Clinical Research Papers:
Increased local connectivity of brain functional networks during facial processing in schizophrenia: evidence from EEG data
PDF | HTML | How to cite
Metrics: PDF 1225 views | HTML 2039 views | ?
Tianyi Yan1,2, Wenhui Wang1,2, Tiantian Liu1,2, Duanduan Chen1, Changming Wang3, Yulong Li4, Xudong Ma5, Xiaoying Tang1, Jinglong Wu2, Yiming Deng6,7 and Lun Zhao8
1School of Life Science, Beijing Institute of Technology, Beijing, China
2Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
3Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
4Beijing National Day School, Beijing, China
5Guang Zhou Clifford School, Guang Dong, China
6Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
7China National Clinical Research Center for Neurological Diseases, Beijing, China
8School of Education, Beijing Normal University Zhuhai, Zhuhai, China
Tianyi Yan, email: [email protected]
Yiming Deng, email: [email protected]
Keywords: schizophrenia, facial processing, dynamic brain network, phase synchrony, graph theory
Received: April 09, 2017 Accepted: June 12, 2017 Published: September 01, 2017
Schizophrenia is often considered to be a disconnection syndrome. The abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. The present study investigated event-related functional connectivity networks to compare facial processing in individuals with and without schizophrenia. Faces and tables were presented to participants, and event-related phase synchrony, represented by the phase lag index (PLI), was calculated. In addition, cortical oscillatory dynamics may be useful for understanding the neural mechanisms underlying the disparate cognitive and functional impairments in schizophrenic patients. Therefore, the dynamic graph theoretical networks related to facial processing were compared between individuals with and without schizophrenia. Our results showed that event-related phase synchrony was significantly reduced in distributed networks, and normalized clustering coefficients were significantly increased in schizophrenic patients relative to those of the controls. The present data suggest that schizophrenic patients have specific alterations, indicated by increased local connectivity in gamma oscillations during facial processing.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.