Development of novel signal and spike velocity analysis tools in peripheral nerve cuffs

ObjectivePeripheral nerve neurotechnologies hold significant promise as avenues for new closed-loop clinical treatments. However, analysis tools for nerve recordings - a key component of closed-loop nerve technologies - remain underdeveloped compared to brain-focused methods. This study introduces and explores the performance of two novel nerve signal analysis techniques which rely on a defining feature of peripheral nerve signals: the reliable conduction velocity of signals transmitted by axons in nerves. ApproachWe 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 resultsOur findings show that both techniques can be successfully employed to extract transmission direction and velocity information from nerve cuff recordings. 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. SignificanceOur findings provide new techniques to both enhance detection and extract new information in the form of velocity data from nerve recordings. 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.