ArticleBrain and behavior2020
Neonatal brain connectivity outliers identify over forty percent of IQ outliers at 4 years of age.
Article in Brain and behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A hierarchical model of early brain functional network development.Trends in cognitive sciences · 2025Review
- Sex differences in brain-behavior relationships in the first 2 years of life.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- An efficient interpretable framework for unsupervised low, very low and extreme birth weight detection.PloS one · 2025Article
- Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds.Developmental cognitive neuroscience · 2022Article
- Maternal trait anxiety symptoms, frontolimbic resting-state functional connectivity, and cognitive development in infancy.Developmental psychobiology · 2021Article
- Hippocampal functional connectivity development during the first two years indexes 4-year working memory performance.Cortex; a journal devoted to the study of the nervous system and behavior · 2021Article
- Neonatal brain connectivity outliers identify over forty percent of IQ outliers at 4 years of age.Brain and behavior · 2020Article
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Authors and funding
5 authors.
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Abstract
backgroundDefining reliable brain markers for the prediction of abnormal behavioral outcomes remains an urgent but extremely challenging task in neuroscience research. This is particularly important for infant studies given the most dramatic brain and behavioral growth during infancy.
methodsIn this study, we proposed a novel prediction scheme through abstracting individual newborn's whole-brain functional connectivity pattern to three outlier measures (Triple O) and tested the hypothesis that neonates identified as "brain outliers" based on Triple O were more likely to develop as IQ outliers at 4 years of age. Without need for training with behavioral data, Triple O represents a novel proof-of-concept approach to predict later IQ outcomes based on neonatal brain data.
resultsTriple O correctly identified 42.1% true IQ outliers among a mixed cohort of 175 newborns with different term, twin, and maternal disorder statuses. Triple O also reached a high level of specificity (96.2%) and overall accuracy (90.3%). Further incorporating a demographic information indicator, the enhanced Triple O+ could further differentiate between high and low 4YR IQ outliers. Validation tests against seven independent reference samples revealed highly consistent results and a minimum sample size of ~50 for robust performance.
conclusionsConsidering that postnatal brain growth and various environmental factors likely also contribute to 4YR IQ, the fact that Triple O, based purely on neonatal functional connectivity data, could identify >40% of 4YR IQ outliers is striking. Together with the very high level of specificity, each outlier predicted by Triple O represents a meaningful risk but future efforts are needed to explore ways to identify the rest of outliers. Overall, with no need for training, a high level of robustness, and a minimal requirement on sample size, the proposed Triple O approach demonstrates great potential to predict later outlying IQ performances using neonatal functional connectivity data.
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