Functional Brain Parcellations of the Infant Brain and the Associated Developmental Trends. (14th March 2017)

• Record Type: Journal Article
• Authors: Shi, Feng; Salzwedel, Andrew P; Lin, Weili; Gilmore, John H; Gao, Wei
• Is Part Of: Cerebral cortex. Volume 28:Number 4(2018)
• Page Start: 1358
• Page End: 1368
• Publication Date: 2017-03-14
• Subjects: atlas -- connectome -- early development -- functionally connectivity -- graph cut; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhx062
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Resting-state functional connectivity studies have dramatically improved our understanding of the early human brain functional development during the past decade. However, one emerging problem that could potentially impede future progresses in the field is the definition of regions of interest (ROI), since it is well known that functional connectivity estimation can be seriously contaminated by within-ROI signal heterogeneity. In this study, based on a large-scale rsfMRI data set in human infants (230 neonates, 143 1-year olds, and 107 2-year olds), we aimed to derive a set of anatomically constrained, infant-specific functional brain parcellations using functional connectivity-based clustering. Our results revealed significantly higher levels of signal homogeneity within the newly defined functional parcellations compared with other schemes. Importantly, the global functional connectivity patterns associated with the newly defined functional subunits demonstrated significantly increasing levels of differentiation with age, confirming increasing levels of local specialization. Subsequent whole brain connectivity analysis revealed intriguing patterns of regional-level functional connectivity developments and system-level hub redistribution during infancy. Overall, the newly derived infant-specific functional brain parcellations and the associated novel developmental patterns will likely prove valuable for future early developmental studies using the functional connectivity technique.