השוואת שיטות

	ניתוח דמיון ייצוגי	מודלים סיבתיים דינמיים
תחום	הדמיה עצבית	הדמיה עצבית
משפחה	Process / pipeline	Process / pipeline
שנת המקור	2008	2003
הוגה השיטה	Nikolaus Kriegeskorte	Karl J. Friston
סוג	fMRI similarity structure comparison	Causal modeling pipeline for neuroimaging
מקור מכונן	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.
כינויים	RSA, representational geometry, similarity structure analysis	DCM, Dynamic Causal Model
קשורות	3	2
תקציר	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.