Characterizing and Optimizing Spatial Selectivity of Peripheral Nerve Stimulation Montages and Electrode Configurations In Silico

Spatially selective nerve stimulation is an active area of research, with the capability to reduce side effects and increase the clinical efficacy of nerve stimulation technologies. Several research groups have demonstrated proof-of-concept devices capable of performing spatially selective stimulation with multi-contact cuff electrodes in vivo; however, optimizing the technique is difficult due to the large possibility space granted by a multi-electrode cuff. Our work attempts to elucidate the most valuable stimulation montages (current ratios between stimulating electrodes) provided by a multi-contact cuff. We characterized the performance of five different montage types when stimulating fibers in different “electrode configurations”, with configurations including up to three rings of electrode contacts, 13 different counts of electrodes per ring, and five electrode arc lengths per electrode count (for 195 unique configurations). Selected montages included several methods from prior art, as well as our own. Among montage types, the most spatially selective stimulation was one we refer to as “X-Adjacent” stimulation, in which three adjacent electrodes are active per ring. Optimized X-adjacent montages achieved an average fiber specificity of 71.9% for single-ring electrode configurations when stimulating fibers located at a depth of two-thirds of the nerve radius, and an average fiber specificity of 77.2% for two-ring configurations. These values were the highest among montages tested, and in combination with our other metrics, led these montages to perform best in the majority of cost functions investigated. This success leads us to recommend X-Adjacent montages to researchers exploring spatially selective stimulation.

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Publication Details

Journal
Algorithms
Published
2025-10-09
DOI
https://doi.org/10.3390/a18100635
Primary Topic
Neuroscience and Neural Engineering
Type
article
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article

Characterizing and Optimizing Spatial Selectivity of Peripheral Nerve Stimulation Montages and Electrode Configurations In Silico

Vasav Shah, Wentai Liu, Ryan Kochis, Jonathan P. Brand
Algorithms
Neuroscience and Neural Engineering
article

Characterizing and Optimizing Spatial Selectivity of Peripheral Nerve Stimulation Montages and Electrode Configurations In Silico

Vasav Shah, Wentai Liu, Ryan Kochis, Jonathan P. Brand
article en

Abstract

Spatially selective nerve stimulation is an active area of research, with the capability to reduce side effects and increase the clinical efficacy of nerve stimulation technologies. Several research groups have demonstrated proof-of-concept devices capable of performing spatially selective stimulation with multi-contact cuff electrodes in vivo; however, optimizing the technique is difficult due to the large possibility space granted by a multi-electrode cuff. Our work attempts to elucidate the most valuable stimulation montages (current ratios between stimulating electrodes) provided by a multi-contact cuff. We characterized the performance of five different montage types when stimulating fibers in different “electrode configurations”, with configurations including up to three rings of electrode contacts, 13 different counts of electrodes per ring, and five electrode arc lengths per electrode count (for 195 unique configurations). Selected montages included several methods from prior art, as well as our own. Among montage types, the most spatially selective stimulation was one we refer to as “X-Adjacent” stimulation, in which three adjacent electrodes are active per ring. Optimized X-adjacent montages achieved an average fiber specificity of 71.9% for single-ring electrode configurations when stimulating fibers located at a depth of two-thirds of the nerve radius, and an average fiber specificity of 77.2% for two-ring configurations. These values were the highest among montages tested, and in combination with our other metrics, led these montages to perform best in the majority of cost functions investigated. This success leads us to recommend X-Adjacent montages to researchers exploring spatially selective stimulation.

AlgorithmsVol. 18(10)
California NanoSystems Institute (US), University of California, Los Angeles (US)
Openalex Percentile: Top 69%
Neuroscience and Neural Engineering
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Characterizing and Optimizing Spatial Selectivity of Peripheral Nerve Stimulation Montages and Electrode Configurations In Silico — Vasav Shah, Wentai Liu, et al. · Algorithms (2025) | TGRS Research Map | TGRS