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首页> 美国卫生研究院文献>Frontiers in Computational Neuroscience >Emulated muscle spindle and spiking afferents validates VLSI neuromorphic hardware as a testbed for sensorimotor function and disease
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Emulated muscle spindle and spiking afferents validates VLSI neuromorphic hardware as a testbed for sensorimotor function and disease

机译：模拟的肌肉纺锤体和刺突传入验证了VLSI神经形态硬件是否可作为感觉运动功能和疾病的试验台

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The lack of multi-scale empirical measurements (e.g., recording simultaneously from neurons, muscles, whole body, etc.) complicates understanding of sensorimotor function in humans. This is particularly true for the understanding of development during childhood, which requires evaluation of measurements over many years. We have developed a synthetic platform for emulating multi-scale activity of the vertebrate sensorimotor system. Our design benefits from Very Large Scale Integrated-circuit (VLSI) technology to provide considerable scalability and high-speed, as much as 365× faster than real-time. An essential component of our design is the proprioceptive sensor, or muscle spindle. Here we demonstrate an accurate and extremely fast emulation of a muscle spindle and its spiking afferents, which are computationally expensive but fundamental for reflex functions. We implemented a well-known rate-based model of the spindle (Mileusnic et al., ) and a simplified spiking sensory neuron model using the Izhikevich approximation to the Hodgkin–Huxley model. The resulting behavior of our afferent sensory system is qualitatively compatible with classic cat soleus recording (Crowe and Matthews, ; Matthews, , ). Our results suggest that this simplified structure of the spindle and afferent neuron is sufficient to produce physiologically-realistic behavior. The VLSI technology allows us to accelerate this behavior beyond 365× real-time. Our goal is to use this testbed for predicting years of disease progression with only a few days of emulation. This is the first hardware emulation of the spindle afferent system, and it may have application not only for emulation of human health and disease, but also for the construction of compliant neuromorphic robotic systems.
机译：缺乏多尺度的经验测量（例如，同时从神经元，肌肉，全身等进行记录）使对人感觉运动功能的理解变得复杂。对于了解儿童时期的发展尤其如此，因为这需要评估多年的测量结果。我们已经开发了一个合成平台，用于模拟脊椎动物感觉运动系统的多尺度活动。我们的设计受益于超大规模集成电路（VLSI）技术，可提供可观的可扩展性和高速性，比实时速度快365倍。我们设计的重要组成部分是本体感受传感器或肌肉纺锤体。在这里，我们演示了肌肉纺锤体及其刺突传入的精确且极其快速的仿真，这在计算上是昂贵的，但对于反射功能而言却至关重要。我们实现了一个著名的基于心率的纺锤体模型（Mileusnic等人），并使用了与霍奇金-赫克斯利模型相似的Izhikevich简化的尖峰感觉神经元模型。我们传入的感觉系统所产生的行为在质量上与经典的猫比目鱼唱片兼容（Crowe和Matthews，； Matthews ，，）。我们的结果表明，纺锤体和传入神经元的这种简化结构足以产生生理上真实的行为。 VLSI技术使我们能够将这种行为加速到超过365倍的实时性。我们的目标是仅使用几天的时间，就可以使用该试验台来预测疾病的发展年份。这是主轴传入系统的第一个硬件仿真，它不仅可以用于仿真人类健康和疾病，而且可以用于构建顺应性神经形态机器人系统。

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