Mesoscopic Collective Activity in Excitatory Neural Fields: Governing Equations

TL;DR

This paper derives mesoscopic equations for collective cortical activity from Hodgkin-Huxley models, focusing on energy redistribution and excitability, providing a new framework for understanding neural field dynamics at an intermediate scale.

Contribution

The paper introduces a novel derivation of mesoscopic neural field equations from microscopic Hodgkin-Huxley models, emphasizing energy transfer and excitability at the mesoscale.

Findings

Supports wave-like oscillations with frequency-dependent propagation.

Equations are consistent with known excitatory neural field dynamics.

Framework can be extended to include more complex cell types.

Abstract

In this study we derive the governing equations for mesoscopic collective activity in the cortex, starting from the generic Hodgkin-Huxley equations for microscopic cell dynamics. For simplicity, and to maintain focus on the essential elements of the derivation, the discussion is confined to excitatory neural fields. The fundamental assumption of the procedure is that mesoscale processes are macroscopic with respect to cell-scale activity, and emerge as the average behavior of a large population of cells. Because of their duration, action-potential details are assumed not observable at mesoscale; the essential mesoscopic function of action potentials is to redistribute energy in the neural field. The Hodgkin-Huxley dynamical model is first reduced to a set of equations that describe subthreshold dynamics. An ensemble average over a cell population then produces a closed system of equations involving two mesoscopic state variables: the density of kinetic energy J, carried by sodium ionic currents, and the excitability H of the neural field, which could be described as the average state of gating variable h. The resulting model is represented as essentially a subthreshold process; and the dynamical role of the firing rate is naturally reassessed as describing energy transfers. The linear properties of the equations are consistent with expectations for the dynamics of excitatory neural fields: the system supports oscillations of progressive waves, with shorter waves typically having higher frequencies, propagating slower, and decaying faster. Extending the derivation to include more complex cell dynamics (e.g., including other ionic channels, e.g., calcium channels) and multiple-type, excitatory-inhibitory, neural fields is straightforward, and will be presented elsewhere.