Neurocircuitry of Deep Brain Stimulation for Obsessive-Compulsive Disorder as Revealed by Tractography: A Systematic Review
Bibliographic record
Abstract
Objective: Deep brain stimulation (DBS) was proposed in 1999 to treat refractory obsessive-compulsive disorder (OCD). Despite the accumulated experience over more than two decades, 30–40% of patients fail to respond to this procedure. One potential reason to explain why some patients do not improve in the postoperative period is that DBS might not have engaged structural therapeutic networks that are crucial to a favorable outcome in non-responders. This article reviews magnetic resonance imaging diffusion studies (DTI-MRI), analyzing neural networks likely modulated by DBS in OCD patients and their corresponding clinical outcome. Methods: We used a systematic review process to search for studies published from 2005 to 2020 in six electronic databases. Search terms included obsessive-compulsive disorder, deep brain stimulation, diffusion-weighted imaging, diffusion tensor imaging, diffusion tractography, tractography, connectome, diffusion analyses, and white matter. No restriction was made concerning the surgical target, DTI-MRI technique and the method of data processing. Results: Eight studies published in the last 15 years were fully assessed. Most of them used 3 Tesla DTI-MRI, and different methods of data acquisition and processing. There was no consensus on potential structures and networks underlying DBS effects. Most studies stimulated the ventral anterior limb of the internal capsule (ALIC)/nucleus accumbens. However, the contribution of different white matter pathways that run through the ALIC for the effects of DBS remains elusive. Moreover, the improvement of cognitive and affective symptoms in OCD patients probably relies on electric modulation of distinct networks. Conclusion: Though, tractography is a valuable tool to understand neural circuits, the effects of modulating different fiber tracts in OCD are still unclear. Future advances on image acquisition and data processing and a larger number of studies are still required for the understanding of the role of tractography-based targeting and to clarify the importance of different tracts for the mechanisms of DBS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".