Identifying Local Field Potential Biomarkers for Obsessive-compulsive Disorder Treatment With Deep Brain Stimulation

Recruiting now · Not applicable

Conditions studied: Obsessive-Compulsive Disorder

In brief

Obsessive-compulsive disorder (OCD) is a complex and severe mental illness characterized by multiple symptoms and is considered a leading cause of non-fatal health loss. However, nearly 20% of patients do not respond to standard pharmacological or psychological treatments. Currently, we lack objective brain-based biomarkers. To address this issue, we used a novel device for electrophysiology recording and applied deep brain stimulation (DBS) to 16 OCD patients. In this study, we aim to use long-term invasive neural signal collection and machine learning techniques to reveal the complex relationship between these signals and OCD symptoms. By applying advanced machine learning algorithms, our goal is to establish highly accurate prediction models to identify biomarkers associated with the occurrence and progression of OCD. The research will focus on the spatiotemporal features of neural signals and build personalized OCD decoding models based on individual differences through the integration and analysis of large-scale data. By delving into the information contained in neural signals, we hope to provide academic and practical innovations for the development of personalized treatment approaches for OCD.

Key facts

Study ID
NCT06542224
Run by
West China Hospital
People needed
16
Starts
2024-08-03
Expected to finish
2026-12-03
Last updated by the study team
2024-08-07

Who can join

Age: 18 and older, up to 65. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.