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Record W3184591174 · doi:10.3389/fncir.2021.653116

A Characterization of the Electrophysiological and Morphological Properties of Vasoactive Intestinal Peptide (VIP) Interneurons in the Medial Entorhinal Cortex (MEC)

2021· article· en· W3184591174 on OpenAlexafffund
Saishree Badrinarayanan, Frédéric Manseau, Sylvain Williams, Mark P. Brandon

Bibliographic record

VenueFrontiers in Neural Circuits · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanada Research ChairsCanada First Research Excellence FundCanada Excellence Research Chairs, Government of CanadaScottish Rite Charitable Foundation of CanadaMcGill University
KeywordsVasoactive intestinal peptideElectrophysiologyNeuroscienceEntorhinal cortexInhibitory postsynaptic potentialPatch clampExcitatory postsynaptic potentialBiologyNeuropeptideHippocampusReceptor

Abstract

fetched live from OpenAlex

Circuit interactions within the medial entorhinal cortex (MEC) translate movement into a coherent code for spatial location. Entorhinal principal cells are subject to strong lateral inhibition, suggesting that a disinhibitory mechanism may drive their activation. Cortical Vasoactive Intestinal Peptide (VIP) expressing inhibitory neurons are known to contact other interneurons and excitatory cells and are thus capable of providing a local disinhibitory mechanism, yet little is known about this cell type in the MEC. To investigate the electrophysiological and morphological properties of VIP cells in the MEC, we use in vitro whole-cell patch-clamp recordings in VIPcre/tdTom mice. We report several gradients in electrophysiological properties of VIP cells that differ across laminae and along the dorsal-ventral MEC axis. We additionally show that VIP cells have distinct morphological features across laminae. Together, these results characterize the cellular and morphological properties of VIP cells in the MEC.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.351

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 studies0.0000.001
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 head0.032
GPT teacher head0.228
Teacher spread0.196 · 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.

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

Citations9
Published2021
Admission routes2
Has abstractyes

Explore more

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