Zhao, Zongya and Feng, Yifan and Wang, Menghan and Wei, Jiarong and Tan, Tao and Li, Ruijiao and Hu, Heshun and Wang, Mengke and Chen, Peiqi and Gao, Xudong and Wei, Yinping and Wang, Chang and Gao, Zhixian and Jiang, Wenshuai and Zhou, Xuezhi and Li, Mingcai and Wang, Chong and Pang, Ting and Yu, Yi (2024) Investigating cortical complexity and connectivity in rats with schizophrenia. Frontiers in Neuroinformatics, 18. p. 1392271. ISSN 1662-5196, DOI https://doi.org/10.3389/fninf.2024.1392271.
Full text not available from this repository.Abstract
Background The above studies indicate that the SCZ animal model has abnormal gamma oscillations and abnormal functional coupling ability of brain regions at the cortical level. However, few researchers have focused on the correlation between brain complexity and connectivity at the cortical level. In order to provide a more accurate representation of brain activity, we studied the complexity of electrocorticogram (ECoG) signals and the information interaction between brain regions in schizophrenic rats, and explored the correlation between brain complexity and connectivity.Methods We collected ECoG signal from SCZ rats. The frequency domain and time domain functional connectivity of SCZ rats were evaluated by magnitude square coherence and mutual information (MI). Permutation entropy (PE) and permutation Lempel-Ziv complexity (PLZC) were used to analyze the complexity of ECoG, and the relationship between them was evaluated. In addition, in order to further understand the causal structure of directional information flow among brain regions, we used phase transfer entropy (PTE) to analyze the effective connectivity of the brain.Results Firstly, in the high gamma band, the complexity of brain regions in SCZ rats is higher than that in normal rats, and the neuronal activity is irregularity. Secondly, the information integration ability of SCZ rats decreased and the communication of brain network information was hindered at the cortical level. Finally, compared with normal rats, the causal relationship between brain regions of SCZ rats was closer, but the information interaction center was not clear.Conclusion The above findings suggest that at the cortical level, complexity and connectivity are valid biomarkers for identifying SCZ. This bridges the gap between peak potentials and EEG. This may help to understand the pathophysiological mechanisms at the cortical level in schizophrenics.
| Item Type: | Article |
|---|---|
| Funders: | National Natural Science Foundation of China (NSFC) (82201709) ; (82302298), Science and Technology Research Project of Henan Province (242102310055) ; (232102310009) ; (242102310005), Open Project Program of Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder (XTkf07) ; (XTkf01), Innovative Research Team (in Science and Technology) in University of Henan Province (24IRTSTHN042), Major Science and Technology Projects of Henan Province (221100310500) |
| Uncontrolled Keywords: | schizophrenia; electrocorticogram; brain network; complexity; connectivity |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 06 Feb 2025 01:10 |
| Last Modified: | 06 Feb 2025 01:10 |
| URI: | http://eprints.um.edu.my/id/eprint/47529 |
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