期刊
NEUROIMAGE
卷 62, 期 2, 页码 856-863出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2012.01.034
关键词
Effective connectivity; Dynamic causal modeling; DCM; Granger causality; Granger causality mapping; GCM; Bayesian model selection; BMS; Model evidence; Brain Connectivity Workshop
资金
- Wellcome Trust [091593] Funding Source: Medline
Twenty years ago, the discovery of the blood oxygen level dependent (BOLD) contrast and invention of functional magnetic resonance imaging (MRI) not only allowed for enhanced analyses of regional brain activity, but also laid the foundation for novel approaches to studying effective connectivity, which is essential for mechanistically interpretable accounts of neuronal systems. Dynamic causal modeling (DCM) and Granger causality (G-causality) modeling have since become the most frequently used techniques for inferring effective connectivity from fMRI data. In this paper, we provide a short historical overview of these approaches, describing milestones of their development from our subjective perspectives. (C) 2012 Elsevier Inc. All rights reserved.
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