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Dynamic brain network evolution in normal aging based on computational experiments
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DOI：10.1016/j.neucom.2016.09.056.png)
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Abstract
En 中文
The mechanisms of normal aging of the human brain are insufficiently understood at present. This lack of systematic understanding impedes the exploration of new treatments for age-related diseases and approaches to extend our lifespan. The objective of this study was to develop a novel evolution model to simulate the dynamic alteration processes in functional brain networks that occur during normal aging, using computational experiments. Six global topological properties and a nodal metric were applied to characterize functional magnetic resonance imaging data on the brain networks of individuals from three different age groups. Comparing these real-world results to our simulation results showed that our evolution model captures well the dynamic processes of normal aging in functional brain networks. Our research shows that a tradeoff exists between the constraints on the degree distribution and the tendency toward clustered connections of functional brain networks during normal aging. These computational experiments provide a more comprehensive perspective that addresses dynamic alterations across a large time scale, which traditional research techniques cannot achieve. Our model is therefore of profound significance for exploring the mechanisms of normal aging.
Keywords:
Normal aging
Resting-state fMRI
Functional brain network
Evolution
Simulation
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