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

College of Mechatronics and Automation, National University of Defense Technology, 109 Deya Road, Changsha 410073, China
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Entropy 2017, 19(9), 471; https://doi.org/10.3390/e19090471
Received: 3 August 2017 / Revised: 25 August 2017 / Accepted: 1 September 2017 / Published: 4 September 2017
(This article belongs to the Special Issue Information Theory in Neuroscience)
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. View Full-Text
Keywords: functional connectome; graph theoretical analysis; eigenvector centrality; orderness; network eigen-entropy functional connectome; graph theoretical analysis; eigenvector centrality; orderness; network eigen-entropy
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Fan, Y.; Zeng, L.-L.; Shen, H.; Qin, J.; Li, F.; Hu, D. Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy. Entropy 2017, 19, 471.

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