Motor adaptation distorts visual space.

Adaptation Cross-modal perception Motor adaptation Space perception

Journal

Vision research
ISSN: 1878-5646
Titre abrégé: Vision Res
Pays: England
ID NLM: 0417402

Informations de publication

Date de publication:
01 May 2020
Historique:
received: 21 01 2020
revised: 17 04 2020
accepted: 21 04 2020
pubmed: 7 5 2020
medline: 7 5 2020
entrez: 7 5 2020
Statut: aheadofprint

Résumé

It has been suggested that the human visual system exploits an adaptable metric to implement a precise but plastic spatial representation. Indeed, adapting to a dense dot-texture reduces the apparent separation of subsequently presented dots pairs. Whether this metric is purely visual or shared between senses is still unknown. Here we present a new cross-modal after-effect revealing that the metric with which the visual system computes the relative spatial position of objects is shared with the motor system. A few seconds of mid-air self-produced tapping movements (adaptation) yielded a robust compression of the apparent separation of dot pairs subsequently displayed around the tapping region. This visuo-motor spatial metric could reflect an efficient functional architecture to program and execute actions aimed at efficient interaction with the objects in the environment.

Identifiants

pubmed: 32371224
pii: S0042-6989(20)30067-5
doi: 10.1016/j.visres.2020.04.007
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

31-35

Informations de copyright

Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Auteurs

Irene Petrizzo (I)

Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy.

Giovanni Anobile (G)

Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy. Electronic address: giovannianobile@hotmail.it.

Roberto Arrighi (R)

Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy.

Classifications MeSH