Anesthesia-triggered dopaminergic bursts actively induce forgetting: a paradigm shift in understanding cold-shock amnesia
Bibliographic record
Abstract
Abstract Retrograde memory loss, the inability to recall events preceding amnesia onset, is a well-documented consequence of anesthesia. Recent discoveries, pioneered by Drosophila research, have challenged the view that forgetting is a passive process, and have demonstrated that rather it is a highly active, well-regulated biological process. This work builds on this and makes a remarkable and unexpected discovery that anesthesia itself triggers a robust, widespread burst of activity in dopaminergic neurons. Here, we report that both cold-shock and CO 2 anesthesia elicits strong activation in PAM and PPL1 dopaminergic neuron populations. This calcium activity is accompanied by robust synaptic release of dopamine. Strikingly, pharmacological experiments show that this response is input-driven, as it is completely abolished by Na+ channel blockers and dampened by nAChR antagonists. Using behavioral methods, crucially, we show that anesthesia-induced amnesia can be prevented by blocking activity in PAM and PPL1 neurons during anesthesia. Together, our findings reveal a previously unrecognized active mechanism by which anesthesia induces forgetting, mediated by rapid dopaminergic signaling. This paradigm-shifting discovery redefines how we think about anesthesia-induced amnesia and the biology of forgetting.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".