动态因果模型在脑网络研究中的应用进展

The Application Progress of Dynamic Causal Model in Brain Network Research

大脑各功能区之间的有效连接是脑科学研究领域的一个重要内容。研究在不同情形下相关脑区之间有效连接所构成的大脑网络,对于全面理解大脑的功能机制,治疗各种与大脑相关疾病,开发脑功能具有重要意义。动态因果模型是一种分析大脑有效连接的优势方法。结合功能性磁共振成像、脑电、近红外脑功能成像等3种检测技术,综述动态因果模型的相关研究。动态因果模型在功能性磁共振成像中的应用涉及脑卒中、认知神经科学和精神疾病相关的脑网络研究;脑电相关动态因果模型的应用主要涉及认知神经科学以及与精神分裂症、阿尔兹海默症、癫痫、帕金森等疾病相关的内容;目前动态因果模型在近红外脑功能成像中的应用还较少,主要涉及认知神经科学研究。最后,对这3种技术进行了比较和展望。

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.