Independent components of neural activity carry information on individual populations.

Helena Głąbska,Daniel K Wójcik,Szymon Łęski,Jan Potworowski,Gennady Cymbalyuk

doi:10.1371/journal.pone.0105071

Helena Głąbska, Daniel K Wójcik + Show 3 more

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https://doi.org/10.1371/journal.pone.0105071

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Abstract

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges.

Highlights

Local field potentials, the low-frequency part of the extracellular potential, are convenient signals to study activity of neural populations over temporal scales ranging from milliseconds to months [1,2]
These results show that applying the proposed method of analysis to simulated cortical Local field potential (LFP) allows one to obtain a good approximation of the activity of the individual cell populations of pyramidal cells with less reliable recovery of the activity of pyramidal cells from layer 6
By combining modeling of extracellular potentials in a largescale model of thalamocortical loop with data analysis employing Kernel Current Source Density (kCSD) and Independent Component Analysis (ICA) we showed that: N Spatiotemporal activity of model populations may not have simple product structure, it may not be possible to represent activity of a population with just one product component of the kind typically assumed in ICA or other decomposition methods (Fig. 7)

Summary

Introduction

The low-frequency part of the extracellular potential, are convenient signals to study activity of neural populations over temporal scales ranging from milliseconds to months [1,2]. Easy to record, they are difficult to interpret, because the low frequencies of the potential can carry over long distances from a source [3,4,5]. To extract activity of individual populations one can use different techniques for signal decomposition, for instance independent component analysis (ICA [6,7]) on which we shall concentrate in the present work, and success of several such approaches has been reported [8,9,10]

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