Statistical mechanics of neocortical interactions: large-scale EEG influences on molecular processes

TL;DR

This paper explores how large-scale neuronal synchrony during EEG recordings influences molecular calcium processes, using a statistical mechanics model to connect macroscopic EEG signals with microscopic molecular activity.

Contribution

It introduces a novel coupling mechanism linking EEG signals to calcium wave dynamics, integrating statistical mechanics with EEG analysis for the first time.

Findings

EEG signals are sensitive to calcium wave-mediated synaptic interactions.

The SMNI model effectively fits EEG data during short-term memory tasks.

Large-scale neuronal activity can influence molecular processes via electromagnetic coupling.

Abstract

Recent calculations further supports the premise that large-scale synchronous firings of neurons may affect molecular processes. The context is scalp electroencephalography (EEG) during short-term memory (STM) tasks. The mechanism considered is $\mathbf{\Pi} = \mathbf{p} + q \mathbf{A}$ (SI units) coupling, where $\mathbf{p}$ is the momenta of free $\mathrm{Ca}^{2+}$ waves $q$ the charge of $\mathrm{Ca}^{2+}$ in units of the electron charge, and $\mathbf{A}$ the magnetic vector potential of current $\mathbf{I}$ from neuronal minicolumnar firings considered as wires, giving rise to EEG. Data has processed using multiple graphs to identify sections of data to which spline-Laplacian transformations are applied, to fit the statistical mechanics of neocortical interactions (SMNI) model to EEG data, sensitive to synaptic interactions subject to modification by $\mathrm{Ca}^{2+}$ waves.