Abstract
Background
This paper describes a series of experiments designed to verify a new method of electroneurogram (ENG) recording that enables the rate of neural firing within prescribed bands of propagation velocity to be determined in real time. Velocity selective recording (VSR) has been proposed as a solution to the problem of increasing the information available from an implantable neural interface (typically with electrodes in circumferential nerve cuffs) and has been successful in transforming compound action potentials into the velocity domain.
New method
The new method extends VSR to naturally-evoked (physiological) ENG in which the rate of neural firing at particular velocities is required in addition to a knowledge of the velocities present in the recording.
Results
The experiments, carried out in rats required individual spikes to be distinct and non-overlapping, which could be achieved by a microchannel or small-bore cuff. In these experiments, strands of rat nerve were laid on ten hook electrodes in oil to demonstrate the principle.
Comparison with existing method
The new method generates a detailed overview of the firing rates of neurons based on their conduction velocity and direction of propagation. In addition it allows real time working in contrast to existing spike sorting methods using statistical pattern processing techniques.
Conclusions
Results show that by isolating neural activity based purely on conduction velocity it was possible to determine the onset of direct cutaneous stimulation of the L5 dermatome.
This paper describes a series of experiments designed to verify a new method of electroneurogram (ENG) recording that enables the rate of neural firing within prescribed bands of propagation velocity to be determined in real time. Velocity selective recording (VSR) has been proposed as a solution to the problem of increasing the information available from an implantable neural interface (typically with electrodes in circumferential nerve cuffs) and has been successful in transforming compound action potentials into the velocity domain.
New method
The new method extends VSR to naturally-evoked (physiological) ENG in which the rate of neural firing at particular velocities is required in addition to a knowledge of the velocities present in the recording.
Results
The experiments, carried out in rats required individual spikes to be distinct and non-overlapping, which could be achieved by a microchannel or small-bore cuff. In these experiments, strands of rat nerve were laid on ten hook electrodes in oil to demonstrate the principle.
Comparison with existing method
The new method generates a detailed overview of the firing rates of neurons based on their conduction velocity and direction of propagation. In addition it allows real time working in contrast to existing spike sorting methods using statistical pattern processing techniques.
Conclusions
Results show that by isolating neural activity based purely on conduction velocity it was possible to determine the onset of direct cutaneous stimulation of the L5 dermatome.
Original language | English |
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Pages (from-to) | 47-55 |
Number of pages | 9 |
Journal | Journal of Neuroscience Methods |
Volume | 251 |
Early online date | 13 May 2015 |
DOIs | |
Publication status | Published - 15 Aug 2015 |
Keywords
- Velocity selective recording
- VSR
- spike sorting
- ENG
- Velocity spectral density
Fingerprint
Dive into the research topics of 'A new method for spike extraction using velocity selective recording demonstrated with physiological ENG in Rat'. Together they form a unique fingerprint.Profiles
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Benjamin Metcalfe, FRSA
- Department of Electronic & Electrical Engineering - Head of Department
- UKRI CDT in Accountable, Responsible and Transparent AI
- Centre for Bioengineering & Biomedical Technologies (CBio)
- Bath Institute for the Augmented Human
- IAAPS: Propulsion and Mobility
Person: Research & Teaching, Core staff, Affiliate staff
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John Taylor
- Department of Electronic & Electrical Engineering - Professor
- Electronics Materials, Circuits & Systems Research Unit (EMaCS)
Person: Research & Teaching
Datasets
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Multi-channel Recordings from L2 Dorsal Root of Rat
Metcalfe, B. (Creator), Taylor, J. (Researcher) & Chew, D. (Data Collector), University of Bath, 2016
DOI: 10.15125/BATH-00249
Dataset