Sequence learning recodes cortical representations instead of strengthening initial ones
Fig 3
Testing the predictions of learning models using RSA.
Left: model prediction expressed as a representational dissimilarity matrix (RDM) of pairwise between-stimulus distances (the cells in the matrix display the associative learner predictions in terms of item-position associations as quantified by the Hamming distance). The small matrices on the top refer to the representations of individual sequences in the matrix form (as shown on Fig 1). For example, second cell in the first row is the predicted Hamming distance between sequences presented on trials 1 and 2. Right: RDM of measured voxel activity patterns elicited by the stimuli. The small matrices are illustrative representations of voxel patterns from an arbitrary brain region. The correlation between these two RDMs reflects the evidence for the predictive model. The significance of the correlation can be evaluated via permuting the labels of the matrices and thus deriving the null-distribution. See Representational similarity analysis (RSA) in Methods for details.