Treatment-resistant depression is a severely disabling disorder with no proven treatment options once multiple medications, psychotherapy, and electroconvulsive therapy have failed. Based on our preliminary observation that the subgenual cingulate region (Brodmann area 25) is metabolically overactive in treatment-resistant depression, we studied whether the application of chronic deep brain stimulation to modulate BA25 could reduce this elevated activity and produce clinical benefit in six patients with refractory depression. Chronic stimulation of white matter tracts adjacent to the subgenual cingulate gyrus was associated with a striking and sustained remission of depression in four of six patients. Antidepressant effects were associated with a marked reduction in local cerebral blood flow as well as changes in downstream limbic and cortical sites, measured using positron emission tomography. These results suggest that disrupting focal pathological activity in limbic-cortical circuits using electrical stimulation of the subgenual cingulate white matter can effectively reverse symptoms in otherwise treatment-resistant depression.

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.

Context: An association between dopamine-replacement therapies and impulse control disorders (ICDs) in Parkinson disease (PD) has been suggested in preliminary studies. Objectives: To ascertain point prevalence estimates of 4 ICDs in PD and examine their associations with dopamine-replacement therapies and other clinical characteristics. Design: Cross-sectional study using an a priori established sampling procedure for subject recruitment and raters blinded to PD medication status. Patients: Three thousand ninety patients with treated idiopathic PD receiving routine clinical care at 46 movement disorder centers in the United States and Canada. Main Outcome Measures: The Massachusetts Gambling Screen score for current problem/pathological gambling, the Minnesota Impulsive Disorders Interview score for compulsive sexual behavior and buying, and Diagnostic and Statistical Manual of Mental Disorders research criteria for binge-eating disorder. Results: An ICD was identified in 13.6% of patients (gambling in 5.0%, compulsive sexual behavior in 3.5%, compulsive buying in 5.7%, and binge-eating disorder in 4.3%), and 3.9% had 2 or more ICDs. Impulse control disorders were more common in patients treated with a dopamine agonist than in patients not taking a dopamine agonist (17.1% vs 6.9%; odds ratio [OR], 2.72; 95% confidence interval [CI], 2.08-3.54; PϽ .001). Impulse control disorder frequency was similar for pramipexole and ropinirole (17.7% vs 15.5%; OR, 1.22; 95% CI, 0.94-1.57; P =.14). Additional variables independently associated with ICDs were levodopa use, living in the United States, younger age, being unmarried, current cigarette smoking, and a family history of gambling problems. Conclusions: Dopamine agonist treatment in PD is associated with 2-to 3.5-fold increased odds of having an ICD. This association represents a drug class relationship across ICDs. The association of other demographic and clinical variables with ICDs suggests a complex relationship that requires additional investigation to optimize prevention and treatment strategies.

IMPORTANCE-Functional neurological disorders (FND) are common sources of disability in medicine. Patients have often been misdiagnosed, correctly diagnosed after lengthy delays, and/or subjected to poorly delivered diagnoses that prevent diagnostic understanding and lead to inappropriate treatments, iatrogenic harm, unnecessary and costly evaluations, and poor outcomes. OBSERVATIONS-Functional Neurological Symptom Disorder/Conversion Disorder was adopted by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, replacing the term psychogenic with functional and removing the criterion of psychological stress as a Funding/Support: This article presents independent research part-funded by the

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...

Impulsivity and compulsivity represent useful conceptualizations that involve dissociable cognitive functions, mediated by neuroanatomically and neurochemically distinct components of cortico-subcortical circuitry. The constructs were historically viewed as diametrically opposed, with impulsivity being associated with risk-seeking and compulsivity with harm-avoidance. However, they are increasingly recognized to be linked by shared neuropsychological mechanisms involving dysfunctional inhibition of thoughts and behaviors. In this paper, we selectively review new developments in the investigation of the neurocognition of impulsivity and compulsivity in humans, in order to advance our understanding of the pathophysiology of impulsive, compulsive and addictive disorders and indicate new directions for research.

range of behaviors presumed to be related to aberrant or excessive dopaminergic medications are being increasingly recognized in Parkinson disease. These behaviors are linked by their incentive-or reward-based and repetitive natures and include pathological gambling, hypersexuality, compulsive shopping, compulsive eating, hobbyism, and compulsive medication use. Such behaviors can have potentially devastating psychosocial consequences and are often hidden. Whether these behaviors are simply related to dopaminergic medications interacting with an underlying individual vulnerability or whether the primary pathological features of Parkinson disease play a role is not known. We reviewed the literature on these behaviors in Parkinson disease, including definitions, epidemiological and potential pathophysiological features, and management. The study of these behaviors allows not only improved clinical management but also greater insight into a biologically mediated complex behavioral model.

We surveyed 297 patients with Parkinson disease (PD) with systematic screens and rigorous definitional criteria. Pathologic hypersexuality lifetime prevalence was 2.4%. Compulsive shopping was 0.7%. Combined with our pathologic gambling data, the lifetime prevalence of these behaviors was 6.1% and increases to 13.7% in patients on dopamine agonists.