Evaluating Information Transfer Between Auditory Cortical Neurons

Abstract

Transfer entropy, presented as a new tool for investigating neural assemblies, quantifies the fraction of information in a neuron found in the past history of another neuron. The asymmetry of the measure allows feedback evaluations. In particular, this tool has potential applications in investigating windows of temporal integration and stimulus-induced modulation of firing rate. Transfer entropy is also able to eliminate some effects of common history in spike trains and obtains results that are different from cross-correlation. The basic transfer entropy properties are illustrated with simulations. The information transfer through a network of 16 simultaneous multiunit recordings in cat's auditory cortex was examined for a large number of acoustic stimulus types. Application of the transfer entropy to a large database of multiple single-unit activity in cat's primary auditory cortex revealed that most windows of temporal integration found during spontaneous activity range between 2 and 15 ms. The normalized transfer entropy shows similarities and differences with the strength of cross-correlation; these form the basis for revisiting the neural assembly concept.