Spatiotemporal Organization of Touch Information in Tactile Neuron Population Responses

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Manual touch interactions elicit widespread skin vibrations that excite spiking responses in tactile neurons distributed throughout the hand. The spatiotemporal structure of these population responses is not yet fully understood. Here, we evaluate how touch information is encoded in the spatiotemporal organization of simulated Pacinian corpuscle neuron (PC) population responses when driven by a vibrometry dataset of whole-hand skin motion during commonly performed gestures. We assess the amount of information preserved in these peripheral population responses at various spatiotemporal scales using several non-parametric classification methods. We find that retaining the spatial structure of the whole-hand population responses is important for encoding touch gestures while conserving the temporal structure becomes more consequential for gesture representation in the responses of PCs located in the palm. In addition, preserving spatial structure is more beneficial for capturing gestures involving single rather than multiple digits. This work contributes to further understanding the sense of touch by introducing novel measurement-driven computational methods for analyzing the population-level neural representations of natural touch gestures over multiple spatiotemporal scales.

Details

OriginalspracheEnglisch
Titel2023 IEEE World Haptics Conference, WHC 2023 - Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten183-189
Seitenumfang7
ISBN (elektronisch)979-8-3503-9993-6
PublikationsstatusVeröffentlicht - 2023
Peer-Review-StatusJa

Publikationsreihe

ReiheWorld Haptics Conference (WHC)

Konferenz

Titel10th IEEE World Haptics Conference
KurztitelWHC 2023
Veranstaltungsnummer10
Dauer10 - 13 Juli 2023
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtDelft University of Technology
StadtDelft
LandNiederlande

Schlagworte

Schlagwörter

  • Haptic neuroscience, Natural touch gestures, Neural spiking classification, Tactile information encoding