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Neural Computing and Applications
Published in: Neural Computing and Applications 10/2019

29-03-2018 | Original Article

A spike train distance-based method to evaluate the response of mechanoreceptive afferents

Published in: Neural Computing and Applications | Issue 10/2019

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Abstract

Spike train distances have gained increasing attention in the neuroscience community and provided an important tool to quantify the similarity between spike trains. A number of comparisons of the spike train distances have been carried out and mainly focused on the discriminative or clustering ability of the spike train distance. This paper proposes a spike train distance-based method to compare repeatability and linearity of mechanoreceptive afferents. The compared spike train distances include both parameter-dependent and parameter-free distances. We examined these two features on the response of mechanoreceptive afferents under the sinusoidal stimuli. We demonstrated that the parameter-dependent spike train distances (i.e., the Victor–Purpura distance and the van Rossum distance) consistently outperform the parameter-free ones (i.e., the ISI distance, the SPIKE distance, and the Event-Synchronization distance) in terms of repeatability and linearity of mechanoreceptive afferents.
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Footnotes
1
The recorded data are available upon request.
 
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Metadata
Title
A spike train distance-based method to evaluate the response of mechanoreceptive afferents
Publication date
29-03-2018
Published in
Neural Computing and Applications / Issue 10/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3465-6

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