# Analysis and Modelling of Subthreshold Neural Multi-electrode Array Data by Statistical Field Theory

## TL;DR

This paper develops a Gaussian statistical field theory model to characterize subthreshold neural fluctuations in multi-electrode array data, revealing correlations related to neural connectivity and spike activity.

## Contribution

The paper introduces a novel theoretical framework for analyzing subthreshold neural signals using Gaussian field theory, applied to real MEA data from rat hippocampal slices.

## Key findings

- Empirical correlation functions follow logarithmic behavior predicted by the model.
- Clear correlation between neural activity and spike occurrence.
- Artefact removal is crucial for accurate analysis.

## Abstract

Multi-electrode arrays (MEA) are increasingly used to investigate spontaneous neuronal network activity. The recorded signals comprise several distinct components: Apart from artefacts without biological significance, one can distinguish between spikes (action potentials) and subthreshold fluctuations (local fields potentials). Here we aim to develop a theoretical model that allows for a compact and robust characterization of subthreshold fluctuations in terms of a Gaussian statistical field theory in two spatial and one temporal dimension. What is usually referred to as the driving noise in the context of statistical physics is here interpreted as a representation of the neural activity. Spatial and temporal correlations of this activity give valuable information about the connectivity in the neural tissue. We apply our methods on a dataset obtained from MEA-measurements in an acute hippocampal brain slice from a rat. Our main finding is that the empirical correlation functions indeed obey the logarithmic behaviour that is a general feature of theoretical models of this kind. We also find a clear correlation between the activity and the occurence of spikes. Another important insight is the importance of correcly separating out certain artefacts from the data before proceeding with the analysis.