Recollection versus strength as the primary determinant of hippocampal engagement at retrieval
Bibliographic record
Abstract
We examined whether hippocampal activity in recognition relates to the strength of the memory or to recollective experience, a subject of considerable current debate. Participants studied word pairs and then made two successive recognition decisions on each item: first on the uncued target and then on the target presented with the studied cue word. We compared recollection and familiarity patterns of activation in fMRI for these decisions. Critically, our analyses attempted in two ways to equate perceived memory strength while varying the associative information available. First, activity for targets judged familiar before cueing was contrasted with activity for the same items in the second decision as a function of whether the targets converted to recollection or remained familiar when the context cues were provided. We found increased hippocampal activity following cueing only with recollective conversion. Second, we investigated whether hippocampal activity was modulated by the rated familiarity strength of cued items or whether it increased uniquely in recollection. Hippocampal activation was not modulated parametrically by familiarity strength and recollected items were associated with greater activity relative to highly familiar items. Together, our results support the notion that it is recollection of context, rather than memory strength, that underlies hippocampal engagement at retrieval.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".