Evidence for sparse synergies in grasping actions

被引:0
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作者
Roberto Prevete
Francesco Donnarumma
Andrea d’Avella
Giovanni Pezzulo
机构
[1] Department of Electric Engineering and Information Technologies (DIETI) Università di Napoli Federico II,Institute of Cognitive Sciences and Technologies
[2] National Research Council (ISTC-CNR),Department of Biomedical and Dental Sciences and Morphofunctional Imaging
[3] University of Messina,undefined
[4] Laboratory of Neuromotor Physiology,undefined
[5] Santa Lucia Foundation,undefined
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Scientific Reports | / 8卷
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摘要
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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