A model of temporal scaling correctly predicts that motor timing improves with speed

Humans can perform complex motor movements at varying speeds. Here, the authors show that a recurrent neural network can be trained to exhibit temporal scaling obeying Weber’s law as well as validate a prediction of the model of improved precision of movements at faster speeds.

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Nicholas F. Hardy, Vishwa Goudar, Juan L. Romero-Sosa, Dean V. Buonomano
Format: article
Langue:EN
Publié: Nature Portfolio 2018
Sujets:
Q
Accès en ligne:https://doaj.org/article/1735b53621ec48ce80e9bab83c18ff20
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!