Information transfer between rich-club structures in the human brain

被引:2
|
作者
Sharaev, Maksim [1 ]
Orlov, Vyacheslav [1 ]
Ushakov, Vadim [1 ,2 ]
Velichkovsky, Boris [1 ]
机构
[1] Natl Res Ctr, Kurchatov Inst, Moscow, Russia
[2] Natl Res Nucl Univ MEPhI, Moscow Engn Phys Inst, Moscow, Russia
基金
俄罗斯科学基金会;
关键词
effective connectivity; information transfer; rich club; transfer entropy; ORGANIZATION;
D O I
10.1016/j.procs.2018.01.067
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The performance of the human brain depends on how effectively its distinct regions communicate, especially the regions which are more strongly connected to each other than to other regions, or so called "rich-clubs". The aim of the current work is to find a connectivity pattern between the three brain rich-club regions without any a priori assumptions on the underlying network architecture. Rich-clubs for the analysis were previously identified with structural MRI. Functional magnetic resonance imaging (fMRI) data from 25 healthy subjects (1000 time points from each one) was acquired and Transfer Entropy (TE) between fMRI time-series from rich-clubs was calculated. The significant results at the group level were obtained by testing against the surrogate data generated on a novel approach. We found stable causal interactions between rostral Anterior Cingulate Cortex L and Dorsal Anterior Cingulate Cortex L, dorsal Anterior Cingulate Cortex L and Paracentral Lobule R but not vice versa. Our work provides an approach to causal analysis of experimental data and demonstrates the applicability to real fMRI study. (C) 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 8th Annual International Conference on Biologically Inspired Cognitive Architectures
引用
收藏
页码:440 / 445
页数:6
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