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Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy.

Authors :
Yiming Fan
Ling-Li Zeng
Hui Shen
Jian Qin
Fuquan Li
Dewen Hu
Source :
Entropy. Sep2017, Vol. 19 Issue 9, p471. 19p.
Publication Year :
2017

Abstract

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying functional connectivity patterns of the developing and aging brain. Normal brain development is characterized by continuous and significant network evolution through infancy, childhood, and adolescence, following specific maturational patterns. Normal aging is related to some resting state brain networks disruption, which are associated with certain cognitive decline. It is a big challenge to design an integral metric to track connectome evolution patterns across the lifespan, which is to understand the principles of network organization in the human brain. In this study, we first defined a brain network eigen-entropy (NEE) based on the energy probability (EP) of each brain node. Next, we used the NEE to characterize the lifespan orderness trajectory of the whole-brain functional connectivity of 173 healthy individuals ranging in age from 7 to 85 years. The results revealed that during the lifespan, the whole-brain NEE exhibited a significant non-linear decrease and that the EP distribution shifted from concentration to wide dispersion, implying orderness enhancement of functional connectome over age. Furthermore, brain regions with significant EP changes from the flourishing (7-20 years) to the youth period (23-38 years) were mainly located in the right prefrontal cortex and basal ganglia, and were involved in emotion regulation and executive function in coordination with the action of the sensory system, implying that self-awareness and voluntary control performance significantly changed during neurodevelopment. However, the changes from the youth period to middle age (40-59 years) were located in the mesial temporal lobe and caudate, which are associated with long-term memory, implying that the memory of the human brain begins to decline with age during this period. Overall, the findings suggested that the human connectome shifted from a relatively anatomical driven state to an orderly organized state with lower entropy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10994300
Volume :
19
Issue :
9
Database :
Academic Search Index
Journal :
Entropy
Publication Type :
Academic Journal
Accession number :
125322096
Full Text :
https://doi.org/10.3390/e19090471