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PodručjeNeurooslikavanjeNeurooslikavanje
ObiteljProcess / pipelineProcess / pipeline
Godina nastanka20012008
TvoracJames V. HaxbyNikolaus Kriegeskorte
VrstafMRI pattern classification pipelinefMRI similarity structure comparison
Temeljni izvorNorman, K. A., Polyn, S. M., Detre, G. J., & Haxby, J. V. (2006). Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10(9), 424–430. DOI ↗Kriegeskorte, N., Mur, M., & Bandettini, P. A. (2008). Representational similarity analysis—connecting the branches of systems neuroscience. Frontiers in Systems Neuroscience, 2, 4. DOI ↗
Drugi naziviMVPA, brain decoding, pattern classificationRSA, representational geometry, similarity structure analysis
Srodne33
SažetakMultivariate Pattern Analysis (MVPA) is a machine learning approach to fMRI that decodes cognitive states, stimuli, or behavior from whole-brain spatial patterns of neural activity. Pioneered by Haxby and colleagues in 2001, MVPA treats fMRI as a classification problem: can a trained decoder predict what a person is perceiving or thinking based solely on their brain activity pattern?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.
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ScholarGateUsporedite metode: Multivariate Pattern Analysis · Representational Similarity Analysis. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare