3T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation
Bibliographic record
Abstract
Deep brain stimulation targeting the subcallosal cingulate area, a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While subcallosal cingulate deep brain stimulation drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 T functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of 12 patients with fully implanted deep brain stimulation devices targeting the subcallosal cingulate area. Four additional subcallosal cingulate deep brain stimulation patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n = 78 acquisitions overall) during (i) inactive deep brain stimulation; (ii) clinically optimal active deep brain stimulation; and (iii) suboptimal active deep brain stimulation. All scans were acquired within a single MRI session, each separated by a 5-min washout period. Analysis of the amplitude of low-frequency fluctuations in each sequence indicated that clinically optimal deep brain stimulation reduced spontaneous brain activity in several areas, including the bilateral dorsal anterior cingulate cortex, the bilateral posterior cingulate cortex, the bilateral precuneus and the left inferior parietal lobule (PBonferroni < 0.0001). Stimulation-induced dorsal anterior cingulate cortex signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings and was related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dorsal anterior cingulate cortex, posterior cingulate cortex and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated amplitude of low-frequency fluctuations changes in these three areas (along with preoperative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally, all three brain areas exhibited significant changes in functional connectivity between active and inactive deep brain stimulation states (PBonferroni < 0.01). These results provide insight into the network-level mechanisms of subcallosal cingulate deep brain stimulation and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".