Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637.
Active Touch Laboratory, Department of Psychology, University of Sheffield, Sheffield S1 2LT, United Kingdom.
Proc Natl Acad Sci U S A. 2017 Jul 11;114(28):E5693-E5702. doi: 10.1073/pnas.1704856114. Epub 2017 Jun 26.
When we grasp and manipulate an object, populations of tactile nerve fibers become activated and convey information about the shape, size, and texture of the object and its motion across the skin. The response properties of tactile fibers have been extensively characterized in single-unit recordings, yielding important insights into how individual fibers encode tactile information. A recurring finding in this extensive body of work is that stimulus information is distributed over many fibers. However, our understanding of population-level representations remains primitive. To fill this gap, we have developed a model to simulate the responses of all tactile fibers innervating the glabrous skin of the hand to any spatiotemporal stimulus applied to the skin. The model first reconstructs the stresses experienced by mechanoreceptors when the skin is deformed and then simulates the spiking response that would be produced in the nerve fiber innervating that receptor. By simulating skin deformations across the palmar surface of the hand and tiling it with receptors at their known densities, we reconstruct the responses of entire populations of nerve fibers. We show that the simulated responses closely match their measured counterparts, down to the precise timing of the evoked spikes, across a wide variety of experimental conditions sampled from the literature. We then conduct three virtual experiments to illustrate how the simulation can provide powerful insights into population coding in touch. Finally, we discuss how the model provides a means to establish naturalistic artificial touch in bionic hands.
当我们抓握和操纵物体时，大量的触觉神经纤维被激活，并传递有关物体的形状、大小、质地以及其在皮肤上运动的信息。在单细胞记录中，对触觉纤维的反应特性进行了广泛的描述，这为我们理解单个纤维如何编码触觉信息提供了重要的线索。在这一广泛的研究中，一个反复出现的发现是，刺激信息分布在许多纤维上。然而，我们对群体水平表示的理解仍然很原始。为了填补这一空白，我们开发了一个模型来模拟所有支配手部光滑皮肤的触觉纤维对施加在皮肤上的任何时空刺激的反应。该模型首先重建皮肤变形时感受器所经历的应力，然后模拟将在支配该感受器的神经纤维中产生的尖峰反应。通过模拟整个手掌表面的皮肤变形，并以其已知密度的感受器进行平铺，我们重建了整个神经纤维群体的反应。我们表明，模拟的反应与从文献中采样的各种实验条件下的实测反应非常吻合，甚至包括诱发尖峰的精确时间。然后，我们进行了三个虚拟实验来说明模拟如何为触摸中的群体编码提供有力的见解。最后，我们讨论了该模型如何为仿生手中的自然人工触摸提供一种手段。
