قارن الطرق

	تحليل التشابه التمثيلي	النمذجة السببية الديناميكية
المجال	التصوير العصبي	التصوير العصبي
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	2008	2003
صاحب الطريقة	Nikolaus Kriegeskorte	Karl J. Friston
النوع	fMRI similarity structure comparison	Causal modeling pipeline for neuroimaging
المصدر التأسيسي	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.
الأسماء البديلة	RSA, representational geometry, similarity structure analysis	DCM, Dynamic Causal Model
ذات صلة	3	2
الملخص	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.