Representational similarity analysis (RSA) tests models of brain computation by investigating how neural activity patterns reflect experimental conditions. Instead predicting directly, the predict geometry representation, as defined representational dissimilarity matrix (RDM), which captures similar or dissimilar different associated conditions are. RSA therefore first quantifies calculating a ...

Spectral clustering is a powerful clustering method for document data set. However, spectral clustering needs to solve an eigenvalue problem of the matrix converted from the similarity matrix corresponding to the data set. Therefore, it is not practical to use spectral clustering for a large data set. To overcome this problem, we propose the method to reduce the similarity matrix size. First, u...

Figure 6: Strongly related (SSM based) functional sets and similarities between them, Case Study I. Nodes represent set of closely related methods; weight of the edge between two nodes represents the average value of SSM among the methods of the corresponding sets. Non trivial sets are represented by smaller circles and are merged with trivial sets (bigger circles) of the same color.. Figure 11...