A Dynamical Clustering Model of Brain Connectivity Inspired by the N -Body Problem.

Multimodal brain image analysis : third International Workshop, MBIA 2013, held in conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013 : proceedings. MBIA (Workshop) (3rd : 2013 : Nagoya-shi, Japan) Pub Date : 2013-01-01 DOI:10.1007/978-3-319-02126-3_13

Gautam Prasad, Josh Burkart, Shantanu H Joshi, Talia M Nir, Arthur W Toga, Paul M Thompson

{"title":"A Dynamical Clustering Model of Brain Connectivity Inspired by the N -Body Problem.","authors":"Gautam Prasad, Josh Burkart, Shantanu H Joshi, Talia M Nir, Arthur W Toga, Paul M Thompson","doi":"10.1007/978-3-319-02126-3_13","DOIUrl":null,"url":null,"abstract":"We present a method for studying brain connectivity by simulating a dynamical evolution of the nodes of the network. The nodes are treated as particles, and evolved under a simulated force analogous to gravitational acceleration in the well-known N -body problem. The particle nodes correspond to regions of the cortex. The locations of particles are defined as the centers of the respective regions on the cortex and their masses are proportional to each region's volume. The force of attraction is modeled on the gravitational force, and explicitly made proportional to the elements of a connectivity matrix derived from diffusion imaging data. We present experimental results of the simulation on a population of 110 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI), consisting of healthy elderly controls, early mild cognitively impaired (eMCI), late MCI (LMCI), and Alzheimer's disease (AD) patients. Results show significant differences in the dynamic properties of connectivity networks in healthy controls, compared to eMCI as well as AD patients.","PeriodicalId":90659,"journal":{"name":"Multimodal brain image analysis : third International Workshop, MBIA 2013, held in conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013 : proceedings. MBIA (Workshop) (3rd : 2013 : Nagoya-shi, Japan)","volume":"8159 ","pages":"129-137"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-319-02126-3_13","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal brain image analysis : third International Workshop, MBIA 2013, held in conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013 : proceedings. MBIA (Workshop) (3rd : 2013 : Nagoya-shi, Japan)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-319-02126-3_13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 6

Abstract

We present a method for studying brain connectivity by simulating a dynamical evolution of the nodes of the network. The nodes are treated as particles, and evolved under a simulated force analogous to gravitational acceleration in the well-known N -body problem. The particle nodes correspond to regions of the cortex. The locations of particles are defined as the centers of the respective regions on the cortex and their masses are proportional to each region's volume. The force of attraction is modeled on the gravitational force, and explicitly made proportional to the elements of a connectivity matrix derived from diffusion imaging data. We present experimental results of the simulation on a population of 110 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI), consisting of healthy elderly controls, early mild cognitively impaired (eMCI), late MCI (LMCI), and Alzheimer's disease (AD) patients. Results show significant differences in the dynamic properties of connectivity networks in healthy controls, compared to eMCI as well as AD patients.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

受N体问题启发的脑连接动态聚类模型。

我们提出了一种通过模拟网络节点的动态演化来研究大脑连通性的方法。节点被视为粒子，并在类似于著名的N体问题中的重力加速度的模拟力下演化。粒子节点对应于皮层的区域。粒子的位置被定义为皮层上各个区域的中心，它们的质量与每个区域的体积成正比。引力以引力为模型，并明确地与从扩散成像数据导出的连通性矩阵的元素成比例。我们介绍了来自阿尔茨海默病神经影像学倡议(ADNI)的110名受试者的模拟实验结果，包括健康老年人对照组、早期轻度认知障碍(eMCI)、晚期轻度认知障碍(LMCI)和阿尔茨海默病(AD)患者。结果显示，与eMCI和AD患者相比，健康对照组的连接网络的动态特性存在显著差异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Multimodal brain image analysis : third International Workshop, MBIA 2013, held in conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013 : proceedings. MBIA (Workshop) (3rd : 2013 : Nagoya-shi, Japan)

自引率

0.00%

发文量