Information content and interpretation of CSD non-trivially depends on array density

Abstract

Abstract Objective. We aim to determine whether commonly-used current source density (CSD) estimation techniques provide valid results when used with recordings from the latest generation of high-density arrays and how the density affects signal interpretation. Approach. We first develop an analytic formulation for the contributions of Gaussian current sources to an estimated CSD as a function of current source position and array density. We then simulate local field potential recordings in a biophysically detailed model of a subvolume of rat somatosensory cortex, and compare estimated current source densities to the ground truth current densities averaged over relevant tissue volumes. Main results. Commonly used methods to estimate the CSD can produce spurious results when the inter-electrode spacing is small relative to the width of the current source, confusing sources and sinks. For high-density recording electrodes, the estimated CSD diverges from the volume-averaged ground-truth current distribution that the CSD estimation method attempts to reconstruct. Both confusion of sinks and sources and amplification of local current fluctuations play a role in this divergence. Careful choice of CSD reconstruction parameters can be used to preferentially reveal the information content on a local or higher-level scale. Significance. Our results shed light on high-spatial-frequency oscillations observed in estimated current source densities from in vivo experiments. Care must be taken when choosing a reconstruction method and interpreting the results from high density arrays, but proper parameter tuning allows to focus on specific information-of-interest. In addition, it was found that detailed network models, including active conductances and background noise, can be necessary to accurately simulate high-frequency current fluctuations.

The authors' abstract, as published at the source. Journal of Neural Engineering, 2026 · DOI ↗