DocumentCode :
1783053
Title :
Abnormality of inter-network dynamic interaction in resting-state brains of schizophrenic patients
Author :
Zhenfeng Li ; Hui Shen ; Ling-Li Zeng ; Lin Yuan ; Dewen Hu
Author_Institution :
Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2014
fDate :
28-29 Sept. 2014
Firstpage :
1
Lastpage :
5
Abstract :
Resting-state functional connectivity (rs-FC) analyses have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and disconnectivity of intrinsic brain networks. However, these studies assumed temporal stationarity of rs-FCs, while the temporal dynamic of rs-FCs is rarely explored. Here, we test the variability of spontaneous fluctuation in rs-FCs of schizophrenic patients, using a measure of amplitude of low-frequency fluctuation (ALFF) of dynamic functional connectivity. Two-tailed two-sample t-tests and nonlinear support vector machines were employed to classify 24 schizophrenic patients from 25 healthy controls. The experimental results demonstrated that 81.3% of subjects were correctly classified by leave-one-out cross-validation. Moreover, the majority of the most discriminating functional connections were located across the identified networks, indicating that the inter-network dynamic interaction changes existed in schizophrenic patients. The current study may shed new light on the pathophysiological mechanism of schizophrenia and suggests that the abnormal temporal communication across networks may provide potential biomarkers for its clinical diagnosis.
Keywords :
biomedical MRI; brain; image classification; medical disorders; medical image processing; neurophysiology; statistical testing; support vector machines; ALFF; abnormal temporal communication; abnormality; amplitude of low-frequency fluctuation; biomarkers; classification; clinical diagnosis; complex symptoms; disrupted neural circuits; dynamic functional connectivity; fMRI; healthy controls; inter-network dynamic interaction; intrinsic brain networks disconnectivity; leave-one-out cross-validation; nonlinear support vector machines; pathophysiological mechanism; resting-state brains; resting-state functional connectivity analyses; rs-FC analyses; schizophrenia; schizophrenic patients; spontaneous fluctuation; t-tests; temporal dynamic; temporal stationarity; Biomarkers; Diffusion tensor imaging; Feature extraction; Head; Psychiatry; Support vector machines; Transmission line matrix methods; amplitude of low-frequency fluctuation (ALFF); classification; dynamic functional connectivity; fMRI; schizophrenia;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multisensor Fusion and Information Integration for Intelligent Systems (MFI), 2014 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6731-5
Type :
conf
DOI :
10.1109/MFI.2014.6997664
Filename :
6997664
Link To Document :
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