機能分化と機能統合からシステムとして脳をとらえる : Dynamic Causal Modellingを中心に(<特集>脳機能計測と基礎心理学)
スポンサーリンク
概要
- 論文の詳細を見る
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.
- 2009-09-30
著者
関連論文
- 未知語の模倣と反復による語彙学習の神経基盤と自動化プロセス(人間の言語処理と学習)
- 脳活動から視知覚像を読む(招待講演セッション,手,実・仮想空間の知覚・認知,一般)
- 多重解像度局所画像復号器の組み合わせによる視覚像の再構成
- 機能分化と機能統合からシステムとして脳をとらえる : Dynamic Causal Modellingを中心に(脳機能計測と基礎心理学)
- 二言語における語彙カテゴリー判断課題のプライミング効果 : 習熟度別脳活性状態の解明のために