Emily R. Stern - US grants

[unreadable] DESCRIPTION (provided by applicant): Pathological uncertainty is a key feature of obsessive compulsive disorder (OCD), impairing everyday decision-making in addition to driving specific obsessions and compulsions. As a potential core process in OCD, increased uncertainty may be a trait characteristic that occurs independently of symptom provocation and could be the focus of research into treatment and prevention of the disorder. Although previous research has shown that OCD patients acquire more information in order to reach a decision than healthy controls, little work has focused on elucidating the cognitive and neural mechanisms associated with abnormal decision-making in OCD. In our preliminary study, sequential pieces of evidence were requested in order to reduce uncertainty and reach a decision. Results revealed that the cost of acquiring new information and the ambiguity of the context in which information was presented were important factors influencing subjective uncertainty and evidence accumulation among control subjects. In three studies, we will test a series of hypotheses predicting that prolonged information acquisition in OCD is driven by a relative insensitivity to these factors. In the first behavioral study, we predict that increasing OC symptom severity will be associated with greater uncertainty and increased evidence accumulation, regardless of the context and cost of information search. In the second and third studies, neural activity will be examined in healthy controls and OCD patients using functional magnetic resonance imagining (fMRI), with the aim of identifying the neural mechanisms underlying the abnormal cognitive experience or emotional appraisal of uncertainty. In particular, hyperactivity in frontal regions implicated in the pathology of OCD, such as dorsomedial prefrontal cortex/anterior cingulate cortex and orbitofrontal cortex, may underlie increases in distinct cognitive and affective aspects of uncertainty processing, respectively. Results from these studies will provide a thorough characterization of OC-related decision-making behavior, enabling clinicians to refine therapeutic techniques for treatment-resistant patients. Moreover, investigation into the neural substrates of these processes may lead to the identification of biological endophenotypes of OCD and further research on genetic susceptibilities of the disorder. The significant disability and emotional distress resulting from pathological indecisiveness in OCD constitutes an important concern for the patient as well as the health care community. The investigation of uncertainty as a core process in OCD is a promising step toward advancing treatment strategies and identifying genetic factors influencing the development of the disorder. [unreadable] [unreadable] [unreadable]

Project Summary This project investigates behavioral and neural heterogeneity in obsessive-compulsive disorder (OCD) and major depressive disorder (MDD) using hypothesis- and data-driven approaches. OCD and MDD are major sources of disability worldwide, with fewer than half of patients responding adequately to first-line treatments. Treatment may be impeded by the fact that OCD and MDD are both highly heterogeneous, with clusters of symptoms likely derived from differing psychological and neurobiological etiologies. The Research Domain Criteria (RDoC) framework seeks to address this problem in part by investigating dimensional components of behavior that span across disorders and more closely align with brain circuitry than does the multifaceted diagnostic phenotype. In the present project, we follow an RDoC approach to the study of heterogeneity by investigating relationships between behavior, clinical symptoms, and brain function using task-based and resting-state fMRI in a sample of 75 OCD patients and 75 MDD patients. Our preliminary data in OCD patients and individuals with depressive symptoms point to interoceptive sensitivity (IS) and perseverative negative thinking (PT) as dimensional components of behavior that are not only transdiagnostic but also explain important within-disorder heterogeneity; the first aim of this proposal builds on these findings by investigating associations of IS and PT with clinical symptoms, behavior, and brain function in OCD and MDD. Complementing this hypothesis-driven approach, the second aim of the project is a data-driven investigation using unsupervised machine learning (ML) to uncover neurobiological profiles that characterize variability in brain function across OCD and MDD. Building on our preliminary analysis identifying three subgroups within OCD distinguished by differential patterns of resting-state functional connectivity, we will investigate neurobiological heterogeneity across OCD and MDD and link clinical and behavioral data to neurobiological subgroups using a comprehensive ?deep phenotyping? approach to data acquisition and analysis. The overarching goals of both aims are to identify factors contributing to heterogeneity that can be developed as novel targets for personalized treatments based on an individual patient?s neurobehavioral profile.