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Author Etamagnone, Irene ♦ Esumma, Susanna ♦ Ecasadio, Maura ♦ Esanguineti, Vittorio
Source Directory of Open Access Journals (DOAJ)
Content type Text
Publisher Frontiers Media S.A.
File Format HTM / HTML
Date Created 2014-05-22
Copyright Year ©2013
Language English
Subject Domain (in LCC) RC321-571
Subject Keyword Motor skill learning ♦ Neuropsychiatry ♦ Robot ♦ Biological psychiatry ♦ Neurosciences ♦ Cortical reorganization ♦ Internal medicine ♦ Medicine ♦ Compensation ♦ Functional recovery ♦ Muscle Synergy
Abstract Computational models of neuromotor recovery after a stroke might help to unveil the underlying physiological mechanisms and might suggest how to make recovery faster and more effective. At least in principle, these models could serve: (i) To provide testable hypotheses on the nature of recovery; (ii) To predict the recovery of individual patients; (iii) To design patient-specific ’optimal’ therapy, by setting the treatment variables for maximizing the amount of recovery or for achieving a better generalization of the learned abilities across different tasks.Here we review the state of the art of computational models for neuromotor recovery through exercise, and their implications for treatment. We show that to properly account for the computational mechanisms of neuromotor recovery, multiple levels of description need to be taken into account. The review specifically covers models of recovery at central, functional and muscle synergy level.
ISSN 16625188
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2013-08-01
e-ISSN 16625188
Journal Frontiers in Computational Neuroscience
Volume Number 7


Source: Directory of Open Access Journals (DOAJ)