_:nc05c453c77e54bcba5acd2fa82b8e026xb0
<http://schema.org/description>
"Representational similarity analysis (RSA) has been shown to be an effective\nframework to characterize brain-activity profiles and deep neural network\nactivations as representational geometry by computing the pairwise distances of\nthe response patterns as a representational dissimilarity matrix (RDM).\nHowever, how to properly analyze and visualize the representational geometry as\ndynamics over the time course from stimulus onset to offset is not well\nunderstood. In this work, we formulated the pipeline to understand\nrepresentational dynamics with RDM movies and Procrustes-aligned\nMultidimensional Scaling (pMDS), and applied it to neural recording of monkey\nIT cortex. Our results suggest that the the multidimensional scaling alignment\ncan genuinely capture the dynamics of the category-specific representation\nspaces with multiple visualization possibilities, and that object\ncategorization may be hierarchical, multi-staged, and oscillatory (or\nrecurrent)."
<https://deepai.org/publication/visualizing-representational-dynamics-with-multidimensional-scaling-alignment>