Stimulus-specific recruitment of human amygdala neurons predicts episodic memory encoding success
Bibliographic record
Abstract
Controlling whether a given experience is encoded into long-term memory and thus later remembered is a crucial component of our memory system whose failure is often at the root of memory disorders. One brain area that takes part in controlling which experiences are remembered is the amygdala, but the mechanisms by which it does so remain poorly understood. Here we examined single-neuron activity and local field potentials as human participants performed recognition memory tasks with visual stimuli. Category-selective amygdala neurons exhibited elevated firing rates during encoding of later remembered items versus forgotten items. This subsequent memory effect was restricted to images of the preferred category of a given cell, was stronger and appeared earlier in the amygdala compared to the hippocampus, and did not depend on the valence and arousal of the stimuli. In contrast, category selective cells immediately upstream in the ventral temporal cortex did not exhibit a subsequent memory effect, highlighting specificity to the amygdala. Successful memory formation was accompanied by enhanced spike-field coherence between the activity of category cells in the amygdala and hippocampal field potentials. These findings, replicated in two large independent datasets with two different tasks, demonstrate that recruitment of stimulus-specific amygdala representations predicts episodic memory formation, particularly in the right amygdala. This data suggests category cells in the right amygdala as a cellular target for interventions to treat memory disorders in humans.
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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 | 0.001 |
| 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".