ArticleCommunications biology2024
Identifying individual brain development using multimodality brain network.
Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Functional gradient analysis reveals potential therapeutic mechanisms of nrTMS for postoperative motor deficits in glioma patients: A randomized controlled trial.NeuroImage. Clinical · 2026Trial
- ADBrainNet: a deep neural network for Autism Spectrum Disorder (ASD) and Attention Deficit and Hyperactivity Disorder (ADHD) classification using resting-state fMRI images based on explainable artificial intelligence.Medical & biological engineering & computing · 2026Article
- Artificial intelligence as a surrogate brain: bridging neural dynamical models and data.National science review · 2026Review
- Stable individualized brain computing model informed by spatiotemporal co-activity patterns.PLoS computational biology · 2025Article
- On the translational potential of atlases in precision oncology.Translational cancer research · 2025Review
- Specific Neural Mechanisms Underlying Humans' Processing of Information Related to Companion Animals: A Comparison with Domestic Animals and Objects.Animals : an open access journal from MDPI · 2025Article
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Authors and funding
7 authors.
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Abstract
The cortical development of our brains is in a hierarchical manner and promotes the emergence of large-scale functional hierarchy. However, under interindividual heterogenicity, how the spatiotemporal features of brain networks reflect brain development and mental health remains unclear. Here we collect both resting-state electroencephalography and functional magnetic resonance imaging data from the Child Mind Institute Biobank to demonstrate that during brain growth, the global dynamic patterns of brain states become more active and the dominant networks shift from sensory to higher-level networks; the individual functional network patterns become more similar to that of adults and their spatial coupling tends to be invariable. Furthermore, the properties of multimodality brain networks are sufficiently robust to identify healthy brain age and mental disorders at specific ages. Therefore, multimodality brain networks provide new insights into the functional development of the brain and a more reliable and reasonable approach for age prediction and individual diagnosis.
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Registered trials
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