Evidence for sparse synergies in grasping actions
Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, a...
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Published in | Scientific reports Vol. 8; no. 1; pp. 616 - 16 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
12.01.2018
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Summary: | Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control:
sparse-combination hypothesis (SC)
– sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies;
sparse-elements hypothesis (SE)
– sparsity in synergy representation – i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse;
double-sparsity hypothesis (DS)
– a novel view combining both SC and SE – i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-017-18776-y |