Cluster method for analysis of transmitted information in multivariate neuronal data

Abstract
A new method for quantifying the transmitted information and channel capacity of high-dimensional data, based on cluster formation, is described. The method's ability to handle high-dimensional data allows for a complete measurement of information transmitted by neuronal data. It is computationally efficient in terms of both processing time and memory storage. Application of the method to the responses of a V1 neuron shows that more information was transmitted about the pattern of stimuli than about their color.