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Record W2914866118 · doi:10.1101/543777

Fan cells in layer 2 of lateral entorhinal cortex are critical for episodic-like memory

2019· preprint· en· W2914866118 on OpenAlexaff
Brianna Vandrey, Derek L.F. Garden, Veronika Ambrozova, Christina McClure, Matthew F. Nolan, James A. Ainge

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsDiscovery Centre
FundersBiotechnology and Biological Sciences Research CouncilRoyal Society of EdinburghRoyal SocietyWellcome Trust
KeywordsEntorhinal cortexNeuroscienceEpisodic memoryContext (archaeology)HippocampusObject (grammar)Content-addressable memoryLayer (electronics)Associative propertyPsychologyBiologyComputer scienceCognitionChemistryArtificial intelligenceArtificial neural networkMathematics

Abstract

fetched live from OpenAlex

Abstract The lateral entorhinal cortex (LEC) is a critical structure for episodic memory, but the roles of discrete neuronal populations within LEC are unclear. Here, we establish an approach for selectively targeting fan cells in layer 2 (L2) of LEC. Whereas complete lesions of the LEC were previously found to abolish associative recognition memory, we find that after selective suppression of synaptic output from fan cells mice still recognise novel object-context configurations, but are impaired in recognition of novel object-place-context associations. Our experiments suggest a segregation of memory functions within LEC networks and indicate that specific inactivation of fan cells leads to behavioural deficits reminiscent of early stages of Alzheimer’s disease.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.282
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2019
Admission routes1
Has abstractyes

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