手法を比較

	表象類似性解析	動的因果モデリング
分野	神経画像学	神経画像学
系統	Process / pipeline	Process / pipeline
提唱年	2008	2003
提唱者	Nikolaus Kriegeskorte	Karl J. Friston
種類	fMRI similarity structure comparison	Causal modeling pipeline for neuroimaging
原典	Kriegeskorte, N., Mur, M., & Bandettini, P. A. (2008). Representational similarity analysis—connecting the branches of systems neuroscience. Frontiers in Systems Neuroscience, 2, 4.	Friston, K. J., Harrison, L., & Penny, W. (2003). Dynamic causal modelling. NeuroImage, 19(4), 1273–1302.
別名	RSA, representational geometry, similarity structure analysis	DCM, Dynamic Causal Model
関連	3	2
概要	Representational Similarity Analysis (RSA) is a framework for comparing representational geometry across brain regions, computational models, and behavioral measures. Introduced by Kriegeskorte and colleagues in 2008, RSA measures how similarly a brain region represents different stimuli or concepts by examining pairwise similarity structure rather than absolute activity patterns.	Dynamic Causal Modeling (DCM) is a Bayesian framework for specifying and inverting generative models of brain connectivity from neuroimaging data. Introduced by Karl Friston and colleagues in 2003, DCM treats brain regions as dynamical systems and estimates effective connectivity by fitting observed fMRI time series to a biophysically plausible model of neuronal interactions.