Brain Network Analysis of Schizophrenia Based on the Functional Connectivity

ZHANG Xuejun; WANG Longqiang; DING Yuhan; HUANG Liya; CHENG Xiefeng

doi:10.1049/cje.2019.03.017

Volume 28 Issue 3

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ZHANG Xuejun, WANG Longqiang, DING Yuhan, et al., “Brain Network Analysis of Schizophrenia Based on the Functional Connectivity,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 535-541, 2019, doi: 10.1049/cje.2019.03.017

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ZHANG Xuejun, WANG Longqiang, DING Yuhan, et al., “Brain Network Analysis of Schizophrenia Based on the Functional Connectivity,” Chinese Journal of Electronics, vol. 28, no. 3, pp. 535-541, 2019, doi: 10.1049/cje.2019.03.017

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Brain Network Analysis of Schizophrenia Based on the Functional Connectivity

doi: 10.1049/cje.2019.03.017

1.
School of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;
2.
Nation-Local Joint Project Engineering Lab of RF Integration & Micropackage, Nanjing 210023, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61271334).

Received Date: 2017-04-26
Publish Date: 2019-05-10

Abstract

Abstract

Network analysis based on graph theory has greatly promoted the cognition of the human brain network. A detailed brain network function connection analysis was carried out for the brain of normal human brain and mental illness patients. We studied the Magnetoencephalography (MEG) of 9 normal subjects and 9 schizophrenics in left hemisphere temporal lobe and frontal lobe regions. And obtained the dynamic function connectivity matrix by calculating Pearson correlation coefficients that based on sliding time window and shorttime Fourier transform, and constructed weight and binary network by graph theory. Analyzed the small world properties of normal human brain networks, and compared the differences of network between normal subjects and patients with schizophrenia.
- Magnetoencephalography (MEG),
- Dynamic functional connectivity,
- Functional networks,
- Graph theory

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References(32)

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