방법 비교

	표상 유사성 분석	동적 인과 모델링
분야	신경영상	신경영상
계열	Process / pipeline	Process / pipeline
기원 연도	2008	2003
창시자	Nikolaus Kriegeskorte	Karl J. Friston
유형	fMRI similarity structure comparison	Causal modeling pipeline for neuroimaging
원전	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.
별칭	RSA, representational geometry, similarity structure analysis	DCM, Dynamic Causal Model
관련	3	2
요약	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.