title: Causal information quantification of prominent dynamical features of biological neurons.
abstract: 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, dynamic currents and initial condition that 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 usually be 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, which 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 versus Fisher information versus Shannon entropy.
authors.affiliation: Instituto de Física de Líquidos y Sistemas Biológicos (IFLYSIB), CONICET, and Universidad Nacional de La Plata, Calle 59-789, La Plata 1900, Argentina fmontani@gmail.com.
authors.forename: Fernando
authors.initials: F
authors.lastname: Montani
authors.affiliation: Instituto de Física de Líquidos y Sistemas Biológicos (IFLYSIB), CONICET, and Universidad Nacional de La Plata, Calle 59-789, La Plata 1900, Argentina.
authors.forename: Roman
authors.initials: R
authors.lastname: Baravalle
authors.affiliation: Instituto de Física de Líquidos y Sistemas Biológicos (IFLYSIB), CONICET, and Universidad Nacional de La Plata, Calle 59-789, La Plata 1900, Argentina.
authors.forename: Lisandro
authors.initials: L
authors.lastname: Montangie
authors.affiliation: Instituto Tecnológico de Buenos Aires (ITBA), Av Eduardo Madero 399, C1106ACD Ciudad Autónoma de Buenos Aires, Argentina Instituto de Física, Universidade Federal de Alagoas (UFAL), BR 104 Norte km 97, 57072-970 Maceió, Alagoas, Brazil.
authors.forename: Osvaldo A
authors.initials: OA
authors.lastname: Rosso
mesh_terms: D000818:Animals; D001703:Biophysics; D001921:Brain / Q000502:physiology; D003198:Computer Simulation; D004569:Electroencephalography; D006801:Humans; D008564:Membrane Potentials; D008959:Models, Neurological; D015233:Models, Statistical; D009474:Neurons / Q000502:physiology*; D009991:Oscillometry; D012815:Signal Processing, Computer-Assisted; D009435:Synaptic Transmission
keywords: Fisher information measure; entropy; neurons; statistical complexity