Lingering Cognitive States Shape Fundamental Mnemonic Abilities
Bibliographic record
Abstract
Why are people sometimes able to recall associations in exquisite detail while at other times left frustrated by the deficiencies of memory? Although this apparent fickleness of memory has been extensively studied by investigating factors that build strong memory traces, researchers know less about whether memory success also depends on cognitive states that are in place when a cue is encountered. Motivating this possibility, neurocomputational models propose that the hippocampus's capacity to support associative recollection (pattern completion) is biased by persistent neurochemical states, which can be elicited by exposure to familiarity and novelty. We investigated these models' behavioral implications by assessing how recent familiarity influences different memory-retrieval processes. We found that recent familiarity selectively benefitted associative memory (Experiment 1) and that this effect decayed over seconds (Experiment 2), consistent with the timescale of hippocampal neuromodulation. Thus, we show that basic memory computations can be shaped by a subtle, biologically motivated manipulation.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".