Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight m...

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Bibliographic Details
Main Authors: Ana eBengoetxea, Françoise eLeurs, Thomas eHoellinger, Ana Maria Cebolla, Bernard eDan, Joseph eMcIntyre, Guy eCheron
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-09-01
Series:Frontiers in Computational Neuroscience
Subjects:
Principal Component Analysis
rhythmic movements
upper-limb
muscular synergies
figure-eight
Dynamic recurrent neuronal network
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00100/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00100/full

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