Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis
Fig 4
Representational dissimilarity matrices (RDMs) for the models used in simulation.
Each entry of an RDM shows the dissimilarity between the patterns associated with two experimental conditions. RDMs are symmetric about a diagonal of zeros. Note that while zero is meaningfully defined (no difference between conditions), the scaling of the distances is arbitrary. For Experiment 1, the distance between the activity patterns for the five fingers are predicted from the structure of (A) muscle activity and (B) the natural statists of movement. In Experiment 2 (C, D) the same models predict the representational dissimilarities between finger movements for 31 piano-like chords. For Experiment 3 (E, F), model predictions come from the activity of the seven layers of a deep convolutional neural network in response to 96 visual stimuli. The 1st convolutional layer and the 1st fully connected layer are shown as examples.