动态因果模型在脑网络研究中的应用进展

doi:10.3969/j.issn.0258-8021.2022.01.010

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Abstract The effective connectivity between different functional areas of the brain is one important research issue in brain science. It is of great significance to investigate the brain networks formed by effective connectivity between brain regions in different situations, which can help people to understand the comprehensive functional mechanism of the brain. This research also has advantages in the treatment of various brain-related diseases and the development of brain functions. Dynamic causal model (DCM) is an advantageous way to analyze effective connectivity in the brain network. In this paper, we reviewed the research on the dynamic causal model based on functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and functional near-infrared spectroscopy (fNIRS). The application of DCM in fMRI can be divided into stroke-related brain networks, cognitive neuroscience brain networks and mental disease related brain networks. The application of DCM in EEG mainly includes cognitive neuroscience and diseases related to schizophrenia, Alzheimer's disease, epilepsy, Parkinson's disease, etc., however, rare in fNIRS so far, is only involved with cognitive neuroscience. Finally, we compared the three technologies and discussed the prospectives.

Key words： dynamic causal model (DCM) brain network functional magnetic resonance imaging(fMRI) electroencephalogram (EEG) functional near-infrared spectroscopy (fNIRS)

Received: 15 November 2020

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R318

Corresponding Authors: ^* E-mail: duojin.wang@usst.edu.cn

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	Liang Sailan
	Wang Duojin

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Liang Sailan,Wang Duojin. The Application Progress of Dynamic Causal Model in Brain Network Research[J]. Chinese Journal of Biomedical Engineering, 2022, 41(1): 86-99.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2022.01.010 OR http://cjbme.csbme.org/EN/Y2022/V41/I1/86

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