SEEG と刺激を利用した OCD バイオマーカー調査: OBSESS 試験

Traditional strategies for diagnosing psychiatric disorders focus on definitions based on constellations of co-occurring symptoms. Tracking symptom severity across therapy arcs relies on administering scales that again ask questions about symptoms. These strategies have allowed some degree of standardization but suffer from having a phenomenological rather than mechanistic foundation (in terms of diagnosis) as well as subjectivity and temporal sparseness (in terms of measurement).

The investigators apply a transdiagnostic framework based on the neurobiological concept of approach behavior. Several psychiatric disorders (including OCD, uni- and bipolar depression, PTSD and anxiety disorders, and addiction disorders) are characterized by dysfunction in approach behavior. The investigators study the neurobehavioral basis of approach dysfunction in a cohort of individuals with severe OCD and bipolar disorder (BD). To study these behaviors, the investigators deploy a suite of wearables and peripherals (Oura ring, Apple Watch, iPhone, audioband) that allow continuous and dense measurement of behaviors relevant to the approach hypothesis: socialization, activity, and sleep patterns. The investigators perform these measurements in two selected environments. One is a novel apartment-style setting (neurobehavioral unit, NBU) that combines the high-bandwidth data acquisition capability of a lab with the naturalistic relevance and comfort of the home. The second is the truly natural and maximally ethologically relevant setting of the ambulatory "home" environment in which people spend the majority of their time.

The participants will be individuals planned for deep brain stimulation (DBS) implant for their OCD or BD. The bi-directional (stimulate as well as record) nature of the DBS systems will allow neural recordings that the investigators will synchronize with the behavioral data streams. The investigators will apply predictive computational models in conjunction with the causal manipulation provided by stimulation to test mechanistic hypothesis relating neurophysiology, behavior, and clinical status. In Aim 1, The investigators study reward-driven decision making by employing an augmented reality approach-avoidance task in the NBU. In Aim 2, the investigators test the neurobehavioral models' ability to predict clinical status from passively (and therefore low burden to patient-participants) acquired data in the "home" environment. In Aim 3, the investigators identify neural predictors of the patterns of sleep dysregulation associated with these disorders using the unique environment of the NBU. In Aim 4, the investigators examine critical concepts of ethics and ethology that arise with this new field of naturalistic, chronic brain-behavior relationship investigation.

The investigators hope that methods validated and lessons learned in this project will improve understanding of the mechanistic basis of a range of psychiatric disorders and thereby allow greater rational design of therapeutic delivery.