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

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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.

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Zhou, Z., Zhang, H., Hsu, L. M., Lin, W., Pan, G., & Shen, D. (2019). Multi-layer Temporal Network Analysis Reveals Increasing Temporal Reachability and Spreadability in the First Two Years of Life. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11766 LNCS, pp. 665–672). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32248-9_74

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