Abstract

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

Highlights

  • The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code

  • We investigated the relationship between the shape of the Inter-Spike Interval (ISI) distribution and information transmission by calculating information transmission between two simulated neuronal populations while varying the properties of the network

  • The Intra-Burst Interval (IBI) distribution could overlap with the Inter-Event Interval (IEI) distribution

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Summary

Introduction

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. We found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. The vast majority of neurons in the brain communicate complex and irregular sequences of voltage spikes—a window into neuronal information processing These spike trains may be parsed into recurring syllables, a small set of short spike timing patterns bearing potentially different meanings. We quantified the linearly decodable information between inputs applied to a simulated ensemble of cells utilizing the burst m­ ultiplexing[20] burst code (see Fig. 1Bi) and readouts that mimic synaptic processing as a function of changing firing statistics.

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