Spike-timing prediction in cortical neurons with active dendrites.

Richard Naud (1) , Brice Bathellier (2, 3) , Wulfram Gerstner (4)

1 University of Ottawa [Ottawa]
2 INAF - Institut de Neurobiologie Alfred Fessard
3 UNIC - Unité de Neurosciences Information et Complexité [Gif sur Yvette]
4 School of Computer and Communication Sciences and Brain-Mind Institute

A complete single-neuron model must correctly reproduce the firing of spikes and bursts. We present a study of a simplified model of deep pyramidal cells of the cortex with active dendrites. We hypothesized that we can model the soma and its apical dendrite with only two compartments, without significant loss in the accuracy of spike-timing predictions. The model is based on experimentally measurable impulse-response functions, which transfer the effect of current injected in one compartment to current reaching the other. Each compartment was modeled with a pair of non-linear differential equations and a small number of parameters that approximate the Hodgkin-and-Huxley equations. The predictive power of this model was tested on electrophysiological experiments where noisy current was injected in both the soma and the apical dendrite simultaneously. We conclude that a simple two-compartment model can predict spike times of pyramidal cells stimulated in the soma and dendrites simultaneously. Our results support that regenerating activity in the apical dendritic is required to properly account for the dynamics of layer 5 pyramidal cells under in-vivo-like conditions.

Domaines: Sciences cognitives

Richard Naud, Brice Bathellier, Wulfram Gerstner. Spike-timing prediction in cortical neurons with active dendrites.. Frontiers in Computational Neuroscience, 2013, 8, pp.90. ⟨10.3389/fncom.2014.00090⟩. ⟨hal-01179725⟩