Literature DB >> 21741541

Naturalistic approaches to sensorimotor control.

James N Ingram1, Daniel M Wolpert.   

Abstract

Human sensorimotor control has been predominantly studied using fixed tasks performed under laboratory conditions. This approach has greatly advanced our understanding of the mechanisms that integrate sensory information and generate motor commands during voluntary movement. However, experimental tasks necessarily restrict the range of behaviors that are studied. Moreover, the processes studied in the laboratory may not be the same processes that subjects call upon during their everyday lives. Naturalistic approaches thus provide an important adjunct to traditional laboratory-based studies. For example, wearable self-contained tracking systems can allow subjects to be monitored outside the laboratory, where they engage spontaneously in natural everyday behavior. Similarly, advances in virtual reality technology allow laboratory-based tasks to be made more naturalistic. Here, we review naturalistic approaches, including perspectives from psychology and visual neuroscience, as well as studies and technological advances in the field of sensorimotor control.
Copyright © 2011 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21741541     DOI: 10.1016/B978-0-444-53752-2.00016-3

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  10 in total

Review 1.  Computations in Sensorimotor Learning.

Authors:  Daniel M Wolpert
Journal:  Cold Spring Harb Symp Quant Biol       Date:  2015-04-07

2.  Testing the concurrent validity of a naturalistic upper extremity reaching task.

Authors:  S Y Schaefer; C R Hengge
Journal:  Exp Brain Res       Date:  2015-10-05       Impact factor: 1.972

3.  Computer Vision to Automatically Assess Infant Neuromotor Risk.

Authors:  Claire Chambers; Nidhi Seethapathi; Rachit Saluja; Helen Loeb; Samuel R Pierce; Daniel K Bogen; Laura Prosser; Michelle J Johnson; Konrad P Kording
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2020-11-06       Impact factor: 3.802

4.  A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Authors:  James N Ingram; Ian S Howard; J Randall Flanagan; Daniel M Wolpert
Journal:  PLoS Comput Biol       Date:  2011-09-29       Impact factor: 4.475

5.  The value of the follow-through derives from motor learning depending on future actions.

Authors:  Ian S Howard; Daniel M Wolpert; David W Franklin
Journal:  Curr Biol       Date:  2015-01-08       Impact factor: 10.834

6.  Multiple motor memories are learned to control different points on a tool.

Authors:  James B Heald; James N Ingram; J Randall Flanagan; Daniel M Wolpert
Journal:  Nat Hum Behav       Date:  2018-04-09

7.  Pose estimates from online videos show that side-by-side walkers synchronize movement under naturalistic conditions.

Authors:  Claire Chambers; Gaiqing Kong; Kunlin Wei; Konrad Kording
Journal:  PLoS One       Date:  2019-06-06       Impact factor: 3.240

8.  Acute Aerobic Exercise-Induced Motor Priming Improves Piano Performance and Alters Motor Cortex Activation.

Authors:  Terence Moriarty; Andrea Johnson; Molly Thomas; Colin Evers; Abi Auten; Kristina Cavey; Katie Dorman; Kelsey Bourbeau
Journal:  Front Psychol       Date:  2022-03-18

9.  Structural changes in hand related cortical areas after median nerve injury and repair.

Authors:  Per F Nordmark; Christina Ljungberg; Roland S Johansson
Journal:  Sci Rep       Date:  2018-03-14       Impact factor: 4.379

10.  The measurement, evolution, and neural representation of action grammars of human behavior.

Authors:  Dietrich Stout; Thierry Chaminade; Jan Apel; Ali Shafti; A Aldo Faisal
Journal:  Sci Rep       Date:  2021-07-02       Impact factor: 4.379

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.