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Record W2014806995 · doi:10.1073/pnas.1214107109

Neuronal code for extended time in the hippocampus

2012· article· en· W2014806995 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.

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2012
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Lethbridge
FundersNational Institute of Neurological Disorders and Stroke
KeywordsHippocampal formationHippocampusNeuroscienceCoding (social sciences)Context (archaeology)Interval (graph theory)Code (set theory)Computer scienceBiologyMathematicsStatistics

Abstract

fetched live from OpenAlex

The time when an event occurs can become part of autobiographical memories. In brain structures that support such memories, a neural code should exist that represents when or how long ago events occurred. Here we describe a neuronal coding mechanism in hippocampus that can be used to represent the recency of an experience over intervals of hours to days. When the same event is repeated after such time periods, the activity patterns of hippocampal CA1 cell populations progressively differ with increasing temporal distances. Coding for space and context is nonetheless preserved. Compared with CA1, the firing patterns of hippocampal CA3 cell populations are highly reproducible, irrespective of the time interval, and thus provide a stable memory code over time. Therefore, the neuronal activity patterns in CA1 but not CA3 include a code that can be used to distinguish between time intervals on an extended scale, consistent with behavioral studies showing that the CA1 area is selectively required for temporal coding over such periods.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.089
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.139
GPT teacher head0.360
Teacher spread0.221 · 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