title: Deterministic excitable media under Poisson drive: power law responses, spiral waves, and dynamic range.
abstract: When each site of a spatially extended excitable medium is independently driven by a Poisson stimulus with rate h , the interplay between creation and annihilation of excitable waves leads to an average activity F . It has recently been suggested that in the low-stimulus regime (h approximately 0) the response function F(h) of hypercubic deterministic systems behaves as a power law, F approximately h{m} . Moreover, the response exponent m has been predicted to depend only on the dimensionality d of the lattice, m=1/(1+d) [T. Ohta and T. Yoshimura, Physica D 205, 189 (2005)]. In order to test this prediction, we study the response function of excitable lattices modeled by either coupled Morris-Lecar equations or Greenberg-Hastings cellular automata. We show that the prediction is verified in our model systems for d=1 , 2, and 3, provided that a minimum set of conditions is satisfied. Under these conditions, the dynamic range-which measures the range of stimulus intensities that can be coded by the network activity-increases with the dimensionality d of the network. The power law scenario breaks down, however, if the system can exhibit self-sustained activity (spiral waves). In this case, we recover a scenario that is common to probabilistic excitable media: as a function of the conductance coupling G among the excitable elements, the dynamic range is maximized precisely at the critical value G_{c} above which self-sustained activity becomes stable. We discuss the implications of these results in the context of neural coding.
authors.affiliation: Laboratório de Física Teórica e Computacional, Departamento de Física, Universidade Federal de Pernambuco, 50670-901 Recife, PE, Brazil. tlr@df.ufpe.br
authors.forename: Tiago L
authors.initials: TL
authors.lastname: Ribeiro
authors.forename: Mauro
authors.initials: M
authors.lastname: Copelli
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*; D009475:Neurons, Afferent / Q000502:physiology*; D016012:Poisson Distribution