Memory’s avalanche: Recent feelings of familiarity and resultant DA nuclei activity enable subsequent memory reactivation
Bibliographic record
Abstract
Abstract Memory retrieval is notoriously variable. Various neurocognitive states have been theorized to affect retrieval success from moment to moment, but the presence and catalysts of these states in the human brain remain largely understudied. Building on previous work, we studied how recent memory judgments during an ongoing retrieval task (i.e. retrieval judgments vs. novelty detection) and their corresponding neural activity prepare the brain to reinstate unrelated memories during upcoming trials. High-level ventral stream regions, including the hippocampus, reinstated memories with significantly greater fidelity following recent retrieval judgments compared to novelty detection. Activity in dopaminergic nuclei rose during retrieval judgments, which predicted and partially mediated the effect of retrieval judgments on upcoming reinstatement. While dopaminergic nuclei activity predicted upcoming reinstatement, it did not predict upcoming retrieval accuracy. Exploratory analyses revealed the opposite effect in the dorsal and lateral prefrontal cortex, whose activity predicted upcoming retrieval accuracy, but not reinstatement. These results point to distinct neural contributions to what is reinstated and how it may guide memory decisions, and by identifying dopaminergic nuclei as partial mediators of reinstatement, our results open new avenues for investigating how neuromodulatory states may dynamically shape memory accessibility. Significance Statement Why can we effortlessly recall memories in some moments but struggle at others? Here, we draw on computational models to uncover why human brains are sometimes better prepared to remember and how to nudge them into that state. We discover that recent retrieval judgments, compared to recent novelty detection, increase upcoming accuracy and neural reinstatement of unrelated memories. This effect is so powerful that key memory regions only show reinstatement following preceding retrieval judgments. We found that dopaminergic nuclei are more active during retrieval judgments and predict upcoming memory reinstatement. This pattern partially explains why engaging in remembering prepares your brain to reinstate other memories and reveals new insights for the role dopaminergic nuclei may play in retrieval.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".