Abstract

The brain is a complex organ composed of distinct modules that govern thought, memory, motion, emotion, touch, vision, olfaction, and every process that regulates the body, respectively. The overall function of the brain critically relies upon the coordination among these modules. Despite extensive investigation on its mechanism, we still know little about how different brain regions crosstalk and communicate as a cohesive whole. In this talk, I will present a new model of statistical mechanics for reconstructing inter-module crosstalk networks in the aging brain. These networks can capture a full set of interaction properties, including bidirectionality, sign, weight, and feedback cycle. We use this model to analyze metabolic data collected from the mouse brains at a spectrum of ages,identifying several key metabolites that mediate inter-modular crosstalk and its age-specific change in the mouse brain. This model could potentially serve as a tool to unveil the genetic and developmental secrets of how the brain functions and dysfunctions during aging processes. (Joint work with Shen Zhang and Rongling Wu at Tsinghua University Yau Mathematical Sciences Center and Beijing Institute of Mathematics and Applications,Daqi Cao at Beijing University of Architecture and Civil Engineering, Mengmeng Sang at Nantong University).