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手指的肌腱网络在宏观尺度上执行解剖学计算。

The tendon network of the fingers performs anatomical computation at a macroscopic scale.

作者信息

Valero-Cuevas Francisco J, Yi Jae-Woong, Brown Daniel, McNamara Robert V, Paul Chandana, Lipson Hood

机构信息

Neuromuscular Biomechanics Laboratory, Cornell University, 220 Upson Hall, Ithaca, NY 14853, USA.

出版信息

IEEE Trans Biomed Eng. 2007 Jun;54(6 Pt 2):1161-6. doi: 10.1109/TBME.2006.889200.

Abstract

Current thinking attributes information processing for neuromuscular control exclusively to the nervous system. Our cadaveric experiments and computer simulations show, however, that the tendon network of the fingers performs logic computation to preferentially change torque production capabilities. How this tendon network propagates tension to enable manipulation has been debated since the time of Vesalius and DaVinci and remains an unanswered question. We systematically changed the proportion of tension to the tendons of the extensor digitorum versus the two dorsal interosseous muscles of two cadaver fingers and measured the tension delivered to the proximal and distal interphalangeal joints. We find that the distribution of input tensions in the tendon network itself regulates how tensions propagate to the finger joints, acting like the switching function of a logic gate that nonlinearly enables different torque production capabilities. Computer modeling reveals that the deformable structure of the tendon networks is responsible for this phenomenon; and that this switching behavior is an effective evolutionary solution permitting a rich repertoire of finger joint actuation not possible with simpler tendon paths. We conclude that the structural complexity of this tendon network, traditionally oversimplified or ignored, may in fact be critical to understanding brain-body coevolution and neuromuscular control. Moreover, this form of information processing at the macroscopic scale is a new instance of the emerging principle of nonneural "somatic logic" found to perform logic computation such as in cellular networks.

摘要

当前的观点认为,神经肌肉控制中的信息处理完全由神经系统负责。然而,我们的尸体实验和计算机模拟表明,手指的肌腱网络会进行逻辑计算,以优先改变扭矩产生能力。自维萨里和达·芬奇时代以来,关于这种肌腱网络如何传递张力以实现操作的问题一直存在争议,至今仍未得到解答。我们系统地改变了示指伸肌腱与两个尸体手指的两块背侧骨间肌之间的张力比例,并测量了传递到近端和远端指间关节的张力。我们发现,肌腱网络本身的输入张力分布调节着张力向手指关节的传播方式,其作用类似于逻辑门的开关功能,非线性地实现不同的扭矩产生能力。计算机建模显示,肌腱网络的可变形结构是造成这一现象的原因;并且这种开关行为是一种有效的进化解决方案,使得手指关节能够实现丰富多样的驱动方式,而简单的肌腱路径则无法做到。我们得出结论,这种传统上被过度简化或忽视的肌腱网络的结构复杂性,实际上可能对于理解脑-体协同进化和神经肌肉控制至关重要。此外,这种宏观尺度上的信息处理形式是新兴的非神经“躯体逻辑”原则的一个新实例,该原则已被发现可在细胞网络等中执行逻辑计算。

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