High‐frequency stimulation of the medial prefrontal cortex decreases cellular firing in the dorsal raphe
Bibliographic record
Abstract
High-frequency deep brain stimulation (HFS-DBS) of the subcallosal cingulate (SCC) region has been investigated as a treatment for refractory forms of depression with a ~50% remission rate in open label studies. However, the therapeutic mechanisms of DBS are still largely unknown. Using anaesthetized Sprague Dawley rats, we recorded neuronal spiking activity in 102 neurons of the dorsal raphe (DR) before, during and after the induction of a 5-min HFS train in the infralimbic region (IL) of the medial prefrontal cortex (mPFC), the rodent homologue of the human SCC. The majority of DR cells (82%) significantly decreased firing rate during HFS (P < 0.01, 55.7 ± 4.5% of baseline, 35 rats). To assess whether mPFC-HFS mediates inhibition of DR cellular firing by stimulating local GABAergic interneurons, the GABAA antagonist bicuculline (Bic, 100 μm) was injected directly into the DR during HFS. Neurons inhibited by HFS recovered their firing rate during Bic+HFS (P < 0.01, n = 15, seven rats) to levels not different from baseline. Cells that were not affected by HFS did not change firing rate during Bic+HFS (P = 0.968, n = 7, three rats). These results indicate that blocking GABAA reverses HFS-mediated inhibition of DR neurons. As the cells that were not inhibited by HFS were also unaffected by HFS+Bic, they are probably not innervated by local GABA. Taken together, our results suggest that mPFC-HFS may exert a preferential effect on DR neurons with GABAA receptors.
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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 | 0.000 | 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) | 0.001 | 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".