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Record W2766601113 · doi:10.1038/s41467-017-01184-1

Neuronal baseline shifts underlying boundary setting during free recall

2017· article· en· W2766601113 on OpenAlexfundno aff
Yitzhak Norman, Erin M. Yeagle, Michal Harel, Ashesh D. Mehta, Rafael Malach

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsnot available
FundersCanadian Institute for Advanced Research
KeywordsBaseline (sea)RecallBoundary (topology)Computer scienceNeuroscienceMedicineBiologyPsychologyCognitive psychologyMathematics

Abstract

fetched live from OpenAlex

Asked to freely recall items from a predefined set (e.g., animals), we rarely recall a wrong exemplar (e.g., a vegetable). This capability is so powerful and effortless that it is essentially taken for granted, yet, surprisingly, the underlying neuronal mechanisms are unknown. Here we investigate this boundary setting mechanism using intracranial recordings (ECoG), in 12 patients undergoing epilepsy monitoring engaged in episodic free recall. After viewing vivid photographs from two categories (famous faces and places), patients were asked to freely recall these items, targeting each category in separate blocks. Our results reveal a rapid and sustained rise in neuronal activity ("baseline shift") in high-order visual areas that persists throughout the free recall period and reflects the targeted category. We further show a more transient reactivation linked to individual recall events. The results point to baseline shift as a flexible top-down mechanism that biases spontaneous recall to remain within the required categorical boundaries.

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)0.000
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.063
GPT teacher head0.333
Teacher spread0.271 · 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

Citations43
Published2017
Admission routes1
Has abstractyes

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