A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder
Problem
Surgeons use multiple competing deep brain stimulation targets for obsessive-compulsive disorder, and it is unclear which location produces clinical improvement.
Why it matters
DBS for OCD requires precise electrode placement; poor targeting means failed treatment for severely ill patients.
What the AI did
Connectivity-derived models analyzed four patient cohorts (N=50) and identified one fiber bundle linking frontal regions to the STN whose stimulation overlap significantly predicted clinical improvement across centers.
Results
Same fiber bundle associated with optimal response across cohorts; clinical improvement significantly predicted in independent cohorts of 8 and 6 patients.
Impact
The tract model could inform DBS target selection for OCD, per cross-cohort validation.
Record
| Venue | Nature Communications |
|---|---|
| Published | 2020 |
| Work type | article |
| Authors | Ningfei Li, Juan Carlos Baldermann, Astrid Kibleur, Svenja Treu, Harith Akram, Gavin J.B. Elias, Alexandre Boutet, Andrés M. Lozano et al. |
| Citations | 316 (OpenAlex, at import time) |
| References | 102 |
| Model or method | connectivity-derived models (no specific architecture named) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1038/s41467-020-16734-3 |
| Open access | gold |
| Keywords | deep brain stimulation, obsessive-compulsive disorder, connectomics, tractography, target selection |
Importance rating
significant — thousands to millions affected
DBS targeting uncertainty affects severely ill OCD patients; abstract validates a shared tract across targets/centers but states no population scale.