Cortical Entropy Values Correlate With Brain Scale-Free Dynamics

Abstract

A two-dimensional shadow may encompass more information than its corresponding three-dimensional object. If we rotate the object, we achieve a pool of observed shadows from different angulations, gradients, shapes and variable length contours that make it possible for us to increase our available information. Starting from this simple observation, we show how informational entropies might turn out to be useful in the evaluation of scale-free dynamics in the brain. Indeed, brain activity exhibits a scale-free distribution, which appears as a straight line when plotted in a log power versus log frequency plot. A variation in the scale-free exponent and in the line scaling slope may occur during different functional neurophysiological states. Here we show that modifications in scaling slope are associated with variations in Renyi entropy, a generalization of Shannon informational entropy. From a three-dimensional object's perspective, by changing its orientation (standing for the cortical scale-free exponent), we detect different two-dimensional shadows from different perception angles (standing for Renyi entropy in different brain areas). We perform simulations showing how, starting from known values of Renyi entropy (easily detectable in brain fMRIs or EEG traces), it is feasible to calculate the scaling slope in a given moment and a given brain area. Because changes in scale-free cortical dynamics modify brain activity, suggests the possibility of novel insights in mind reading and description of the forces required for transcranial stimulation.