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Record W2767366333 · doi:10.1177/0956797617728592

Lingering Cognitive States Shape Fundamental Mnemonic Abilities

2017· article· en· W2767366333 on OpenAlexaff
Anuya Patil, Katherine Duncan

Bibliographic record

VenuePsychological Science · 2017
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMnemonicPsychologyNoveltyRecallCognitive psychologyCognitionAssociative propertyContent-addressable memoryEpisodic memoryReconstructive memoryCognitive scienceNeuroscienceExplicit memorySocial psychologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.258
GPT teacher head0.452
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations54
Published2017
Admission routes1
Has abstractyes

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