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| Anàlisi de Similitud Representacional× | Anàlisi de Xarxes Cerebrals Gràfiques× | |
|---|---|---|
| Camp | Neuroimatge | Neuroimatge |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 2008 | 2009 |
| Autor original≠ | Nikolaus Kriegeskorte | Ed Bullmore |
| Tipus≠ | fMRI similarity structure comparison | Brain network graph analysis pipeline |
| 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. DOI ↗ | Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186–198. DOI ↗ |
| Àlies | RSA, representational geometry, similarity structure analysis | graph theory, brain network analysis, network neuroscience |
| Relacionats | 3 | 3 |
| 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. | Graph Theoretical Brain Network Analysis applies network science to understand brain organization, treating the brain as a complex network of interconnected nodes (regions) and edges (connections). Formalized by Bullmore and Sporns in 2009, graph analysis reveals fundamental organizational principles—modularity, efficiency, resilience—that characterize healthy and diseased brains. |
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