Compara mètodes

	Anàlisi de Similitud Representacional	Modelatge Causal Dinàmic
Camp	Neuroimatge	Neuroimatge
Família	Process / pipeline	Process / pipeline
Any d'origen	2008	2003
Autor original	Nikolaus Kriegeskorte	Karl J. Friston
Tipus	fMRI similarity structure comparison	Causal modeling pipeline for neuroimaging
Font seminal	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.
Àlies	RSA, representational geometry, similarity structure analysis	DCM, Dynamic Causal Model
Relacionats	3	2
Resum	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.