Bottom up modeling of the connectome: Linking structure and function in the resting brain and their changes in aging
Bottom up modeling of the connectome: Linking structure and function in the resting brain and their changes in aging
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DOI：
10.1016/j.neuroimage.2013.04.055
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发表时间：
2013-10-15
期刊：
影响因子：
5.7
通讯作者：
Deco, Gustavo
中科院分区：
文献类型：
--
作者：
Nakagawa, Tristan T.;Jirsa, Viktor K.;Deco, Gustavo
随着先进成像技术的日益普及，我们正在进入神经科学的新时代。对复杂大脑网络的详细描述使我们能够绘制出结构连接体，用图论方法对其进行表征，并将其与功能网络进行比较。为了将这两个方面联系起来，并了解动力学和结构如何相互作用以形成任务和静息状态下的功能性大脑网络，我们使用理论模型。使用理论模型的优势在于，通过从结构和预定义的动力学中明确地重建功能连接和时间序列，我们可以通过以真实的大脑中无法直接访问的方式将结构和功能联系起来来提取关键机制。最近，休息状态模型与不同的本地动态再现经验的功能连接模式，并支持认为，大脑工作在一个临界点的系统的分叉的边缘。在这里，我们提出了一个概述的休息脑网络的建模方法，并给出了一个神经质量模型在衰老的复杂性变化的研究中的应用。(C)2013 Elsevier Inc. All rights reserved.
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. (C) 2013 Elsevier Inc. All rights reserved.