Antidepressant Effect of Optogenetic Stimulation of the Medial Prefrontal Cortex
Bibliographic record
Abstract
Brain stimulation and imaging studies in humans have highlighted a key role for the prefrontal cortex in clinical depression; however, it remains unknown whether excitation or inhibition of prefrontal cortical neuronal activity is associated with antidepressant responses. Here, we examined cellular indicators of functional activity, including the immediate early genes (IEGs) zif268 (egr1), c-fos, and arc, in the prefrontal cortex of clinically depressed humans obtained postmortem. We also examined these genes in the ventral portion of the medial prefrontal cortex (mPFC) of mice after chronic social defeat stress, a mouse model of depression. In addition, we used viral vectors to overexpress channel rhodopsin 2 (a light-activated cation channel) in mouse mPFC to optogenetically drive "burst" patterns of cortical firing in vivo and examine the behavioral consequences. Prefrontal cortical tissue derived from clinically depressed humans displayed significant reductions in IEG expression, consistent with a deficit in neuronal activity within this brain region. Mice subjected to chronic social defeat stress exhibited similar reductions in levels of IEG expression in mPFC. Interestingly, some of these changes were not observed in defeated mice that escape the deleterious consequences of the stress, i.e., resilient animals. In those mice that expressed a strong depressive-like phenotype, i.e., susceptible animals, optogenetic stimulation of mPFC exerted potent antidepressant-like effects, without affecting general locomotor activity, anxiety-like behaviors, or social memory. These results indicate that the activity of the mPFC is a key determinant of depression-like behavior, as well as antidepressant responses.
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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".