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Record W4362512950 · doi:10.21203/rs.3.rs-2715680/v1

Early Life Stress Accelerates Critical Periods and Causes Precocious Visual Cortex Development

2023· preprint· en· W4362512950 on OpenAlexafffund
Janet Poplawski, Tony Montina, Gerlinde A. S. Metz

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsVisual cortexStress (linguistics)NeurosciencePsychologyCognitive psychologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract The developing nervous system displays remarkable plasticity in response to sensory stimulation during critical periods of development. Critical periods may also increase the brain’s vulnerability to adverse experiences. Here we show that early-life stress in mice shifts the timing of critical period of the visual cortex. Early-life stress accelerated the opening and closing of the visual cortex critical period along with precocious development of visual acuity. Premature emergence of inhibitory perineuronal nets was accompanied by activated energy metabolism and protein biosynthesis and expression of genes linked to psychiatric disease risk, with hemispheric asymmetries favoring the right side. Thus, early-life stress desynchronizes the orchestrated temporal sequence of regional brain development leading to permanent functional deficiencies. These findings provide new insights into the dichotomy between adaptive brain plasticity versus neurodevelopmental risk factors.

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: Observational · Consensus signal: none
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)0.0000.000
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 head0.091
GPT teacher head0.423
Teacher spread0.332 · 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 designObservational
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

Citations1
Published2023
Admission routes2
Has abstractyes

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