Causal information quantification of prominent dynamical features of biological neurons

FERNANDO MONTANI; ROMAN BARAVALLE; LISANDRO MONTANGIE; OSVALDO A. ROSSO

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

ROYAL SOC

Lugar: Londres; Año: 2015 vol. 373 p. 10901 - 10914

1364-503X

Neurons tend to fire a spike when they are near a bifurcation from resting state to spiking activity. It is a delicate balance between noise, dynamic currents and initial condition what determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source of spike generation; moreover, the biophysics and the dynamics behind it can be usually described through a phase diagram that involves membrane voltage versus the activation variable of the ionic channel. In this paper, we present a novel methodology to characterize the dynamics of this system, that takes into account the fine temporal ``structures" of the complex neuronal signals. This allows us to accurately distinguish the most fundamental properties of neurophysiological neurons that were previously described by Izhikevich considering the phase-space trajectory, using a time causal space: Statistical Complexity vs. Fisher Information vs. Shannon Entropy.