Final colloquium Hubald Verzijl
26 October 2021 14:00 till 14:45 - Location: Aula Senaatszaal - By: DCSC
"Mitigating Neuropathic Pain: From Theory to Practice. Inhibiting Neuroma Pain In-silico and Measuring Neural Activity In-vivo"
Neuropathic pain (NP) affects approximately seven to ten percent of the general population. Seventeen percent of NP patients scored their life as “worse than death”. A myriad of causes may underlie NP, such as stroke or spinal cord injury. Also, damage or disease of the peripheral nervous system (PNS) may result in NP. One of the main issues of NP caused by a PNI is the development of a neuroma, which is a tumor-like mass at the proximal end of a severed nerve that can become very painful.
Neuromas show unique neurophysiological characteristics. Cell membrane alternations result in different ion channel distributions what results in subthreshold oscillations (SO) and ectopic discharges (ED). It is assumed that this behavior could lead to NP generation. Theoretically, by neutralizing SO and ED, it should be possible to mitigate the generation of NP.
We propose a methodology to neutralize SO and ED that consists of several steps. First, the nerve activity is real-time monitored. Secondly, an algorithm is designed that finds electrical neurostimulation (ENS) patterns that neutralize SO and ED. Finally and thirdly, these patterns are applied to the nerve by an electrical stimulator.
Neurophysiological signals contain much information and potentially also activity from peripheral neuromas that generate SO and ED. These signals from peripheral origins are not commonly measured, emphasizing the need for a dedicated setup, capable of measuring this nerve activity. We designed a full functional, validated and in-vivo tested neural amplifier for microneurography. Recordings in lugworms and rats reveal nerve activity at the level of a single or a few axons. This setup can further be used to measure activity from a peripheral origin, potentially also pain-related activity as SO and ED.
To design a SO and ED neutralizing algorithm, we seek to provide a data-driven real-time (closed-loop) ENS that suppresses SO and ED in individual neurons in-silico. Because of related stimulation, neurophysiological, and computational limitation constraints, we leverage a scheme known as model predictive control (MPC). We use a class of models known as fractional-order systems (FOS) as a proxy to avoid complex models. We show that by applying MPC with a FOS proxy, it is possible to neutralize SO and ED in three well-established mathematical models of neuropathic pain. Since SO and ED are considered drivers of NP, suppression might mitigate pain.
To close the loop, the suggested (arbitrary shaped) ENS patterns from the in-silico experiments should be applied at the peripheral nerve. Currently, available ENS systems cannot implement arbitrary waveforms at biological tissue. We elaborated on methods to implement arbitrary waveforms using pulse-width modulated (PWM) signals by taking advantage of the biological tissue’s dielectric properties. Increasing the PWM frequency is required, or a low-pass filter should be added to the stimulator’s output. These results urge for further research into ENS designs for arbitrary waveform implementation.
This thesis provides essential building blocks to apply our proposed strategy in-vivo eventually. We conclude this work with a review of the ultimate goal: relief of NP. We outline the next steps within this project that are required to translate NP mitigation from theory to practice.
Join Zoom meeting:
Dr. S. Pequito