Laboratory for Intelligent Systems and Informatics, Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan
Proc Natl Acad Sci U S A. 2020 Jun 2;117(22):12486-12496. doi: 10.1073/pnas.1819707117. Epub 2020 May 19.
Most biological neurons exhibit stochastic and spiking action potentials. However, the benefits of stochastic spikes versus continuous signals other than noise tolerance and energy efficiency remain largely unknown. In this study, we provide an insight into the potential roles of stochastic spikes, which may be beneficial for producing on-site adaptability in biological sensorimotor agents. We developed a platform that enables parametric modulation of the stochastic and discontinuous output of a stochastically spiking neural network (sSNN) to the rate-coded smooth output. This platform was applied to a complex musculoskeletal-neural system of a bipedal walker, and we demonstrated how stochastic spikes may help improve on-site adaptability of a bipedal walker to slippery surfaces or perturbation of random external forces. We further applied our sSNN platform to more general and simple sensorimotor agents and demonstrated four basic functions provided by an sSNN: 1) synchronization to a natural frequency, 2) amplification of the resonant motion in a natural frequency, 3) basin enlargement of the behavioral goal state, and 4) rapid complexity reduction and regular motion pattern formation. We propose that the benefits of sSNNs are not limited to musculoskeletal dynamics. Indeed, a wide range of the stability and adaptability of biological systems may arise from stochastic spiking dynamics.
大多数生物神经元表现出随机和爆发式动作电位。然而,除了噪声容忍度和能量效率之外,随机尖峰相对于连续信号的优势在很大程度上仍然未知。在这项研究中,我们深入了解了随机尖峰的潜在作用,这可能有利于生物感觉运动代理产生现场适应性。我们开发了一个平台,能够对随机尖峰神经网络(sSNN)的随机和不连续输出进行参数调制,以产生速率编码的平滑输出。该平台应用于双足步行者的复杂肌肉骨骼-神经系统,我们展示了随机尖峰如何帮助提高双足步行者对滑面或随机外力干扰的现场适应性。我们进一步将我们的 sSNN 平台应用于更一般和简单的感觉运动代理,并展示了 sSNN 提供的四个基本功能:1)与自然频率同步,2)放大自然频率中的共振运动,3)行为目标状态的盆地扩大,以及 4)快速复杂性降低和规则运动模式形成。我们提出,sSNN 的优势不仅限于肌肉骨骼动力学。实际上,生物系统的稳定性和适应性的广泛范围可能源于随机尖峰动力学。