Action potential identification in rodent sympathetic nerve recordings using a wavelet-based approach.

The sympathetic nervous system is a master regulator of cardiovascular function. Over the last two decades there has been renewed interest in identifying the underlying behavior of post-ganglionic sympathetic nerves. By using wavelet-based approaches to isolate underlying action potentials (APs) within multi-unit recordings, tremendous progress has been made to better understand the firing characteristics of individual, and clusters of, sympathetic neurons. These studies, however, have applied these approaches within the context of muscle sympathetic nerve activity recorded from humans, limiting the depth of experimentation into mechanisms that determine sympathetic action potential behaviours and patterns. Here, we extended and refined this wavelet-based approach and uniquely apply it to the measurement of sympathetic nerve activity directed towards the critical splanchnic vascular bed in rodents (i.e., splanchnic sympathetic nerve activity; sSNA). We subsequently quantified AP occurrence within and across bursts and employed k-means clustering on the amplitude of APs and bursts. We first demonstrate that a wavelet-based approach is feasible to implement in rodent recordings. We subsequently show that there is a significant increase in the proportion of large APs and decrease in the proportion of small APs as burst size increases (p < 0.001). Analysis of AP amplitude and latency demonstrated a significant negative association (p < 0.001), indicating that larger APs exhibit shorter latencies. Finally, we demonstrate good agreement between a group-averaged mother wavelet and individual animal mother wavelets. This methodological advance sets the stage for rodent-based mechanistic studies to further understand communication strategies employed by the sympathetic nervous system.