Cortical reliability amid noise and chaos

Max Nolte,James G King,Michael W Reimann,Henry Markram,Eilif B Muller

doi:10.1038/s41467-019-11633-8

Max Nolte, James G King + Show 3 more

Open Access

https://doi.org/10.1038/s41467-019-11633-8

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Abstract

Typical responses of cortical neurons to identical sensory stimuli appear highly variable. It has thus been proposed that the cortex primarily uses a rate code. However, other studies have argued for spike-time coding under certain conditions. The potential role of spike-time coding is directly limited by the internally generated variability of cortical circuits, which remains largely unexplored. Here, we quantify this internally generated variability using a biophysical model of rat neocortical microcircuitry with biologically realistic noise sources. We find that stochastic neurotransmitter release is a critical component of internally generated variability, causing rapidly diverging, chaotic recurrent network dynamics. Surprisingly, the same nonlinear recurrent network dynamics can transiently overcome the chaos in response to weak feed-forward thalamocortical inputs, and support reliable spike times with millisecond precision. Our model shows that the noisy and chaotic network dynamics of recurrent cortical microcircuitry are compatible with stimulus-evoked, millisecond spike-time reliability, resolving a long-standing debate.

Highlights

Typical responses of cortical neurons to identical sensory stimuli appear highly variable
When cellular noise sources are disabled, we find that the underlying deterministic network dynamics are chaotic, whereas when noise sources are enabled, an interplay of stochastic synaptic transmission and network dynamics determines the rate by which membrane potentials diverge
Combined with chaotic network dynamics, this could lead to highly variable activity trajectories

Summary

Introduction

Typical responses of cortical neurons to identical sensory stimuli appear highly variable. The potential role of spike-time coding is directly limited by the internally generated variability of cortical circuits, which remains largely unexplored. We quantify this internally generated variability using a biophysical model of rat neocortical microcircuitry with biologically realistic noise sources. It is compelling to assume that intrinsic noise plays a negligible role, and that cortical variability is essentially deterministic[11], encoding hidden or unobserved variables This view is supported by the fact that neocortical neurons respond to somatic current injections in vitro with high reliability[12]. They respond highly irregularly to somatic current injections, due to amplified ion-channel noise[20]

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