Why do we repeat choices that we know are bad for us? Decision making is characterized by the parallel engagement of two distinct systems, goal-directed and habitual, thought to arise from two computational learning mechanisms, model-based and model-free. The habitual system is a candidate source of pathological fixedness. Using a decision task that measures the contribution to learning of either mechanism, we show a bias towards model-free (habit) acquisition in disorders involving both natural (binge eating) and artificial (methamphetamine) rewards, and obsessive-compulsive disorder. This favoring of model-free learning may underlie the repetitive behaviors that ultimately dominate in these disorders. Further, we show that the habit formation bias is associated with lower gray matter volumes in caudate and medial orbitofrontal cortex. Our findings suggest that the dysfunction in a common neurocomputational mechanism may underlie diverse disorders involving compulsion.

Highlights d Three groups of highly genetically-related disorders among 8 psychiatric disorders d Identified 109 pleiotropic loci affecting more than one disorder d Pleiotropic genes show heightened expression beginning in 2 nd prenatal trimester d Pleiotropic genes play prominent roles in neurodevelopmental processes Authors Cross-Disorder Group of the Psychiatric Genomics Consortium

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Functional connectivity analysis of resting state blood oxygen level-dependent (BOLD) functional MRI is widely used for noninvasively studying brain functional networks. Recent findings have indicated, however, that even small (≤1 mm) amounts of head movement during scanning can disproportionately bias connectivity estimates, despite various preprocessing efforts. Further complications for interregional connectivity estimation from time domain signals include the unaccounted reduction in BOLD degrees of freedom related to sensitivity losses from high subject motion. To address these issues, we describe an integrated strategy for data acquisition, denoising, and connectivity estimation. This strategy builds on our previously published technique combining data acquisition with multiecho (ME) echo planar imaging and analysis with spatial independent component analysis (ICA), called ME-ICA, which distinguishes BOLD (neuronal) and non-BOLD (artifactual) components based on linear echo-time dependence of signals-a characteristic property of BOLD T p 2 signal changes. Here we show for 32 control subjects that this method provides a physically principled and nearly operator-independent way of removing complex artifacts such as motion from resting state data. We then describe a robust estimator of functional connectivity based on interregional correlation of BOLD-independent component coefficients. This estimator, called independent components regression, considerably simplifies statistical inference for functional connectivity because degrees of freedom equals the number of independent coefficients. Compared with traditional connectivity estimation methods, the proposed strategy results in fourfold improvements in signal-to-noise ratio, functional connectivity analysis with improved specificity, and valid statistical inference with nominal control of type 1 error in contrasts of connectivity between groups with different levels of subject motion.resting state fMRI | human neuroimaging | time series R esting state experiments typically involve a short period (i.e., 10 min) of blood oxygen level-dependent (BOLD) functional MRI (fMRI) scanning while participants lie in the scanner without experimental control over brain function. The data show low-frequency (f ≤ 0.1 Hz) oscillations indicative of spontaneous brain activity. Functional connectivity between brain regions is then typically estimated by the correlation between time series (1). Unfortunately, resting state fMRI is highly susceptible to artifacts. It has recently been shown that small (≤1 mm) and transient movements of the subject's head during scanning can bias estimates of time series correlation for long distance anatomical connections, even after the data have been preprocessed by traditional methods (2-4). The effects of head motion and related artifacts are problematic especially for studies of very young or elderly subjects or patients with neuropsychiatric disorders, all of whom demonstrate a greater extent of head movement than healthy adults.Current pr...

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Pathological gambling (PG) related to dopaminergic treatment in Parkinson's disease (PD) is part of a spectrum of behavioral disorders called the dopamine dysregulation syndrome (DDS). We describe a series of PD patients with preoperative active PG due to dopaminergic treatment from a total of 598 patients who have undergone surgery for subthalamic nucleus stimulation for disabling motor fluctuations. The patients had systematic open assessment of behavioral symptoms and standardized assessments of motor symptoms, mood, and apathy. Seven patients (6 men, 1 woman; age, 54 +/- 9 years; levodopa equivalent dose, 1,390 +/- 350 mg/day) had preoperative PG over a mean of 7 years, intolerant to reduction in medication. Six had nonmotor fluctuations and four had other behavioral symptoms consistent with a diagnosis of the DDS. After surgery, motor symptoms improved, allowing for 74% reduction of dopaminergic treatment, below the dosage of gambling onset. In all patients, PG resolved postoperatively after 18 months on average (range, 0-48), although transient worsening occurred in two. Improvement paralleled the time course and degree of reduction in dopaminergic treatment. Nonmotor fluctuations, off period dysphoria, and other symptoms of the DDS improved. Two patients developed persistent apathy. In conclusion, PG and other symptoms of the DDS-associated dopaminergic treatment improved in our patients following surgery. Dopaminergic dysregulation commonly attributed to pulsatile overstimulation of the limbic dopaminergic system may be subject to desensitization on chronic subthalamic stimulation, which has a relative motor selectivity and allows for decrease in dopaminergic treatment.

Tics are sometimes described as voluntary movements performed in an automatic or habitual way. Here, we addressed the question of balance between goal-directed and habitual behavioural control in Gilles de la Tourette syndrome and formally tested the hypothesis of enhanced habit formation in these patients. To this aim, we administered a three-stage instrumental learning paradigm to 17 unmedicated and 17 antipsychotic-medicated patients with Gilles de la Tourette syndrome and matched controls. In the first stage of the task, participants learned stimulus-response-outcome associations. The subsequent outcome devaluation and 'slip-of-action' tests allowed evaluation of the participants' capacity to flexibly adjust their behaviour to changes in action outcome value. In this task, unmedicated patients relied predominantly on habitual, outcome-insensitive behavioural control. Moreover, in these patients, the engagement in habitual responses correlated with more severe tics. Medicated patients performed at an intermediate level between unmedicated patients and controls. Using diffusion tensor imaging on a subset of patients, we also addressed whether the engagement in habitual responding was related to structural connectivity within cortico-striatal networks. We showed that engagement in habitual behaviour in patients with Gilles de la Tourette syndrome correlated with greater structural connectivity within the right motor cortico-striatal network. In unmedicated patients, stronger structural connectivity of the supplementary motor cortex with the sensorimotor putamen predicted more severe tics. Overall, our results indicate enhanced habit formation in unmedicated patients with Gilles de la Tourette syndrome. Aberrant reinforcement signals to the sensorimotor striatum may be fundamental for the formation of stimulus-response associations and may contribute to the habitual behaviour and tics of this syndrome.

Theories of instrumental learning aim to elucidate the mechanisms that integrate success and failure to improve future decisions. One computational solution consists of updating the value of choices in proportion to reward prediction errors, which are potentially encoded in dopamine signals. Accordingly, drugs that modulate dopamine transmission were shown to impact instrumental learning performance. However, whether these drugs act on conscious or subconscious learning processes remains unclear. To address this issue, we examined the effects of dopamine-related medications in a subliminal instrumental learning paradigm. To assess generality of dopamine implication, we tested both dopamine enhancers in Parkinson's disease (PD) and dopamine blockers in Tourette's syndrome (TS). During the task, patients had to learn from monetary outcomes the expected value of a risky choice. The different outcomes (rewards and punishments) were announced by visual cues, which were masked such that patients could not consciously perceive them. Boosting dopamine transmission in PD patients improved reward learning but worsened punishment avoidance. Conversely, blocking dopamine transmission in TS patients favored punishment avoidance but impaired reward seeking. These results thus extend previous findings in PD to subliminal situations and to another pathological condition, TS. More generally, they suggest that pharmacological manipulation of dopamine transmission can subconsciously drive us to either get more rewards or avoid more punishments.dopamine ͉ instrumental learning ͉ subliminal perception ͉ reward ͉ punishment H ow we learn from success and failure is a long-standing question in neuroscience. Instrumental learning theories explain how outcomes can be used to modify the value of choices, such that better decisions are made in the future. A basic learning mechanism consists of updating the value of the chosen option according to a reward prediction error, which is the difference between the actual and the expected reward (1, 2). This learning rule, using prediction error as a teaching signal, has provided a good account of instrumental learning in a variety of species including both human and nonhuman primates (3, 4). Single-cell recordings in monkeys suggest that reward prediction errors are encoded by the phasic discharge of dopamine neurons (5, 6). In humans, dopamine-related drugs have been shown to bias prediction error encoding in the striatum to modulate reward-based learning (7). One of these drugs, levodopa (a metabolic precursor of dopamine), is used to alleviate motor symptoms in idiopathic Parkinson's disease (PD), which is primarily caused by degeneration of nigral dopamine neurons. PD patients were shown to learn better from positive feedback when on levodopa and from negative feedback when off levodopa (8, 9). This double dissociation lead Frank and colleagues to propose a computational model of fronto-striatal circuits where dopamine bursts (encoding positive prediction errors) reinforce approach pathways,...