Multi-layer Temporal Network Analysis Reveals Increasing Temporal Reachability and Spreadability in the First Two Years of Life

for UNC/UMN Baby Connectome Project Consortium

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    Spatiotemporal dynamics analysis of the human brain functional connectome and its early development in the first few years of life is tremendously essential for grasping such a shining jewel in life science as such a knowledge shed light on the long-standing mysteries of emerging and fast developing of various high-level cognitive abilities in such a pivotal stage. Most of the existing developmental neuroscience studies with resting-state functional MRI (fMRI) failed in correctly modeling information flow, exchanges, and spreads across space and time via the dedicatedly designed and continuously rewiring complex brain networks. We propose a novel multi-layer temporal network analysis with two intuitive and intriguing metrics, reachability and spreadability, measuring the extent of a certain brain region getting in touch with other regions in a short period of time through temporal linkage (inter-layer connections between corresponding regions across time). We applied this method on a large-scale, high-quality, high-resolution sleeping state fMRI of normally developed neonates/infants without sedating them. We unravel a first-ever picture of how the human brain facilitates more and more efficient information exchange and integration. The early and fast maturation of the ventral visual “what” pathway with the highest developing velocity over all other regions during 0–6 months may underpin the rapid developing consciousness and all other aspects of complex cognitive functions.

    Original languageEnglish
    Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
    EditorsDinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages665-672
    Number of pages8
    ISBN (Print)9783030322472
    DOIs
    Publication statusPublished - 2019
    Event22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
    Duration: 2019 Oct 132019 Oct 17

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11766 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
    Country/TerritoryChina
    CityShenzhen
    Period19/10/1319/10/17

    Bibliographical note

    Publisher Copyright:
    © 2019, Springer Nature Switzerland AG.

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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