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Micro-channel sieve electrode for concurrent bidirectional peripheral nerve interface. Part A: recording.

Robert A Coker1, Erik R Zellmer1, Daniel W Moran1

  • 1Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, United States of America.

Journal of Neural Engineering
|December 8, 2018
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Summary
This summary is machine-generated.

Micro-channel sieve electrodes offer superior signal quality for prosthetic control compared to tfTIME electrodes. These findings suggest micro-channel sieves are optimal for bidirectional peripheral neural interfaces.

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Area of Science:

  • Biomedical Engineering
  • Neuroprosthetics
  • Computational Neuroscience

Background:

  • Advancements in prosthetic limb technology necessitate improved neural interfaces for natural control and sensory feedback.
  • Existing peripheral neural interfaces (PNIs), like the thin-film transverse intrafascicular multichannel electrode (tfTIME), face challenges with stimulation artifact, limiting bidirectional communication.
  • Micro-channel sieve electrodes present a potential alternative offering stability and reduced susceptibility to noise.

Purpose of the Study:

  • To computationally compare the recording capabilities of simulated electro neural graphs (ENGs) from tfTIME and micro-channel sieve PNIs.
  • To evaluate the quality of control signals derived from ENGs recorded by each PNI type under varying neural drive levels.
  • To determine the suitability of micro-channel sieve electrodes as a bidirectional PNI.

Main Methods:

  • A computational model was developed using a motor neuron pool to simulate axon firing rates.
  • Core conductor axon models determined extracellular currents, and finite element models calculated contributions to recorded potentials.
  • Simulated ENGs were generated by combining contributions from individual axonal nodes of Ranvier for both tfTIME and micro-channel sieve interfaces.

Main Results:

  • Micro-channel sieve electrodes yielded ENGs with significantly higher amplitudes than tfTIME electrodes.
  • Signals recorded by micro-channel sieves exhibited less variation with axonal placement and spike timing, indicating greater consistency.
  • Signal amplitude was predominantly determined by neural drive levels for micro-channel sieve recordings.

Conclusions:

  • Computational simulations indicate that micro-channel sieve PNIs provide superior control signal quality for decoding ENGs compared to tfTIME PNIs.
  • The enhanced signal quality and stability suggest micro-channel sieve electrodes are a promising candidate for bidirectional neural interfacing.
  • Combined with stimulation data, the micro-channel sieve emerges as an optimal PNI for advanced neuroprosthetic applications.