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Record W3148444750 · doi:10.1093/cercor/bhab081

Maternal Adverse Childhood Experience and Depression in Relation with Brain Network Development and Behaviors in Children: A Longitudinal Study

2021· article· en· W3148444750 on OpenAlexaff
Han Zhang, Ting Yat Wong, Birit F. P. Broekman, Yap Seng Chong, Lynette Pei‐Chi Shek, Peter D. Gluckman, Kok Hian Tan, Michael J. Meaney, Marielle V. Fortier, Anqi Qiu

Bibliographic record

VenueCerebral Cortex · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersMedical Research CouncilNational Medical Research CouncilNational Research Foundation SingaporeSingapore Institute for Clinical SciencesNational University Health SystemNational Research Foundation
KeywordsPsychopathologyPsychologyDepression (economics)OffspringEarly childhoodDevelopmental psychologyMaternal sensitivityLongitudinal studyLanguage developmentClinical psychologyChild developmentPregnancyMedicine

Abstract

fetched live from OpenAlex

Maternal childhood maltreatment and depression increase risks for the psychopathology of the offspring. This study employed a longitudinal dataset of mother-child dyads to investigate the developmental trajectories of brain functional networks and behaviors of children in relation with maternal childhood adverse experience and depression. Maternal childhood trauma was retrospectively assessed via childhood trauma questionnaire, whereas maternal depressive symptoms were prospectively evaluated during pregnancy and after delivery (n = 518). Child brain scans were acquired at age of 4.5, 6, and 7.5 years (n = 163) and behavioral problems were measured at 7.5 years using the Child Behavior Checklist. We found the functional connectivity of the language network with the sensorimotor, frontal, and attentional networks as a function of maternal adverse experience that interacted with sex and age. Girls exposed to mothers with depressive symptoms or childhood abuse showed the increased development of the functional connectivity of the language network with the visual networks, which was associated with social problems. Girls exposed to mothers with depressive symptoms showed the slower growth of the functional connectivity of the language network with the sensorimotor networks. Our findings, in a community sample, suggest the language network organization as neuroendophenotypes for maternal childhood trauma and depression.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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 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

Citations16
Published2021
Admission routes1
Has abstractyes

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