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Neural Computing and Applications

, Volume 31, Issue 10, pp 6319–6330 | Cite as

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

  • Zhengkun Yi
  • Yilei ZhangEmail author
Original Article
  • 104 Downloads

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.

Keywords

Spike train distance Spike train feature Repeatability and linearity Response of mechanoreceptive afferents 

Notes

Acknowledgements

The authors would like to thank Dr. Sliman J. Bensmaia from University of Chicago for providing the observed spike trains from the glabrous skin of macaque monkeys. This project is supported by the Joint Ph.D. Degree Programme NTU–TU Darmstadt. The project is also supported by Fraunhofer Singapore, which is funded by the National Research Foundation (NRF) and managed through the multi-agency Interactive & Digital Media Programme Office (IDMPO) hosted by the Infocomm Media Development Authority of Singapore (IMDA). YL Zhang acknowledges the financial support of this research by the A*STAR AOP Project (1223600005) and the A*STAR Industrial Robotics Programme (1225100007).

Compliance with ethical standards

Conflict of interest

The authors declared that they have no conflict of interest to this work.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.School of Mechanical and Aerospace EngineeringNanyang Technological UniversitySingaporeSingapore

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