TY - GEN
T1 - Modeling electrical stimulation of mammalian nerve fibers
T2 - 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
AU - Sadashivaiah, Vijay
AU - Sacre, Pierre
AU - Guan, Yun
AU - Anderson, William S.
AU - Sarma, Sridevi V.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/13
Y1 - 2017/9/13
N2 - Electrical neurostimulation is increasingly used over neuropharmacology to treat various diseases. Despite efforts to model the effects of electrical stimulation, its underlying mechanisms remain unclear. This is because current mechanistic models just quantify the effects that the electrical field produces near the fiber and do not capture interactions between stimulus-initiated action potentials (APs) and underlying physiological activity initiated APs. In this study, we aim to quantify and compare these interactions. We construct two computational models of a nerve fiber of varying degrees of complexity (probabilistic versus mechanistic) each receiving two inputs: the underlying physiological activity at one end of the fiber, and the external stimulus applied to the middle of the fiber. We then define reliability, R, as the percentage of physiological APs that make it to the other end of the nerve fiber. We apply the two inputs to the fiber at various frequencies and analyze reliability. We find that the probabilistic model captures relay properties for low input frequencies (< 10 Hz) but then differs from the mechanistic model if either input has a larger frequency. This is because the probabilistic model only accounts for only (i) inter signal loss of excitability and (ii) collisions between stimulus-initiated action potentials (APs) and underlying physiological activity initiated APs. This first step towards modeling the interactions in a nerve fiber opens up opportunities towards understanding mechanisms of electrical stimulation therapies.
AB - Electrical neurostimulation is increasingly used over neuropharmacology to treat various diseases. Despite efforts to model the effects of electrical stimulation, its underlying mechanisms remain unclear. This is because current mechanistic models just quantify the effects that the electrical field produces near the fiber and do not capture interactions between stimulus-initiated action potentials (APs) and underlying physiological activity initiated APs. In this study, we aim to quantify and compare these interactions. We construct two computational models of a nerve fiber of varying degrees of complexity (probabilistic versus mechanistic) each receiving two inputs: the underlying physiological activity at one end of the fiber, and the external stimulus applied to the middle of the fiber. We then define reliability, R, as the percentage of physiological APs that make it to the other end of the nerve fiber. We apply the two inputs to the fiber at various frequencies and analyze reliability. We find that the probabilistic model captures relay properties for low input frequencies (< 10 Hz) but then differs from the mechanistic model if either input has a larger frequency. This is because the probabilistic model only accounts for only (i) inter signal loss of excitability and (ii) collisions between stimulus-initiated action potentials (APs) and underlying physiological activity initiated APs. This first step towards modeling the interactions in a nerve fiber opens up opportunities towards understanding mechanisms of electrical stimulation therapies.
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U2 - 10.1109/EMBC.2017.8037701
DO - 10.1109/EMBC.2017.8037701
M3 - Conference contribution
C2 - 29060742
AN - SCOPUS:85032215044
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3868
EP - 3871
BT - 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 July 2017 through 15 July 2017
ER -