TY - GEN
T1 - Multi-layer Temporal Network Analysis Reveals Increasing Temporal Reachability and Spreadability in the First Two Years of Life
AU - for UNC/UMN Baby Connectome Project Consortium
AU - Zhou, Zhen
AU - Zhang, Han
AU - Hsu, Li Ming
AU - Lin, Weili
AU - Pan, Gang
AU - Shen, Dinggang
N1 - Funding Information:
This work utilizes approaches developed by an NIH grant (1U01MH110274) and the efforts of the UNC/UMN Baby Connectome Project (BCP) Consortium. This work was also supported in part by NIH grants EB022880 and MH117943.
Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85075694230&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-32248-9_74
DO - 10.1007/978-3-030-32248-9_74
M3 - Conference contribution
AN - SCOPUS:85075694230
SN - 9783030322472
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 665
EP - 672
BT - Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
A2 - Shen, Dinggang
A2 - Yap, Pew-Thian
A2 - Liu, Tianming
A2 - Peters, Terry M.
A2 - Khan, Ali
A2 - Staib, Lawrence H.
A2 - Essert, Caroline
A2 - Zhou, Sean
PB - Springer Science and Business Media Deutschland GmbH
T2 - 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
Y2 - 13 October 2019 through 17 October 2019
ER -