Cortical Overlap and Cortical-Hippocampal Interactions Predict Subsequent True and False Memory
Bibliographic record
Abstract
The declarative memory system allows us to accurately recognize a countless number of items and events, particularly those strengthened by repeated exposure. However, increased familiarity due to repetition can also lead to false recognition of related but new items, particularly when mechanisms supporting fine-grain mnemonic discrimination fail. The hippocampus is thought to be particularly important in separating overlapping cortical inputs during encoding so that similar experiences can be differentiated. In the current study of male and female human subjects, we examine how neural pattern similarity between repeated exemplars of a given concept (e.g., apple) influences true and false memory for target or lure images. Consistent with past work, we found that subsequent true recognition was related to pattern similarity between concept exemplars and the entire encoding set (global encoding similarity), particularly in ventral visual stream. In addition, memory for an individual target exemplar (a specific apple) could be predicted solely by the degree of pattern overlap between the other exemplars (different apple pictures) of that concept (concept-specific encoding similarity). Critically, subsequent false memory for lures was mitigated when high concept-specific similarity in cortical areas was accompanied by differentiated hippocampal representations of the corresponding exemplars. Furthermore, both true and false memory entailed the reinstatement of concept-related information at varying levels of specificity. These results link both true and false memory to a measure of concept strength expressed in the overlap of cortical representations, and importantly, illustrate how the hippocampus serves to separate concurrent cortical overlap in the service of detailed memory. SIGNIFICANCE STATEMENTIn some instances, the same processes that help promote memory for a general idea or concept can also hinder more detailed memory judgments, which may involve differentiating between closely related items. The current study shows that increased overlap in cortical representations for conceptually-related pictures is associated with increased recognition of repeated concept pictures. Whether similar lure items were falsely remembered as old further depended on the hippocampus, where the presence of more distinct representations protected against later false memory. This work suggests that the differentiability of brain patterns during perception is related to the differentiability of items in memory, but that fine-grain discrimination depends on the interaction between cortex and hippocampus.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".