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Record W2902723876 · doi:10.1111/cdev.13182

Changes in Cortical Sensitivity to Infant Facial Cues From Pregnancy to Motherhood Predict Mother–Infant Bonding

2018· article· en· W2902723876 on OpenAlexaff
Joanna Dudek, Tyler Colasante, Antonio Zuffianò, David Haley

Bibliographic record

VenueChild Development · 2018
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyDevelopmental psychologyPregnancyMaternal sensitivityPostpartum period

Abstract

fetched live from OpenAlex

Abstract The transition to motherhood triggers changes in human brain structure that may facilitate mother–infant bonding. Although much research on maternal cortical responses to infant faces has focused on the postpartum period, no previous study has examined whether longitudinal functional changes in the maternal cortex during pregnancy and postpartum are associated with mother–infant bonding. Using electroencephalography, prenatal to postnatal changes in cortical sensitivity (P1, P2, late positive potential, N170 event-related potentials) to infant and adult faces were examined in relation to reported mother–infant bonding in 40 mothers (Mage = 30.5 years). Prenatal to postnatal increases in P1 and P2 responses to infant faces predicted stronger bonding. Findings suggest that cortical changes in attention allocation rather than in face-specific encoding enhance bonding.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.026
GPT teacher head0.311
Teacher spread0.285 · 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

Citations42
Published2018
Admission routes1
Has abstractyes

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