计算机应用研究2017，Vol.34Issue(11)：3272-3276,5.DOI:10.3969/j.issn.1001-3695.2017.11.016
基于同步多维数据流的脑网络动态特征辨识方法研究
Research of dynamic characteristic identification method for human brain network based on multidimensional synchronization data flow
摘要
Abstract
Focusing on the real-time change characteristic of the human brain,this paper proposed a dynamic characteristic identification method to extract and describe the dynamic properties of the human brain network based on functional magnetic resonance imaging technology.Firstly,the method used multidimensional synchronization data flow analysis technology with real-time updating capability to decompose the blood oxygen level-dependent signal sequences on the whole data acquisition time into small time windows sequences on each sample point.Then it got the continuous state observer windows which could realize the specific time point status extraction of the human brain functional magnetic resonance signal.Secondly,it used a correlation analysis technology to analyze the signals in adjacent state observer windows to obtain a single state observer matrix which could describe the state in a single sample point.Finally,it had the entire dynamic feature matrix during the data collection by combining multiple state observer matrix.The experiment results show this method provides an effective means for dynamic characteristic observation and description of human brain functional network and also gives foundations for further study for human brain network dynamic properties.关键词
动态特征辨识/多维同步数据流/脑功能网络/磁共振成像Key words
dynamic characteristic identification/multidimensional synchronization data flow/brain functional network/magnetic resonance imaging分类
信息技术与安全科学引用本文复制引用
马洒洒,王彬,薛洁,董迎朝,刘辉,熊新..基于同步多维数据流的脑网络动态特征辨识方法研究[J].计算机应用研究,2017,34(11):3272-3276,5.基金项目
国家自然科学基金资助项目(61263017) （61263017）
昆明理工大学人才培养基金资助项(201303120) （201303120）
