Spike timing prediction with active dendrites

TL;DR

This paper introduces a simplified two-compartment model of pyramidal neurons with active dendrites that accurately predicts spike timing, emphasizing the importance of dendritic activity in neuronal dynamics.

Contribution

The study presents a minimalistic, experimentally grounded two-compartment model that effectively predicts spike timing in pyramidal neurons, highlighting dendritic activity's role.

Findings

Two-compartment model accurately predicts spike times.

Active dendrites are essential for realistic neuronal dynamics.

Model uses measurable impulse-response functions.

Abstract

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 tuft 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 dendritic tuft is required to properly account for the dynamics of layer 5 pyramidal cells under in-vivo-like conditions.