Age-Related Changes in Micro Brain Characteristics Based on Relaxed Mean-Field Model

Abstract

Brain health is an important research direction of neuroscience. In addition to the effects of diseases, we cannot ignore the negative effect of aging on brain health. There have been many studies on brain aging, but only a few have used dynamic models to analyze differences in micro brain characteristics in healthy people. In this article, we use the relaxed mean-field model (rMFM) to study the effects of normal aging. Two main parameters of this model are the recurrent connection strength and subcortical input strength. The sensitivity of the rMFM to the initial values of the parameters has not been fully discussed in previous research. We examine this issue through repeated numerical experiments and obtain a reasonable initial parameter range for this model. Differences in recurrent connection strength and subcortical input strength due to aging have also not been studied previously. We use statistical methods to find the regions of interest (ROIs) exhibiting significant differences between young and old groups. Further, we carry out a difference analysis on the process of change of these ROIs on a more detailed timescale. We find that even with the same final results, the trends of change in these ROIs are different. This shows that to develop possible methods to prevent or delay brain damage due to aging, more attention needs to be paid to the trends of change of different ROIs, not just the final results.