Reinstatement of Event Details during Episodic Simulation in the Hippocampus
Bibliographic record
Abstract
According to the constructive episodic simulation hypothesis, episodic simulation (i.e., imagining specific novel future episodes) draws on some of the same neurocognitive processes that support episodic memory (i.e., recalling specific past episodes). Episodic retrieval supports the ability to simulate future experiences by providing access to episodic details (e.g., the people and locations that comprise memories) that can be recombined in new ways. In the current functional neuroimaging study, we test this hypothesis by examining whether the hippocampus, a region implicated in the reinstatement of episodic information during memory, supports reinstatement of episodic information during simulation. Employing a multivoxel pattern similarity analysis, we interrogated the similarity between hippocampal neural patterns during memory and simulation at the level of individual event details. Our findings indicate that the hippocampus supports the reinstatement of detail-specific information from episodic memory during simulation, with the level of reinstatement contributing to the subjective experience of simulated details.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".