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Medical & Biological Engineering & Computing

, Volume 50, Issue 3, pp 309–318 | Cite as

The theory of velocity selective neural recording: a study based on simulation

  • John TaylorEmail author
  • Martin Schuettler
  • Chris Clarke
  • Nick Donaldson
Original Article

Abstract

This paper describes the improvements to the theory of velocity selective recording and some simulation results. In this method, activity in different groups of axons is discriminated by their propagation velocity. A multi-electrode cuff and an array of amplifiers produce multiple neural signals; if artificial delays are inserted and the signals are added, the activity in axons of the matched velocity are emphasized. We call this intrinsic velocity selective recording. However, simulation shows that interpreting the time signals is then not straight-forward and the selectivity Q v is low. New theory shows that bandpass filters improve the selectivity and explains why this is true in the time domain. A simulation study investigates the limits on the available velocity selectivity both with and without additive noise and with reasonable sampling rates and analogue-to-digital conversion parameters. Bandpass filters can improve the selectivity by factors up to 7 but this depends on the speed of the action potential and the signal-to-noise ratio.

Keywords

Electroneurogram recording Simulation Multi-electrode cuffs Velocity selective recording 

Abbreviations

BPF

Bandpass filter

FFT

Fast Fourier transform

ADC

Analogue to digital converter

SNR

Signal to noise ratio

VSR

Velocity selective recording

SFAP

Single fibre action potential

TMAP

Trans-membrane action potential

CAP

Compound action potential

MEC

Multi-electrode cuff

IVS

Intrinsic velocity selectivity

BPFVS

Bandpass filtered velocity selectivity

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Copyright information

© International Federation for Medical and Biological Engineering 2012

Authors and Affiliations

  • John Taylor
    • 1
    Email author
  • Martin Schuettler
    • 2
  • Chris Clarke
    • 1
  • Nick Donaldson
    • 3
  1. 1.Department of Electronic and Electrical EngineeringUniversity of BathBathUK
  2. 2.Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, IMTEKUniversity of FreiburgFreiburgGermany
  3. 3.Department of Medical Physics and BioengineeringUniversity College LondonLondonUK

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