Topic: multi-area neural recording

A number of recent studies have explored the analysis of multi-area neural recording data and, in particular, the shared communication, computation and representational subspaces between brain areas. These have largely relied upon model-based methods to quantify shared variability between areas, but a standard, model-free measure is lacking. In this work we 1) present a candidate for this measure that we call the effective number of shared dimensions (ENSD), 2) demonstrate the utility and computational efficiency of our measure by visiting results from two recent studies (the "communication su