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一种用于在假肢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。

A VLSI field-programmable mixed-signal array to perform neural signal processing and neural modeling in a prosthetic system.

机构信息

Istituto Superiore di Sanità, Rome, Italy.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2012 Jul;20(4):455-67. doi: 10.1109/TNSRE.2012.2187933. Epub 2012 Apr 3.

Abstract

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.

摘要

已经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。该芯片原型的核心部分已经制造完成,用于植入式闭环假肢系统,旨在帮助学习离散运动反应的康复。所选的实验环境是眼跳反应的小脑经典条件反射。可编程系统基于开关电容模拟技术与低速数字计算的紧密混合;在此框架内提出了节能创新。该系统的实用性通过实时实现眼跳条件反射的运动经典条件反射模型来证明,同时进行相关的神经信号处理。成对的条件刺激和非条件刺激被反复呈现给麻醉大鼠,并同时从两个小脑前核记录。从多通道数据中实时检测到这些成对的刺激。这导致获得了一个定时良好的条件眼跳反应的触发,并且从相同的数据构造未配对的试验导致条件反应触发的消失,与清醒动物的自然小脑学习兼容。

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