Spike correlations: Beyond pairwise interaction models

LISANDRO MONTANGIE; OSVALDO A ROSSO; FERNANDO MONTANI

Workshop; LAWNP 2013; 2013

To understand how information is processed by the brain we need to investigate how information is encoded by the activity of a population of neurons. Despite providing an accurate description of the neurophysiological behavior of the neurons in the retina, pairwise interaction models do not always provide a realistic characterization of the population dynamics in the cortex, and higher order interactions should be taken into account. In this work, we present an information theoretical approach by means of an analytically solvable model to formally estimate spike correlations up to third order within maximum entropy principle. Furthermore, we apply the current formalism to study functional interactions underlying the neural code dynamics in healthy and unhealthy tissue.