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Record W3159462218 · doi:10.7554/elife.64567

Linking mPFC circuit maturation to the developmental regulation of emotional memory and cognitive flexibility

2021· review· en· W3159462218 on OpenAlexfundno aff
Cassandra B. Klune, Benita Jin, Laura A. DeNardo

Bibliographic record

VenueeLife · 2021
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsnot available
FundersDavid Geffen School of Medicine, University of California, Los AngelesNational Institute of Neurological Disorders and StrokeWhitehall FoundationNational Institute of Mental HealthNatural Sciences and Engineering Research Council of CanadaBrain Research FoundationBrain and Behavior Research Foundation
KeywordsPrefrontal cortexNeurosciencePsychologyFlexibility (engineering)Cognitive flexibilityCognition

Abstract

fetched live from OpenAlex

The medial prefrontal cortex (mPFC) and its abundant connections with other brain regions play key roles in memory, cognition, decision making, social behaviors, and mood. Dysfunction in mPFC is implicated in psychiatric disorders in which these behaviors go awry. The prolonged maturation of mPFC likely enables complex behaviors to emerge, but also increases their vulnerability to disruption. Many foundational studies have characterized either mPFC synaptic or behavioral development without establishing connections between them. Here, we review this rich body of literature, aligning major events in mPFC development with the maturation of complex behaviors. We focus on emotional memory and cognitive flexibility, and highlight new work linking mPFC circuit disruption to alterations of these behaviors in disease models. We advance new hypotheses about the causal connections between mPFC synaptic development and behavioral maturation and propose research strategies to establish an integrated understanding of neural architecture and behavioral repertoires.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.004

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 head0.215
GPT teacher head0.421
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations176
Published2021
Admission routes1
Has abstractyes

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