Poster; "Information Theory approach to characterize the internal structure of the rhythmic oscillation patterns"

EMILIA B. DELEGLISE; FERNANDO MONTANI

Congreso; Congreso Sociedad Argentina de Investigación en Neurociencias 2012; 2012

The classical point of view is that neurons transmit information exclusively via modulations of their mean firing rates, however it is well established that neurons can fire spike patterns with a few milliseconds of temporal precision. To gain a better understanding of how information is transmitted in the brain we need therefore to learn how characterize first the fine temporal structure of complex neuronal signals not just using the probability distributions associated with inter-spike intervals, but also using much more subtle measures which could account for its causal structure. In this work, we use an Information Theory measure to characterize the self-sustained rhythmic oscillation of a minimal model simulating the neural spiking activity.