Noise-enhanced coding in phasic neuron spike trains.

Cheng Ly,Brent Doiron,Gennady Cymbalyuk

doi:10.1371/journal.pone.0176963

Cheng Ly, Brent Doiron + Show 1 more

Open Access

https://doi.org/10.1371/journal.pone.0176963

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Abstract

The stochastic nature of neuronal response has lead to conjectures about the impact of input fluctuations on the neural coding. For the most part, low pass membrane integration and spike threshold dynamics have been the primary features assumed in the transfer from synaptic input to output spiking. Phasic neurons are a common, but understudied, neuron class that are characterized by a subthreshold negative feedback that suppresses spike train responses to low frequency signals. Past work has shown that when a low frequency signal is accompanied by moderate intensity broadband noise, phasic neurons spike trains are well locked to the signal. We extend these results with a simple, reduced model of phasic activity that demonstrates that a non-Markovian spike train structure caused by the negative feedback produces a noise-enhanced coding. Further, this enhancement is sensitive to the timescales, as opposed to the intensity, of a driving signal. Reduced hazard function models show that noise-enhanced phasic codes are both novel and separate from classical stochastic resonance reported in non-phasic neurons. The general features of our theory suggest that noise-enhanced codes in excitable systems with subthreshold negative feedback are a particularly rich framework to study.

Highlights

We have shown that in the presence of noise, the coding of phasic systems is rich, allowing phasic systems to code for low frequency inputs
Others have demonstrated computationally that background fluctuations can lead to better coding of slow signals [9, 10, 28], we capture the essence of this effect with a 2D planar model which subsequently motivates a reduced phenomenological description of the dynamics
Our analysis enables parsing of the various pieces that contribute to the observed effect

Summary

Introduction

In most models of phasic neurons, this high pass nature is achieved by a subthreshold negative feedback process, often from a low threshold K+ channel dynamic [5, 7, 10, 21,22,23]. Before we consider the response to dynamic input we note that real phasic neurons have a strong subthreshold negative feedback (often a voltage gated K+ channel), whose timescale determines the high pass property of the spike train response [7,8,9,10].

Results

Conclusion