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Early environmental influences on the orbito-frontal cortex function and its effects on behavior

2025· review· en· W4406309123 on OpenAlexafffund
Olivia Ruge, João Paulo Maires Hoppe, Roberta Dalle Molle, Patrícia Pelufo Silveira

Bibliographic record

VenueNeuroscience & Biobehavioral Reviews · 2025
Typereview
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsMcGill University Health CentreDouglas Mental Health University InstituteMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFrontal cortexPsychologyNeuroscienceFunction (biology)Cortex (anatomy)Cognitive psychologyBiologyEvolutionary biology

Abstract

fetched live from OpenAlex

Early-life adversity during pre- and early post-natal phases can impact brain development and lead to maladaptive changes in executive function related behaviors. This increases the risk for a range of psychopathologies and physical diseases. Importantly, exposure to adversities during these periods is also linked to alterations in the orbito-frontal cortex (OFC) which is a key player in these executive functions. The OFC thus appears to be a central node in this association between early life stress and disease risk. Gaining a clear, and detailed understanding of the association between early life stress, OFC function, and executive function, as well as the underlying mechanisms mediating this association is relevant to inform potential therapeutic interventions. In this paper, we begin by reviewing evidence linking early life adversities to 1) alterations in behaviors regulated by the OFC and 2) changes in OFC anatomy and function. We then present insights into the underlying mechanisms for these changes, stemming from early life adversity models, and highlight important future directions for this line of research.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.162
GPT teacher head0.375
Teacher spread0.213 · 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

Citations7
Published2025
Admission routes2
Has abstractyes

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