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Zhang J, Yang Y, Liu T, Shi Z, Pei G, Wang L, Wu J, Funahashi S, Suo D, Wang C, Yan T. Functional connectivity in people at clinical and familial high risk for schizophrenia. Psychiatry Res 2023; 328:115464. [PMID: 37690192 DOI: 10.1016/j.psychres.2023.115464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 09/03/2023] [Accepted: 09/04/2023] [Indexed: 09/12/2023]
Abstract
Patients diagnosed with schizophrenia (SZ) exhibit compromised functional connectivity within extensive brain networks. However, the precise development of this impairment during disease progression in the clinical high-risk (CHR) population and their relatives remains unclear. Our study leveraged data from 128 resting electroencephalography (EEG) channels acquired from 30 SZ patients, 21 CHR individuals, 17 unaffected healthy relatives (RSs; those at heightened SZ risk due to family history), and 31 healthy controls (HCs). These data were harnessed to establish functional connectivity patterns. By calculating the geometric distance between EEG sequences, we unveiled local and global nonlinear relationships within the entire brain. The process of dimensionality reduction led to low-dimensional representations, providing insights into high-dimensional EEG data. Our findings indicated that CHR participants exhibited aberrant functional connectivity across hemispheres, whereas RS individuals showcased anomalies primarily concentrated within hemispheres. In the realm of low-dimensional analysis, RS participants' third-dimensional occipital lobe values lay between those of the CHR individuals and HCs, significantly correlating with scale scores. This low-dimensional approach facilitated the visualization of brain states, potentially offering enhanced comprehension of brain structure, function, and early-stage functional impairment, such as occipital visual deficits, in RS individuals before cognitive decline onset.
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Affiliation(s)
- Jian Zhang
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Yaxin Yang
- School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Tiantian Liu
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Zhongyan Shi
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Guangying Pei
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Li Wang
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Dingjie Suo
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Changming Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Tianyi Yan
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China.
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