Visualizing Representational Dynamics with Multidimensional Scaling Alignment

@article{Lin2019VisualizingRD,
  title={Visualizing Representational Dynamics with Multidimensional Scaling Alignment},
  author={Baihan Lin and Marieke Mur and T. Kietzmann and Nikolaus Kriegeskorte},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.09264}
}
Representational similarity analysis (RSA) has been shown to be an effective framework to characterize brain-activity profiles and deep neural network activations as representational geometry by computing the pairwise distances of the response patterns as a representational dissimilarity matrix (RDM). However, how to properly analyze and visualize the representational geometry as dynamics over the time course from stimulus onset to offset is not well understood. In this work, we formulated the… 

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