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

1364-503X

Neurons tend to fire a spike when they are near a bifurcation from the resting state to spiking activity. It is a delicate balance between noise, dynamiccurrents and initial condition that determines the phase diagram of neural activity. Many possible ionic mechanisms can be accounted for as the source ofspike generation. Moreover, the biophysics and the dynamics behind it can usually be described through a phase diagram that involves membrane voltageversus the activation variable of the ionic channel. In this paper, we present a novel methodology to characterize the dynamics of this system, which takesinto account the fine temporal ?structures? of the complex neuronal signals. This allows us to accurately distinguish the most fundamental properties ofneurophysiological neurons that were previously described by Izhikevich considering the phase-space trajectory, using a time causal space: statisticalcomplexity versus Fisher information versus Shannon entropy.