Reservoirs of Stability: Flux Tubes in the Dynamics of Cortical Circuits

TL;DR

This paper introduces a minimal model of cortical circuit dynamics showing how flux tubes enable rapid state separation following single spikes while maintaining overall stability, providing insights into cortical network sensitivity.

Contribution

It presents a unifying framework of flux tubes that explains how cortical networks can be both highly sensitive to perturbations and dynamically stable.

Findings

Single spike perturbations cause exponential state separation.

Flux tubes enclose stable trajectories in network state space.

Networks exhibit stability to infinitesimal perturbations despite sensitivity.

Abstract

Triggering a single additional spike in a cerebral cortical neuron was recently demonstrated to cause a cascade of extra spikes in the network that is likely to rapidly decorrelate the network's microstate. The mechanisms involved in this extreme sensitivity of cortical networks are currently not well understood. Here, we show in a minimal model of cortical circuit dynamics that exponential state separation after single spike and even single synapse perturbations coexists with dynamical stability to infinitesimal state perturbations. We propose a unifying picture of exponentially separating flux tubes enclosing unique stable trajectories composing the networks' state spaces.