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Bottom up modeling of the connectome: linking structure and function in the resting brain and their changes in aging.

Abstract：

:With the increasing availability of advanced imaging technologies, we are entering a new era of neuroscience. Detailed descriptions of the complex brain network enable us to map out a structural connectome, characterize it with graph theoretical methods, and compare it to the functional networks with increasing detail. To link these two aspects and understand how dynamics and structure interact to form functional brain networks in task and in the resting state, we use theoretical models. The advantage of using theoretical models is that by recreating functional connectivity and time series explicitly from structure and pre-defined dynamics, we can extract critical mechanisms by linking structure and function in ways not directly accessible in the real brain. Recently, resting-state models with varying local dynamics have reproduced empirical functional connectivity patterns, and given support to the view that the brain works at a critical point at the edge of a bifurcation of the system. Here, we present an overview of a modeling approach of the resting brain network and give an application of a neural mass model in the study of complexity changes in aging.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Nakagawa TT,Jirsa VK,Spiegler A,McIntosh AR,Deco G

doi

10.1016/j.neuroimage.2013.04.055

subject

Has Abstract

pub_date

2013-10-15 00:00:00

pages

318-29

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(13)00402-3

journal_volume

80

pub_type

杂志文章,评审

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