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Record W3194723587 · doi:10.1016/j.celrep.2021.109572

Cholinergic modulation of dentate gyrus processing through dynamic reconfiguration of inhibitory circuits

2021· article· en· W3194723587 on OpenAlexfundno aff
Mora B. Ogando, Olivia Pedroncini, Noel Federman, Sebastián A. Romano, Luciano A. Brum, Guillermo M. Lanuza, Damián Refojo, Antonia Marín‐Burgin

Bibliographic record

VenueCell Reports · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsnot available
FundersFondo para la Investigación Científica y TecnológicaVolkswagen FoundationInternational Development Research Centre
KeywordsDentate gyrusNeuroscienceOptogeneticsPerforant pathCholinergicInhibitory postsynaptic potentialDisinhibitionHippocampal formationParvalbuminHippocampusSynaptic plasticityPerforant PathwayBiology

Abstract

fetched live from OpenAlex

The dentate gyrus (DG) of the hippocampus plays a key role in memory formation, and it is known to be modulated by septal projections. By performing electrophysiology and optogenetics, we evaluated the role of cholinergic modulation in the processing of afferent inputs in the DG. We show that mature granule cells (GCs), but not adult-born immature neurons, have increased responses to afferent perforant path stimuli upon cholinergic modulation. This is due to a highly precise reconfiguration of inhibitory circuits, differentially affecting Parvalbumin and Somatostatin interneurons, resulting in a nicotinic-dependent perisomatic disinhibition of GCs. This circuit reorganization provides a mechanism by which mature GCs could escape the strong inhibition they receive, creating a window of opportunity for plasticity. Indeed, coincident activation of perforant path inputs with optogenetic release of acetylcholine produces a long-term potentiated response in GCs, essential for memory formation.

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)0.000
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 score0.003
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.051
GPT teacher head0.338
Teacher spread0.287 · 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

Citations21
Published2021
Admission routes1
Has abstractyes

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