Search

International audience; BACKGROUND: Functional magnetic resonance imaging (fMRI) capture aims at detecting auditory-verbal hallucinations (AVHs) from continuously recorded brain activity. Establishing efficient capture methods with low computational cost that easily generalize between patients remains a key objective in precision psychiatry. To address this issue, we developed a novel automatized fMRI-capture procedure for AVHs in patients with schizophrenia (SCZ). METHODS: We used a previously validated but labor-intensive personalized fMRI-capture method to train a linear classifier using machine learning techniques. We benchmarked the performances of this classifier on 2320 AVH periods versus resting-state periods obtained from SCZ patients with frequent symptoms (n = 23). We characterized patterns of blood oxygen level-dependent activity that were predictive of AVH both within and between subjects. Generalizability was assessed with a second independent sample gathering 2000 AVH labels (n = 34 patients with SCZ), while specificity was tested with a nonclinical control sample performing an auditory imagery task (840 labels, n = 20). RESULTS: Our between-subject classifier achieved high decoding accuracy (area under the curve = 0.85) and discriminated AVH from rest and verbal imagery. Optimizing the parameters on the first schizophrenia dataset and testing its performance on the second dataset led to an out-of-sample area under the curve of 0.85 (0.88 for the converse test). We showed that AVH detection critically depends on local blood oxygen level-dependent activity patterns within Broca's area. CONCLUSIONS: Our results demonstrate that it is possible to reliably detect AVH states from fMRI blood oxygen level-dependent signals in patients with SCZ using a multivariate decoder without performing complex preprocessing steps. These findings constitute a crucial step toward brain-based treatments for severe drug-resistant hallucinations.

IntroductionDeep brain stimulation (DBS) of bilateral anteromedial subthalamic nucleus (amSTN) has been found to be helpful in a subset of patients with severe, chronic and treatment-refractory obsessive–compulsive disorder (OCD). Biomarkers may aid in patient selection and optimisation of this invasive treatment. In this trial, we intend to evaluate neurocognitive function related to STN and related biosignatures as potential biomarkers for STN DBS in OCD.Methods and analysisTwenty-four subjects with treatment-refractory OCD will undergo open-label STN DBS. Structural/functional imaging, electrophysiological recording and neurocognitive assessment would be performed at baseline. The subjects would undergo a structured clinical assessment for 12 months postsurgery. A group of 24 healthy volunteers and 24 subjects with treatment-refractory OCD who receive treatment as usual would be recruited for comparison of biomarkers and treatment response, respectively. Baseline biomarkers would be evaluated as predictors of clinical response. Neuroadaptive changes would be studied through a reassessment of neurocognitive functioning, imaging and electrophysiological activity post DBS.Ethics and disseminationThe protocol has been approved by the National Institute of Mental Health and Neurosciences Ethics Committee. The study findings will be disseminated through peer-reviewed scientific journals and scientific meetings.

BACKGROUNDFunctional magnetic resonance imaging (fMRI) capture aims at detecting auditory-verbal hallucinations (AVHs) from continuously recorded brain activity. Establishing efficient capture methods with low computational cost that easily generalize between patients remains a key objective in precision psychiatry. To address this issue, we developed a novel automatized fMRI-capture procedure for AVHs in schizophrenia patients.METHODSWe used a previously validated, but labor-intensive, personalized fMRI-capture method to train a linear classifier using machine-learning techniques. We benchmarked the performances of this classifier on 2320 AVH periods vs. resting-state periods obtained from schizophrenia patients with frequent symptoms (n=23). We characterized patterns of BOLD activity that were predictive of AVH both within- and between-subjects. Generalizability was assessed with a second independent sample gathering 2000 AVH labels (n=34 schizophrenia patients), while specificity was tested with a nonclinical control sample performing an auditory imagery task (840 labels, n=20).RESULTSOur between-subject classifier achieved high decoding accuracy (area-under-the-curve, AUC = 0.85) and discriminated AVH from rest and verbal imagery. Optimizing the parameters on the first schizophrenia dataset and testing its performance on the second dataset led to a 0.85 out-of-sample AUC (0.88 for the converse test). We showed that AVH detection critically depends on local BOLD activity patterns within Broca’s area.CONCLUSIONSOur results demonstrate that it is possible to reliably detect AVH-states from BOLD signals in schizophrenia patients using a multivariate decoder without performing complex regularization procedures. These findings constitute a crucial step toward brain-based treatments for severe drug-resistant hallucinations.

Standard neuroeconomic decision theory assumes that choice is based on a value comparison process, independent from how information about alternative options is collected. Here, we investigate the opposite intuition that preferences are dynamically shaped as options are sampled, through iterative covert pairwise comparisons. Our model builds on two lines of research, one suggesting that a natural frame of comparison for the brain is between default and alternative options, the other suggesting that comparisons spread preferences between options. We therefore assumed that during sequential option sampling, people would 1) covertly compare every new alternative to the current best and 2) update their values such that the winning (losing) option receives a positive (negative) bonus. We confronted this “covert pairwise comparison” model to models derived from standard decision theory and from known memory effects. Our model provided the best account of human choice behavior in a novel task where participants (n = 92 in total) had to browse through a sequence of items (food, music or movie) of variable length and ultimately select their favorite option. Consistently, the order of option presentation, which was manipulated by design, had a significant influence on the eventual choice: the best option was more likely to be chosen when it came earlier in the sequence, because it won more covert comparisons (hence a greater total bonus). Our study provides a mechanistic understanding of how the option sampling process shapes economic preference, which should be integrated into decision theory., Author summary According to standard views in neuroeconomics, choice is a two-step process, with first the valuation of alternative options and then the comparison of subjective value estimates. Our working hypothesis is, on the contrary, that the comparison process begins during the sequential sampling of alternative options. To capture this idea, we developed a computational model, in which every new alternative is compared with the current best, so as to better contrast their values. This model provided the best account of choice behavior exhibited by participants (n = 92 in total) performing three variants of a novel multi-alternative decision task. Thus, our findings unravel a covert pairwise comparison process, occurring while participants collect information about alternative options, before they are requested to make their choice. They also provide explanations about when this covert process is implemented (when resampling is too costly), why it is implemented (to better discriminate the best options) and how it can bias decisions (because it favors first-encountered valuable options).

In uncertain environments, accurate decision-making requires integrating ambiguous or conflicting signals – a cognitive inference process thought to require n-methyl-d-aspartate (NMDA) synaptic receptors. Here we characterized the causal impact of human NMDA receptor hypofunction on cognitive inference using placebo-controlled infusions of ketamine in a visual cue combination task. Participants tested under ketamine showed elevated uncertainty, together with impaired cognitive inference despite intact visual processing. This behavioral effect of ketamine was associated in patterns of electrical brain activity with degraded and unbalanced coding of presented cues in associative cortex, followed by premature response preparation in motor cortex. Through quantitative simulations, we propose that these cognitive alterations reflect an urge to explain away the elevated uncertainty triggered by ketamine. This compensatory mechanism may cause the emergence of psychotic symptoms observed under chronic NMDA receptor dysfunction, but also forge unusually strong beliefs when confronted with uncertainty in everyday life.

To continue or to switch strategy? Successful behavior in an uncertain, changing, and open-ended environment critically relies on the ability to decide between continuing with the ongoing strategy or exploring new options. Neuroimaging studies have shown that the human medial prefrontal cortex (mPFC) is the part of the brain that primarily deals with this dilemma. However, the contribution of the different mPFC regions remains largely unknown. Domenech et al. recorded neuronal activity in six epileptic patients with depth electrodes in this brain area (see the Perspective by Steixner-Kumar and Gläscher). The ventral mPFC inferred the reliability of the ongoing action plan according to action outcomes. It proactively flagged outcomes either as learning signals to better exploit this plan or as potential triggers to explore new ones. The dorsal mPFC then evaluated action outcomes and generated an adaptive behavioral strategy. Science , this issue p. eabb0184 ; see also p. 1056

Parkinson's disease is typically treated with oral dopamine replacement therapies. However, long-term use is complicated by motor fluctuations from intermittent stimulation of dopamine receptors and off-target effects. ProSavin, a lentiviral vector based gene therapy that delivers local and continuous dopamine, was previously shown to be well tolerated in a Phase I/II first-in-human study, with significant improvements in motor behavior from baseline at 1 year. Here, patients with Parkinson's disease from the open-label trial were followed up in the long term to assess the safety and efficacy of ProSavin after bilateral injection into the putamen. Fifteen patients who were previously treated with ProSavin have been followed for up to 5 years, with some having been seen for 8 years. Eight patients received deep brain stimulation at different time points, and their subsequent assessments continued to assess safety. Ninety-six drug-related adverse events were reported (87 mild, 6 moderate, 3 severe) of which more than half occurred in the first year. The most common drug-related events were dyskinesias (33 events, 11 patients) and on-off phenomena (22 events, 11 patients). A significant improvement in the defined "off" Unified Parkinson's Disease Rating Scale part III motor scores, compared to baseline, was seen at 2 years (mean score 29 · 2 vs. 38 · 4, n = 14, p < 0.05) and at 4 years in 8/15 patients. ProSavin continued to be safe and well tolerated in patients with Parkinson's disease. Moderate improvements in motor behavior over baseline continued to be reported in the majority of patients who could still be evaluated up to 5 years of follow-up.

International audience; Vagus nerve stimulation (VNS) is an old, yet new, option for treatment-resistant depression. Despite several clinical trials over the last 15 years showing a consistent benefit-risk balance of the technic, VNS still struggles to find its place in our therapeutic algorithms. This is especially true in France, where only a few surgeries have been performed nationwide, all in the last year. The reasons behind this lag are manifolds; (1) psychiatrists usually do not consider surgical treatments, even when they are minimally invasive and reversible, (2) early VNS trials stumbled on methodological difficulties that are common to all invasive neurostimulation technics, and initially failed to provide strong evidence for its efficacy, and (3) VNS requires multidisciplinary teams involving psychiatrists and neurosurgeons that did not exist then. Nevertheless, studies of the past twenty years support VNS as a treatment of depression endowed with a unique efficacy profile: a long runner best at maintaining remission in hard-to-stabilize depression, even in the context of ECT withdrawal, and irrespective of whether it is unipolar or bipolar. Thus, VNS potentially addresses the unmet medical needs of some of the most severe and chronic patients with depression. This review aims at introducing VNS as a treatment option for depression, summarizing available evidence for its efficacy and tolerance, and delineating patient profiles that might benefit the most of such treatment.

Vagus nerve stimulation (VNS) is an old, yet new, option for treatment-resistant depression. Despite several clinical trials over the last 15 years showing a consistent benefit-risk balance of the technic, VNS still struggles to find its place in our therapeutic algorithms. This is especially true in France, where only a few surgeries have been performed nationwide, all in the last year. The reasons behind this lag are manifolds; (1) psychiatrists usually do not consider surgical treatments, even when they are minimally invasive and reversible, (2) early VNS trials stumbled on methodological difficulties that are common to all invasive neurostimulation technics, and initially failed to provide strong evidence for its efficacy, and (3) VNS requires multidisciplinary teams involving psychiatrists and neurosurgeons that did not exist then. Nevertheless, studies of the past twenty years support VNS as a treatment of depression endowed with a unique efficacy profile: a long runner best at maintaining remission in hard-to-stabilize depression, even in the context of ECT withdrawal, and irrespective of whether it is unipolar or bipolar. Thus, VNS potentially addresses the unmet medical needs of some of the most severe and chronic patients with depression. This review aims at introducing VNS as a treatment option for depression, summarizing available evidence for its efficacy and tolerance, and delineating patient profiles that might benefit the most of such treatment.

International audience; Estimating the value of alternative options is a key process in decision-making. Human functional magnetic resonance imaging and monkey electrophysiology studies have identified brain regions, such as the ventromedial prefrontal cortex (vmPFC) and lateral orbitofrontal cortex (lOFC), composing a value system. In the present study, in an effort to bridge across species and techniques, we investigated the neural representation of value ratings in 36 people with epilepsy, using intracranial electroencephalography. We found that subjective value was positively reflected in both vmPFC and lOFC high-frequency activity, plus several other brain regions, including the hippocampus. We then demonstrated that subjective value could be decoded (1) in pre-stimulus activity, (2) for various categories of items, (3) even during a distractive task and (4) as both linear and quadratic signals (encoding both value and confidence). Thus, our findings specify key functional properties of neural value signals (anticipation, generality, automaticity, quadraticity), which might provide insights into human irrational choice behaviors.

The ability to infer other people’s intentions is crucial for successful human social interactions. Such inference relies on an adaptive interplay of sensory evidence and prior expectations. Crucially, this interplay would also depend on the type of intention inferred, i.e., on how abstract the intention is. However, what neural mechanisms adjust the interplay of prior and sensory evidence to the abstractness of the intention remains conjecture. We addressed this question in two separate fMRI experiments, which exploited action scenes depicting different types of intentions (Superordinate vs. Basic; Social vs. Non-social), and manipulated both prior and sensory evidence. We found that participants increasingly relied on priors as sensory evidence became scarcer. Activity in the medial prefrontal cortex (mPFC) reflected this interplay between the two sources of information. Moreover, the more abstract the intention to infer (Superordinate > Basic, Social > Non-Social), the greater the modulation of backward connectivity between the mPFC and the temporo-parietal junction (TPJ), resulting in an increased influence of priors over the intention inference. These results suggest a critical role for the fronto-parietal network in adjusting the relative weight of prior and sensory evidence during hierarchical intention inference.

The prefrontal cortex (PFC) subserves decision-making and executive control. Here we review recent empirical and modeling works with a focus on neuroimaging studies, which start unifying these two conceptual approaches of PFC function. We propose that the PFC comprises two arbitration systems: (1) a peripheral system comprising premotor/caudal PFC regions and orbitofrontal regions involved in the selection of actions based on perceptual cues and reward values, respectively, and embedded in behavioral sets associated with external contingencies inferred as being stable; (2) a core system comprising ventromedial, dorsomedial, lateral and polar PFC regions involved in superordinate probabilistic reasoning for arbitrating online between exploiting/adjusting previously learned behavioral sets and exploring/creating new ones for efficient adaptive behavior in variable and open-ended environments.

BackgroundPathological gambling (PG) is an impulse control disorder characterized by excessive monetary risk seeking in the face of negative consequences. We used tools from the field of behavioral economics to refine our description of risk-taking behavior in pathological gamblers. This theoretical framework allowed us to confront two hypotheses: (1) pathological gamblers distort winning probabilities more than controls; and (2) pathological gamblers merely overweight the whole probability range.MethodEighteen pathological gamblers and 20 matched healthy participants performed a decision-making task involving choices between safe amounts of money and risky gambles. The online adjustment of safe amounts, depending on participants' decisions, allowed us to compute ‘certainty equivalents’ reflecting the subjective probability weight associated with each gamble. The behavioral data were then fitted with a mathematical function known as the ‘probability weighting function’, allowing us to disentangle our two hypotheses.ResultsThe results favored the second hypothesis, suggesting that pathological gamblers' behavior reflects economic preferences globally shifted towards risk, rather than excessively distorted probability weighting. A mathematical parameter (elevation parameter) estimated by our fitting procedure was found to correlate with gambling severity among pathological gamblers, and with gambling affinity among controls.ConclusionsPG is associated with a specific pattern of economic preferences, characterized by a global (i.e. probability independent) shift towards risky options. The observed correlation with gambling severity suggests that the present ‘certainty equivalent’ task may be relevant for clinical use.

International audience; Perceptual decisions are made when sensory evidence accumulated over time reaches a decision threshold. Because decisions are also guided by prior information, one important factor that is likely to shape how a decision is adaptively tuned to its context is the predictability of forthcoming events. However, little is known about the mechanisms underlying this contextual regulation of the perceptual decision-making process. Mathematical models of decision making predict two possible mechanisms supporting this regulation: an adjustment of the distance to the decision threshold, which leads to a change in the amount of accumulated evidence required to make a decision, or a gain control of the sensory evidence, leading to a change in the slope of the sensory evidence accumulation. Here, we show that predictability of the forthcoming event reduces the distance to the threshold of the decision. Then, combining model-driven fMRI and the framework of information theory, we show that the anterior cingulate cortex (ACC) adjusts the distance to the decision threshold in proportion to the current amount of predictive information and that the dorsolateral cortex (DLPFC) codes the accumulation of sensory evidence. Moreover, the information flow from the ACC to the DLPFC region that accumulates sensory evidence increases when optimal adjustment of the distance to the threshold requires more complex computations, reflecting the increased weight of ACC's regulation signals in the decision process. Our results characterize the respective contributions of the ACC and the DLPFC to contextually optimized decision making.

International audience; Background: Slowness in movement initiation (akinesia) is a cardinal feature of Parkinson's disease (PD), which is still poorly understood. Notably, akinesia is restored by subthalamic nucleus deep brain stimulation (STN-DBS) but not fully reversed by current dopaminergic treatments. It was recently suggested that this disorder is of executive nature (related to inhibitory control of response) and of non-dopaminergic origin (possibly noradrenergic). Objective: To test the double hypothesis that: 1) the ability to control movement initiation is modified by noradrenergic neurotransmission modulation, and 2) this effect is mediated by the regulation of STN activity. Methods: Sixteen STN-DBS PD patients were enrolled in a placebo-controlled study investigating the effects of noradrenergic attenuation by clonidine (f2-adrenergic receptor agonist). Movement initiation latency was assessed by means of a cue-target reaction time task. Patients, who remained on their chronic dopaminergic medication, were tested on four sessions: two with placebo (ON-or OFF-DBS), and two with a 150 mg oral dose of clonidine (ON-or OFF-DBS). Results: In the OFF stimulation condition, patients were locked into a mode of control maintaining inappropriate response inhibition. This dysfunctional executive setting was overcome by STN-DBS. Clonidine, however, was found to impair specifically the ability to release inhibitory control in the ON-DBS state. Conclusions: Overall our results suggest an important implication of the noradrenergic system in the pathophysiology of akinesia in PD. Reducing the noradrenergic "tonus" may even block the positive action of STN-DBS on akinesia, suggesting, at least by part, a noradrenergic-dependent STN-DBS efficiency.

Pathological gambling is an addictive disorder characterized by a persistent and compulsive desire to engage in gambling activities. This maladaptive behaviour has been suggested to result from a decreased sensitivity to experienced rewards, regardless of reward type. Alternatively, pathological gambling might reflect an imbalance in the sensitivity to monetary versus non-monetary incentives. To directly test these two hypotheses, we examined how the brain reward circuit of pathological gamblers responds to different types of rewards. Using functional magnetic resonance imaging, we compared the brain responses of 18 pathological gamblers and 20 healthy control subjects while they engaged in a simple incentive task manipulating both monetary and visual erotic rewards. During reward anticipation, the ventral striatum of pathological gamblers showed a differential response to monetary versus erotic cues, essentially driven by a blunted reactivity to cues predicting erotic stimuli. This differential response correlated with the severity of gambling symptoms and was paralleled by a reduced behavioural motivation for erotic rewards. During reward outcome, a posterior orbitofrontal cortex region, responding to erotic rewards in both groups, was further recruited by monetary gains in pathological gamblers but not in control subjects. Moreover, while ventral striatal activity correlated with subjective ratings assigned to monetary and erotic rewards in control subjects, it only correlated with erotic ratings in gamblers. Our results point to a differential sensitivity to monetary versus non-monetary rewards in pathological gambling, both at the motivational and hedonic levels. Such an imbalance might create a bias towards monetary rewards, potentially promoting addictive gambling behaviour.

The aim of this study was to estimate the prevalence of psychostimulant use in the French medical community and their motives. A population-based cross-sectional study using a self-administered online survey was done. A total of 1718 French students and physicians (mean age, 26.84±7.19 years, 37.1% men) were included. Self-reported lifetime use, motives, socio-demographic and academic features for over the counter (OTC), medically prescribed (MPP), and illicit (IP) psychostimulant users were reported. Lifetime prevalence of psychostimulant use was 33% (29.7% for OTC, 6.7% for MPP, and 5.2% for IP). OTC consumption mainly aimed at increasing academic performance and wakefulness during competitive exams preparation. OTC consumption started early and was predictive of later MPP use. Corticoids were the most frequently consumed MPP (4.5%) before methylphenidate and modafinil. Motives for MPP consumption were increased academic performance, concentration, memory, and wakefulness. Psychostimulant use is common among French medical community. Our results suggest that restrictions on methylphenidate and modafinil prescriptions are effective at limiting their use. However, these restrictions may explain the observed rates of corticoids consumption, which raise a new public health problem, given that corticoids may have severe side effects.

International audience; BACKGROUND: In schizophrenia, disturbances of cognitive control have been associated with impaired functional specialization within the lateral prefrontal cortex (LPFC), but little is known about the functional interactions between specialized LPFC subregions. Here, we addressed this question with a recent model that describes the LPFC functioning as a cascade of control processes along a rostrocaudal axis, whereby anterior frontal regions influence the processing in posterior frontal regions to guide action selection on the basis of the temporal structure of information. METHODS: We assessed effective connectivity within the rostrocaudal axis of the LPFC by means of functional magnetic resonance imaging in 15 schizophrenic patients and 14 matched healthy control subjects with structural equation modeling and psychophysiological interactions. RESULTS: In healthy subjects, activity in the left caudal LPFC regions was under the influence of left rostral LPFC regions when controlling information conveyed by past events. By contrast, schizophrenic patients failed to demonstrate significant effective connectivity from rostral to caudal LPFC regions in both hemispheres. CONCLUSIONS: The hierarchical control along the rostrocaudal axis of the LPFC is impaired in schizophrenia. This provides the first evidence of a top-down functional disconnection within the LPFC in this disorder. This disruption of top-down connectivity from rostral to caudal LPFC regions observed in patients might affect their ability to select the appropriate sets of stimulus-response associations in the caudal LPFC on the basis of information conveyed by past events. This impaired hierarchical control within the LPFC could result from poorly encoded contextual information due to abnormal computations in the caudal LPFC.

pected. on readmission to the obstetric ward, her treatment included risperidone (2 mg/day), alprazolam (1.5 mg/day), the phenothiazine antipsychotic cyamemazine (62.5 mg/day), and the anticholinergic tropatepine (10 mg/day). Antibiotic treatment was started to treat a possible infection. Unlike in her previous postpartum episodes, Mrs. G’s mental status responded only partially to antipsychotic treatment. A liaison psychiatry consultation was requested. the liaison psychiatrist found a mildly agitated and disoriented young woman who had wet herself and was circling around her bed. the patient was logorrheic, and her speech, which was mostly incoherent, revealed memory impairment. Strikingly, this mild state of confusion fluctuated during the interview, confirming midwives’ reports of hourly changes in the patient’s behavior. Mrs. G anxiously expressed feelings of guilt toward her newborn and the belief that her diagnosis of postpartum psychosis made her less able to take care of her children. She displayed no anger toward her children and no ideas of persecution, infanticide, or suicide. She also expressed the belief that “God talks to humankind through premonitory dreams or providential meetings,” a claim that had previously been interpreted as a mystic delusion. However, it appeared that this view was part of her cultural and religious background, as was later confirmed by her husband, who reported that she had held this belief for a long time and that it was shared by her relatives. overall, Mrs. G was more confused and less delusional than one would have expected in a typical postpartum psychosis. Puzzled by this clinical picture, the psychiatrist reconsidered the diagnosis of postpartum psychosis and extended his examination to assess the differential diagnosis. He found that Mrs. G had chronic headaches and a habitual reluctance to consume meat. His clinical examination revealed little; the patient had a well-tolerated fever, stable blood pressure and pulse, and no signs of severe sepsis. A neurological examination was unremarkable. the psychiatrist ordered immediate blood tests, including ammonia levels. Within an hour, hyperammonemia was confirmed (224 μmol/liter, controls

International audience; Explaining or predicting the behaviour of our conspecifics requires the ability to infer the intentions that motivate it. Such inferences are assumed to rely on two types of information: (1) the sensory information conveyed by movement kinematics and (2) the observer's prior expectations - acquired from past experience or derived from prior knowledge. However, the respective contribution of these two sources of information is still controversial. This controversy stems in part from the fact that "intention" is an umbrella term that may embrace various sub-types each being assigned different scopes and targets. We hypothesized that variations in the scope and target of intentions may account for variations in the contribution of visual kinematics and prior knowledge to the intention inference process. To test this hypothesis, we conducted four behavioural experiments in which participants were instructed to identify different types of intention: basic intentions (i.e. simple goal of a motor act), superordinate intentions (i.e. general goal of a sequence of motor acts), or social intentions (i.e. intentions accomplished in a context of reciprocal interaction). For each of the above-mentioned intentions, we varied (1) the amount of visual information available from the action scene and (2) participant's prior expectations concerning the intention that was more likely to be accomplished. First, we showed that intentional judgments depend on a consistent interaction between visual information and participant's prior expectations. Moreover, we demonstrated that this interaction varied according to the type of intention to be inferred, with participant's priors rather than perceptual evidence exerting a greater effect on the inference of social and superordinate intentions. The results are discussed by appealing to the specific properties of each type of intention considered and further interpreted in the light of a hierarchical model of action representation.

Sir, In a recent study (Chambon et al ., 2011), we investigated the ability of patients with schizophrenia to make accurate predictions about other people’s intentions. This ability has long been shown to be impaired in schizophrenia, and this impairment may be accounted for by an abnormal integration of two different sources of information: the sensory evidence conveyed by movement kinematics, and the observer’s expectations about how likely an intention is. In the task, these two types of information were systematically varied. Our results showed that patients with positive symptoms were prone to over-weight sensory evidence confirming their prior expectations and to disregard evidence that invalidated such priors. We hypothesized that this abnormal interplay of prior expectations and current sensory experiences—that normally guarantee accurate inferences—could result from a disturbance in prediction error signalling, possibly caused by alterations in the dopaminergic circuitry. We speculated that such aberrant prediction error signals might account for the formation, as well as for the update, of delusional beliefs as to how biological agents are most likely to behave. In their comment, Garrett and Singh suggest …

The aetiology of psychiatric disorders remains poorly understood, despite significant progress in neurosciences and psychopharmacology. These approaches might be limited by their lack of causal account linking psychiatric symptoms and neurobiological data. This dissertation presents a new theoretical approach of psychopathology, i.e. computational psychiatry, that aims to develop and test hypotheses about the algorithms that the brain implements to produce observable behavior. To that purpose, we review two major computational models. First, models from reinforcement learning and neuro-economics give a novel account of symptoms as a decision making process gone awry (such as addiction, impulsiveness, compulsions or apathy). Then, we examine how Bayesian modeling of probabilistic inference enlightens psychotic symptoms. Finally, we discuss the limitations and future applications of computational approaches in psychiatry.; L’étiologie des maladies psychiatriques est encore mal connue, malgré d’importants progrès en neurosciences et en psychopharmacologie. La limite que rencontrent ces approches tient probablement à l’absence de modèles explicatifs permettant de lier causalement les symptômes psychiatriques et les données neurobiologiques. Cette thèse aborde une nouvelle approche théorique de la psychopathologie, la psychiatrie computationnelle, dont l’objectif est de proposer et de tester empiriquement des hypothèses quant aux algorithmes implémentés par le cerveau, à l’origine des comportements observés. Pour cela, nous présentons deux grands types de modèles computationnels. Premièrement, les modèles issus de l’apprentissage par renforcement et de la neuro-économie, permettent de redéfinir les symptômes traduisant une altération de la prise de décision (addiction, impulsivité, compulsions, apathie). Deuxièmement, nous examinons en quoi les modèles bayésiens d’inférence probabiliste apportent un éclairage sur les symptômes psychotiques. Enfin, nous discutons dans un troisième temps les limites et perspectives de l’approche computationnelle en psychiatrie.