Neurophysiological Investigation of the Approach-avoidance Axis in OCD: Applications to Neuromodulation

We will collect a broad array of neurobehavioral data across two environments with complementary advantages: the clinic and the home. The first 2 Aims test our mechanistic hypothesis by studying the pattern of VS neural activity in the controlled environment of the lab/clinic during two complementary paradigms: one based on a psychophysical behavioral task, the other based on ERP, a therapeutic behavioral intervention. The third aim tests this hypothesis in an ambulatory, naturalistic setting with chronic neural on-device recordings paired with time resolved behavioral measures. We will investigate a possible common neural basis underlying approach and avoidance across these 3 paradigms.

Subjects will participate in research at 7 critical timepoints during routine clinic visits (Fig. 4): before implant, 1 day before DBS activation, immediately after DBS activation, 2 weeks, 3 months, 6 months, and 12 months after DBS initiation. At these timepoints, patients will complete clinical assessments, perform the Probabilistic Approach Avoidance Task (PAAT), and conduct exposure trials under the guidance of a psychologist. The clinic offers the most controlled environment and provides opportunities for collecting high temporal resolution behavior synchronized to local field potential (LFP) recordings. These data will allow us to identify the degree of overlap in the time-resolved neural activity driving individual decisions to approach potential rewards or avoid potential aversive stimuli (Aim 1), and resist performing compulsions in order to achieve relief after OCD symptoms are triggered (Aim 2).

At home, our goal is to investigate patient trajectories along the approach-avoidance axis as OCD symptoms improve (Aim 3). We will leverage passive, on device recordings that occur in the background of everyday life activities and synchronize these neural recordings with data collected via wearables, ecological assessments, and video diaries. Capturing neural and behavioral data in the home environment is essential for understanding the neural and behavioral changes that occur over longer timescales than individual clinical visits. The neurobehavioral biomarkers generated by this dataset will provide trackable readouts of clinical status that could inform therapeutic decision-making and enable data driven intervention.