MétaCan
Menu
Back to cohort
Record W2046006470 · doi:10.1002/hipo.20985

The nature and time‐course of medial temporal lobe contributions to semantic retrieval: An fMRI study on verbal fluency

2011· article· en· W2046006470 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHippocampus · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsTemporal lobePsychologyVerbal fluency testSemantic memoryCognitive psychologyNeuroscienceFluencyNeuropsychologyCognitionEpilepsy

Abstract

fetched live from OpenAlex

Recent investigations have shown that the medial temporal lobe (MTL), a region thought to be exclusive to episodic memory, can also influence performance on tests of semantic memory. The present study examined further the nature of MTL contributions to semantic memory tasks by tracking MTL activation as participants performed category fluency, a traditional test of semantic retrieval. For categories that were inherently autobiographical (e.g. names of friends), the MTLs were activated throughout the time period in which items were generated, consistent with the MTLs role in retrieving autobiographical memories. For categories that could not benefit from autobiographical or spatial/context information (e.g. governmental offices), the MTL was not implicated at any time point. For categories for which both prototypical and episodically-related information exists (e.g. kitchen utensils), there was more robust MTL activity for the open-ended, late generation periods compared with the more well-defined, early item generation time periods. We interpret these results as suggesting that early in the generation phase, responses are based on well-rehearsed prototypical knowledge whereas later performance relies more on open-ended strategies, such as deriving exemplars from personally relevant contextual information (e.g. imagining one's own kitchen). These findings and interpretation were consistent with the results of an initial, separate behavioral study (Expt 1), that used the distinctiveness of responses as a measure of open-endedness across the generation phase: Response distinctiveness corresponded to the predicted open-endedness of the various tasks at early and late phases. Overall, this is consistent with the view that as generation of semantic information becomes open-ended, it recruits processes from other domains, such as episodic memory, to support performance.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.068
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.312
Teacher spread0.291 · 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