著者

田邊 宏樹

出版者

日本基礎心理学会

雑誌

基礎心理学研究 (ISSN:02877651)

巻号頁・発行日

vol.28, no.1, pp.72-78, 2009

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There are two fundamental principles of functional organization in the human brain: functional specialization, and integration. Functional specialization assumes a local specialization for certain aspects of information processing. However, this view cannot characterize how local areas interact with each other. The other view, functional integration within a system, is able to address and characterize this issue in terms of effective connectivity. Effective connectivity is defined as the causal influences that neural units exert over another. This view is gradually gaining importance in the study of functional neuroimaging. The present article at first introduced four types of dynamic systems that are framed in terms of analyses of functional and effective connectivity. It then focused on dynamical causal modelling (DCM). The conceptual and mathematical basis of DCM are reviewed. The key advantage of DCM is that it allows for generating plausible models of neural population dynamics, and uses a biophysical forward model that describes the transformation from neural activity to hemodynamic response. A Bayesian model selection procedure is an additional benefit. Finally, notions for the usage of DCM have been described.