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Identifying the Latent Active Patterns Underlying the Dynamic Organization of Human Brain Using Resting-State FMRI
Congying Chu1,2; Tianzi Jiang
2016-04
Conference NameThe IEEE International Symposium on Biomedical Imaging (ISBI)
Source PublicationIEEE International Symposium on Biomedical Imaging (ISBI 2016)
Conference Date2016-4-13-2016-4-16
Conference PlacePrague
Abstract
The dynamic organization of human brain functional
networks can be revealed through resting-state fMRI. It is
still an open question about how to determine the essential
factors underlying the dynamic activity of human brain. In
this study, we proposed the assumption that the dynamic
activity of brain was companied with various involvements
of latent active patterns (LAPs). We further supposed that
LAPs were sparsely involved with different brain state. We
modeled our assumptions using a dictionary-learning
framework. An online dictionary learning method was
adopted to calculate the LAPs and the sparse loading
parameters. Based on the results obtained from the resting-
state fMRI dataset, we found some commonly represented
LAPs that were involved with the default mode network,
salience network and frontoparietal attention network. The
sparse represented LAPs at each time point were related
with the time-varying activity. LAPs provided a new
viewpoint to mine the factors related with the dynamic
organization of brain activity.
KeywordDynamic Dictionary Learning Resting- State Fmri Laps
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11963
Collection脑网络组研究中心
Corresponding AuthorTianzi Jiang
Affiliation1.Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
Recommended Citation
GB/T 7714
Congying Chu,Tianzi Jiang. Identifying the Latent Active Patterns Underlying the Dynamic Organization of Human Brain Using Resting-State FMRI[C],2016.
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