Development of novel signal and spike velocity analysis tools in compact peripheral nerve recording designs.

Abstract

Objective: Analysis tools for peripheral nerve recordings remain underdeveloped compared to those for brain signals, limiting the advancement of nerve neurotechnologies for clinical treatments such as closed-loop systems. This study introduces and explores the performance of two novel nerve signal analysis techniques - cross-correlation analysis and spike delay velocity analysis - which rely on a defining feature of peripheral nerve signals: the reliable conduction velocity of signals transmitted by axons in nerves. Approach. We test the capabilities of the introduced cross-correlation and spike delay velocity analysis techniques both in silico on synthetic nerve signals and on in vivo nerve signals acquired from freely-moving rats. Main results. Our findings show that both techniques can be successfully employed to extract transmission direction and velocity information from compact two-electrode site peripheral nerve recording designs. Notably, cross-correlation analysis can be employed to detect neural signals of very low signal-to-noise ratio, otherwise undetectable by typical spike detection approaches. Significance. Our findings provide new techniques to both enhance detection and extract new information in the form of velocity data from nerve recordings using a compact two-electrode site recording setup. Unlike traditional methods, this design eliminates the need for long electrode arrays, making it particularly well-suited for use in freely-moving animal models and translational applications. As axon signal conduction direction and velocity is tightly linked to neural function, these techniques can support new research into peripheral nervous system function and new therapeutic approaches driven by neural interfaces.