Down-regulation of cholinergic signaling in the habenula induces anhedonia-like behavior
Bibliographic record
Abstract
Dysfunction of cholinergic signaling in the brain has long been believed to be associated with depressive disorders. However, the functional impact of habenular cholinergic signaling on the specified depressive behaviors is not well understood. Here, we demonstrated that the expression levels of cholinergic signaling genes (CHAT, VACHT, CHT, CHRNA3, CHRNB3 and CHRNB4) were down-regulated in a chronic restraint stress (CRS) rat model of depression, in which rats display depression-like behaviors such as anhedonia and mood despair. Moreover, knockdown of CHAT in the rat habenula was sufficient to evoke anhedonia-like behavior. The anhedonia-like behavior induced by CHAT knockdown was not reversed by chronic administration of the selective serotonin reuptake inhibitor fluoxetine. To determine whether habenular cholinergic signaling is associated with regulation of dopamine neurons in the ventral tegmental area (VTA) and serotonin neurons in the dorsal raphe nucleus (DRN), we used CHAT::cre transgenic mice expressing the Designer Receptors Exclusively Activated by Designer Drugs (DREADD). Pharmacogenetic activation of habenular cholinergic neurons induces the excitation of dopamine neurons in the VTA and reduces the immunoreactivity of 5-hydroxytryptamine (5-HT) in the DRN. Habenular cholinergic gene down-regulation was recapitulated in the postmortem habenula of suicide victims diagnosed with major depressive disorder (MDD).
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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 | 0.001 |
| 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".