Complexity Leads to Simplicity: A Consensus Layer V Pyramidal Neuron Can Sustain Interpulse-Interval Coding

TL;DR

This study investigates the potential of interpulse interval coding in layer V pyramidal neurons, revealing a linear input-TTS relationship and estimating mutual information capacity, challenging traditional passive neuron models.

Contribution

It demonstrates the feasibility of IPI coding in biophysical neuron models and identifies dominant noise sources affecting information rate.

Findings

Synaptic noise is the primary noise source.

A linear relationship exists between input intensity and inverse TTS.

Mutual information per spike is approximately 3 bits.

Abstract

In terms of the long-distance communication of a single neuron, interpulse intervals (IPIs) are a possible alternative to rate and binary codes. As a proxy for IPI, the time-to-spike (TTS) for a neuron can be found in the biophysical and experimental literature. Using the current, consensus layer V pyramidal neuron, the present study examines the feasibility of IPI-coding and examines the noise sources that limit the information rate of such an encoding. In descending order of noise intensity, the noise sources are (i) synaptic variability, (ii) sodium channel shot-noise, followed by (iii) thermal noise with synaptic noise much greater than the sodium channel-noise. More importantly, the biophysical model demonstrates a linear relationship between input intensity and inverse TTS. This linear observation contradicts the assumption that a neuron should be treated as a passive, electronic circuit (an RC circuit, as in the Stein model). Finally, the biophysical simulations allow the calculation of mutual information, which is about 3.0 bits/spike.