A finite-element model of mechanosensation by a Pacinian corpuscle cluster in human skin

Julia C. Quindlen-Hotek, Victor H. Barocas

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The Pacinian corpuscle (PC) is the cutaneous mechanoreceptor responsible for sensation of high-frequency (20–1000 Hz) vibrations. PCs lie deep within the skin, often in multicorpuscle clusters with overlapping receptive fields. We developed a finite-element mechanical model of one or two PCs embedded within human skin, coupled to a multiphysics PC model to simulate action potentials elicited by each PC. A vibration was applied to the skin surface, and the resulting mechanical signal was analyzed using two metrics: the deformation amplitude ratio (ρ1 S, ρ2 S) and the phase shift of the vibration (δS1mech, δS2mech) between the stimulus and the PC. Our results showed that the amplitude attenuation and phase shift at a PC increased with distance from the stimulus to the PC. Differences in amplitude (ρ12) and phase shift (δ12mech) between the two PCs in simulated clusters directly affected the interspike interval between the action potentials elicited by each PC (δ12spike). While δ12mech had a linear relationship with δ12spike, ρ12’s effect on δ12spike was greater for lower values of ρ12. In our simulations, the separation between PCs and the distance of each PC from the stimulus location resulted in differences in amplitude and phase shift at each PC that caused δ12spike to vary with PC location. Our results suggest that PCs within a cluster receive different mechanical stimuli which may enhance source localization of vibrotactile stimuli, drawing parallels to sound localization in binaural hearing.

Original languageEnglish (US)
Pages (from-to)1053-1067
Number of pages15
JournalBiomechanics and Modeling in Mechanobiology
Volume17
Issue number4
DOIs
StatePublished - Aug 1 2018

Bibliographical note

Funding Information:
Acknowledgements This research was supported by the University of Minnesota Doctoral Dissertation Fellowship. The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper (URL: http://www.msi.umn.edu).

Funding Information:
This research was supported by the University of Minnesota Doctoral Dissertation Fellowship. The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper (URL: http://www.msi.umn.edu). The authors declare they have no conflict of interest.

Publisher Copyright:
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Biomechanics
  • Haptics
  • Neuroscience
  • Touch

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