Porovnat metody

	Analýza podobnosti reprezentací	Dynamické kauzální modelování
Obor	Neurozobrazování	Neurozobrazování
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	2008	2003
Tvůrce	Nikolaus Kriegeskorte	Karl J. Friston
Typ	fMRI similarity structure comparison	Causal modeling pipeline for neuroimaging
Původní zdroj	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.
Další názvy	RSA, representational geometry, similarity structure analysis	DCM, Dynamic Causal Model
Příbuzné	3	2
Shrnutí	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.