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A VLSI Field-Programmable Mixed-Signal Array to Perform Neural Signal Processing and Neural Modeling in a Prosthetic System

机译:在修复系统中执行神经信号处理和神经建模的VLSI现场可编程混合信号阵列

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A very-large-scale integration field-programmable mixed-signal array specialized for neural signal processing and neural modeling has been designed. This has been fabricated as a core on a chip prototype intended for use in an implantable closed-loop prosthetic system aimed at rehabilitation of the learning of a discrete motor response. The chosen experimental context is cerebellar classical conditioning of the eye-blink response. The programmable system is based on the intimate mixing of switched capacitor analog techniques with low speed digital computation; power saving innovations within this framework are presented. The utility of the system is demonstrated by the implementation of a motor classical conditioning model applied to eye-blink conditioning in real time with associated neural signal processing. Paired conditioned and unconditioned stimuli were repeatedly presented to an anesthetized rat and recordings were taken simultaneously from two precerebellar nuclei. These paired stimuli were detected in real time from this multichannel data. This resulted in the acquisition of a trigger for a well-timed conditioned eye-blink response, and repetition of unpaired trials constructed from the same data led to the extinction of the conditioned response trigger, compatible with natural cerebellar learning in awake animals.
机译:设计了一种专门用于神经信号处理和神经建模的超大规模集成现场可编程混合信号阵列。它已被制成芯片原型的核心,旨在用于可植入闭环假体系统,旨在恢复离散运动响应的学习。选择的实验环境是眨眼反应的小脑经典条件。可编程系统基于开关电容器模拟技术与低速数字计算的紧密结合。介绍了在此框架内的节能创新。该系统的实用性通过电机经典调节模型的实施以及相关的神经信号处理实时应用于眨眼调节来证明。配对的条件刺激和非条件刺激重复地施加给麻醉的大鼠,并同时从两个小脑前核中获取记录。从该多通道数据中实时检测到这些配对的刺激。这导致获得了适当的条件性眨眼反应触发信号,并且重复使用相同数据构建的未配对试验导致条件性反应触发信号消失,这与清醒动物的自然小脑学习相适应。

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