 5 variations: 2 Arabic calligraphies, 2 Hebrew calligraphies, 2 Russian calligraphies, 2 Chinese calligraphies, 2 Tamil calligraphies Each of the calligraphies is declined in 5 variations of 7 differences game. Finally, there are: 5 types of language X 2 calligraphies per language X 5 variations of trials per calligraphy = 50 trials. The 5 variations of the 10 calligraphies are presented in a completely random but identical order among the participants. The image pairs are presented for 5 seconds. The subjects have unlimited time to respond. Examples of the other types of calligraphy are in the annexe-Fig1. Between the calligraphy part and the chess part, participants have a 2-minute break. Chess (Figure 1.d.)Two apparently similar chess boards are presented. However, some pieces can be added or removed and sometimes replace other pieces, randomly on all 64 squares between the two boards. Each type of board contains between 15 and 20 pieces distributed in a completely random manner. Having a chess board helps to avoid the reading bias that can be present in calligraphy images, which can be read from left to right or right to left. The gaze is not guided, and the subject is free to explore the two versions of the board as he or she wishes, without being influenced by reading conventions.There are 10 different types of chessboard in 5 variations. There are therefore 50 trials. The 5 variations of the 10 types of chess boards are presented in a completely random but identical order among the participants. The image pairs are presented for 5 seconds. The subjects have unlimited time to respond. The 7-difference task therefore consists of 100+50+50 = 200 trials This task takes about 45 minutes.

  .a.) (with no particular shape), straight (Figure 2.b.) and special (Figure 2.c) (matches take special shapes). The subject must then choose between two proposals the exact quantity of matches he thinks he has seen. The response time is unlimited. After the first 50 trials, the participant's level is estimated. If the subject has had at least 40 correct answers, he or she belongs to the "pro" group. Then the exposure time for the next 50 images is divided by 2 for each image. If the subject is in the neutral group (below 40 correct answers on the first 50 trials), the subject continues the task without changing the condition for the next 50 propositions. The task lasts about 10 minutes. C) Where is Tockie? (Figure 3.a,b,c)

Figure 1 .Figure 2 .Figure 3 .Figure 4 .

 1234 Figure 1.a. Example of non-shocking trial in 7 diff task-six differences

  different hypotheses of long-term recovery induced by DBS in a treatment-refractory OCD patient, notably: (1) A placebo effect; (2) Paradoxical improvements induced by micro-lesions generated by DBS probe implantation procedures; (3) Unexpected late spontaneous improvements; (4) Recovery driven by a combination of active DBS-induction, the effects of medication and DBS-placebo effects.

Table 1 .

 1 Group mean (SD) sociodemographic and clinical variables for OCD patients and healthy controls (HC)

	OCD	Controls	p

Table 2 .

 2 Numbers of patients in the OCD group with lifetime comorbidities, OCD symptom dimensions and medication at inclusionFor each patient, only the main dimension is represented in the table

	Comorbidities		Dimension		Medication
	no comorbidities	13 checker	11	no medication	2
	mild depression	3	washer	6	at least one antidepressant 18
	moderate depression	2	other	3	clomipramine	12
	panic disorder	2			antipsychotic	7
	social phobia	3			benzodiazepine	4
	PTSD(post-traumatic	1
	stress disorder)

Table 3 .

 3 Comparison of performances in DMS and DNMS between OCD patients and healthy controls using Student's t-test.

		Mean (OCD ; HC) t	p	Cohen's d
	Correct answers in OCD	26.00 ; 28.35	-2.687	0.010*** .85
	patients vs HC for the DNMS
	Response time in OCD	2971 ; 2125	2.519	0.016*** .80
	patients vs HC for the DNMS
	Correct answers in OCD	26.30 ; 27.65	-2.089	0.043*	.66
	patients vs HC for the DMS
	Response time in OCD	2623 ; 1889	2.332	0.025**	.74
	patients vs HC for the DMS
	Correct answers DNMS	26.00 ; 26.30	-0.307	0.082	.62
	vs DMS for OCD patients
	Response time DNMS	2971 ; 2623	2.285	0.03*	.24
	vs DMS for OCD patients
	Correct answers DNMS	28.35 ; 27.65	1.788	0.09	.33
	vs DMS for HC
	Response time DNMS	2124 ; 1889	1.423	0.170	.46
	vs DMS for HC

t = t-test; p = p-value; df = degrees of freedom; * significance; response time in ms calculated only for correct answers;

  trained several binary classifications estimators' analysis, notably Support Vector Classifier

	(SVC), logistic regression, and Ridge classifier, penalized in L1 and L2. Particularly useful in
	imbalanced datasets, we built a Dummy classifier which makes predictions without trying to
	find patterns in the data. In other words, it is a "naive" classifier predicting the most frequent
	class label in the training data, but his interest is to establish a baseline and compare other
	model's performance to it.

SVC

Support Vector Classifier (SVC) is a non-probabilistic binary linear classification method. The SVC computes a hyper-plane maximally distant from both groups to separate them, and thus classify with. As, in our case, data is not linearly separable, we transformed the data in a higher dimension where training data can be separated using the Gaussian radial basis kernel function

  reanalyzing the PET data published in Nauczyciel et al. and Le Jeune et al., we were unable to reproduce the results found by replicating the methods used. This therefore raises a to PET data. Therefore, if there isn't even a consensus on the preprocessing strategies used to preprocess PET data, how can we establish if PET is reliable or not? (Eklund et al. 2016,

	Introduction
	Aurich et al. 2015). Obsessive-Compulsive Disorder (OCD) is considered the 4th most common mental
	disease disorder in developed countries. According to the World Health Organization (WHO) it
	In addition, with the growing amount of statistical analysis methods, including machine represents the 10th leading cause of disability(91). Obsessions are incessant, intrusive and
	learning methods, it is difficult to know which method is suitable for which problem. To go upsetting thoughts with non-substantiated contents (i.e., contamination) which will lead
	further, we could question the influence of the choice of metric in the results. Taking into individuals to compulsions (wash their hands or shower repeatedly during the day) or generate
	account the geometry of the problem does not necessarily imply the creation of a new metric Figure 1. Benchmark of ML methods ongoing doubts leading to preventive safety chores to be accomplished (i.e. locking and
	for each study. unlocking doors, or turning off the gas stove or iron) compelling the patient to check the act
	over and over.
	Compulsions are repetitive behaviours or mental acts according to which affected
	Cleaning -Fears of contamination and cleaning rituals
	Symmetry -Symmetry obsessions and repeating, ordering, and counting
	compulsions
	Forbidden or taboo thoughts -Examples include aggressive, sexual, and
	religious obsessions, and related compulsions
	Harm (e.g. thoughts or images about harm befalling oneself or others and
	checking compulsions)(92,93)
	more global problem. Are the old published results still valid today? The question arises today,
	with increasingly efficient statistical analysis algorithms, and demanding in terms of data
	quality but also with the advent of new analysis methods including machine and deep learning
	methods. More than 30, 000 papers have been published in PET brain imaging (source :

Pubmed) from various specialities (oncology, neurology, psychiatry). There are many sources of variability in PET data and unfortunately, the steps chosen in the preprocessing pipeline can be one of these variables. There isn't a consensus on which preprocessing strategy is the best to be applied

In this paper, we developed an open-source PET pipeline analysis in Python using machine learning techniques, which can be forked on GitHub. To do so, we chose Nilearn (version 0.8.) which implements scikit-learn algorithms so makes it easy to use many advanced machine learning, pattern recognition and multivariate statistical techniques on neuroimaging data. This paper lays the foundation stone in the standardization of the PET image processing methodology.

individuals feel driven to perform to alleviate the distress provoked by the obsession. The repetitive action is undoubtedly excessive or not obviously associated realistically with the anxiety it tries to relieve or neutralize, a fact that the individual usually recognizes as illogical (e.g., ordering and arranging household items; counting forward and backward to prevent harm to loved ones).

The specific content of obsessions and compulsions varies widely among individuals; however, there are certain identifiable themes, also described as "symptom dimensions". People with OCD often have symptoms in multiple dimensions, which include:

  al., 20 to 30 specific words related to dimensions of the patient's symptoms were selected by a clinician after a structured interview. Once in the MRI, the patient repeated these words every 4 seconds, whereas in a control condition the same patient repeated names of fruits, vegetables or flowers with the same time interval. The authors observed increased activation of the orbitofrontal cortex and the anterior cingulate cortex during this task(Nakao et al. 2005).(Nakao et al., 2005). In the same vein, consistent findings from functional neuroimaging studies using provocation have shown an increased activations in the OFC, the ACC, the dorsolateral prefrontal cortex and caudate nucleus(Milad & Rauch, 2012) (Sha et

al., 2020). Authors such as (Iervolino et al., 2011) or (Mataix-Cols et al., 2004) have also reported that symptom dimensions may involve different brain structures.

ARTICLE 2: Performance in delayed non matching to sample task predicts the diagnosis of Obsessive-Compulsive Disorder

Acknowledgments

A sincere thank you to Bill Bowen for his diligent proofreading of this article

Acknowledgments

We are thankful to M. Bowen, for proof-reading this manuscript in English, and to Ms. Poinsel, for your help in drawing the figure.

ACKNOWLEDGMENTS

Thank you to Ariane-Paris for supporting our study.

The disorder exists, the substrate is necessarily cerebral and yet, it is it is difficult to highlight the latter.

The reasons are numerous and can range from the acquisition tools used (MRI, PET, EEG) to the analysis tools (machine-learning) or even the way of highlighting the symptoms (at rest, with a provocation task or with a cognitive task).

Research based on the evidence published in the literature but also on the limits pointed out would increase the robustness and the possible extrapolation of our results to the general population.

AVAILABILITY OF DATA AND MATERIALS

The set of images as well as the python code are available on github at the following url: https://github.com/iCRIN-lab

DECLARATION OF COMPETING INTEREST

No competing interest

SOURCES OF SUPPORT FOR THE WORK

None

Conflict of interest

We declare no conflict of interest

Abstract

The use of invasive and non-invasive brain stimulation and neuromodulation technologies combined with neuroimaging approaches can help refine with causal evidence our physiopathological understanding of the obsessive-compulsive disorder (OCD). Two key structures, the Orbitofrontal Cortex (OFC) and the Anterior Cingulate Cortex (ACC) have been found dysfunctional in OCD compared to healthy volunteers and on such basis have been tested as therapeutic targets for invasive and non-invasive neuromodulation therapy. Hereinafter, evidence addressing the cognitive processes subtended by to those two brain regions and their role in wider associated cortico-subcortical networks is reviewed. Very specifically, their relevance for OCD clinical features is discussed in extenso and its modulation with invasive and non-invasive focal brain stimulation such as deep brain stimulation (DBS) or transcranial magnetic Stimulation (TMS). Most importantly, this article brings new insights bridging causal evidence on the structural and functional neuroanatomy subtending OCD and novel therapeutic perspectives based on focal brain stimulation.

Declaration of interest

All authors declare no competing interests. Written informed consent was obtained from the

COMPETING INTERESTS

The authors declare no competing interests