Department of Electric Engineering and Information Technologies (DIETI) Università di Napoli Federico II, Naples, Italy.
Institute of Cognitive Sciences and Technologies, National Research Council (ISTC-CNR), Via S. Martino della Battaglia, 44, 00185, Rome, Italy.
Sci Rep. 2018 Jan 12;8(1):616. doi: 10.1038/s41598-017-18776-y.
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.
越来越多的证据表明,手部动作是在协同作用的层面上进行控制的,而不是单个肌肉。基于协同作用的动作表示的一个有趣方面是,它可能本质上是稀疏的,并且相同的协同作用可以在几种不同类型的手部动作中共享。在这里,我们从规范的角度考虑了三种手动作最优控制的假设:稀疏组合假设 (SC) - 协同作用与动作之间的映射中的稀疏性 - 即使用协同作用的稀疏组合来实现动作;稀疏元素假设 (SE) - 协同作用表示中的稀疏性 - 即自由度 (DoF) 和协同作用之间的映射是稀疏的;双重稀疏性假设 (DS) - 结合了 SC 和 SE 的新颖观点 - 即自由度和协同作用之间以及协同作用和动作之间的映射都是稀疏的,每个动作都使用协同作用的稀疏组合(如 SC 中),每个动作都使用有限数量的自由度(如 SE 中)。我们使用来自六个人类受试者执行九种不同类型的伸手抓握动作的手部运动学数据来评估这些假设。我们的结果支持 DS,表明最佳的动作表示基于相对较大的协同作用集,每个协同作用集涉及较少的自由度,并且不同的协同作用集可能涉及不同的任务。