title: Action potential onset dynamics and the response speed of neuronal populations.
abstract: The result of computational operations performed at the single cell level are coded into sequences of action potentials (APs). In the cerebral cortex, due to its columnar organization, large number of neurons are involved in any individual processing task. It is therefore important to understand how the properties of coding at the level of neuronal populations are determined by the dynamics of single neuron AP generation. Here, we analyze how the AP generating mechanism determines the speed with which an ensemble of neurons can represent transient stochastic input signals. We analyze a generalization of the theta-neuron, the normal form of the dynamics of Type-I excitable membranes. Using a novel sparse matrix representation of the Fokker-Planck equation, which describes the ensemble dynamics, we calculate the transmission functions for small modulations of the mean current and noise noise amplitude. In the high-frequency limit the transmission function decays as omega(-gamma), where gamma surprisingly depends on the phase theta(s) at which APs are emitted. If at theta(s) the dynamics is insensitive to external inputs, the transmission function decays as (i) omega(-3) for the case of a modulation of a white noise input and as (ii) omega(-2) for a modulation of the mean input current in the presence of a correlated and uncorrelated noise as well as (iii) in the case of a modulated amplitude of a correlated noise input. If the insensitivity condition is lifted, the transmission function always decays as omega(-1), as in conductance based neuron models. In a physiologically plausible regime up to 1 kHz the typical response speed is, however, independent of the high-frequency limit and is set by the rapidness of the AP onset, as revealed by the full transmission function. In this regime modulations of the noise amplitude can be transmitted faithfully up to much higher frequencies than modulations in the mean input current. We finally show that the linear response approach used is valid for a large regime of stimulus amplitudes.
authors.affiliation: Max-Planck-Institut für Dynamik und Selbstorganisation and Fakultät für Physik, Universität Göttingen, 37073 Göttingen, Germany.
authors.forename: B
authors.initials: B
authors.lastname: Naundorf
authors.forename: T
authors.initials: T
authors.lastname: Geisel
authors.forename: F
authors.initials: F
authors.lastname: Wolf
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology*; D008959:Models, Neurological; D009474:Neurons / Q000145:classification / Q000502:physiology*; D017711:Nonlinear Dynamics; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology; D013997:Time Factors