A 16-Channel 60µW Neural Synchrony Processor for Multi-Mode Phase-Locked Neurostimulation

Uisub Shin, Cong Ding, Laxmeesha Somappa, V. Woods, A. Widge, Mahsa Shoaran
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引用次数: 6

Abstract

Measuring neural oscillatory synchrony facilitates our understanding of complex brain networks and the underlying pathological states. Altering the cross-regional synchrony-as a measure of brain network connectivity-via phase-locked deep brain stimulation (DBS) could provide a new therapeutic solution for various neurological [1] and psychiatric disorders [2]. This feature is missing in current neuromodulation devices and requires an accurate, energy-efficient computation of oscillatory phase and cross-regional synchrony on chip. The conventional iterative vector processing approach via CORDIC [3] can accurately extract the instantaneous phase and phase locking value (PLV) at the cost of high power consumption (400µW). As a result, it cannot be applied to large-scale (>100-CH) neuronal networks. Moreover, the latency in the pipelined CORDIC processor may hinder timely phase-locked stimulation in the absence of an excessively high clock speed. Alternatively, the PLV extractors in [4], [5] utilized simple approximation algorithms such as 1-bit quantization and local minima detection. These methods, albeit efficient, compromise PLV accuracy and cannot extract the instantaneous phase of neuronal signals. To provide an efficient, flexible, and accurate phase-locked DBS platform, this paper integrates a 16-channel low-noise AFE, an energy-efficient multi-mode phase synchrony processor, and a 4-channel neurostimulator that is locked to specific neuronal oscillatory phases (i.e., fixed or random phase, PLV or PAC). An amplitude-locked control can be further enabled through envelope and multi-band spectral energy extraction for common use cases such as epilepsy.
一种用于多模式锁相神经刺激的16通道60µW神经同步处理器
测量神经振荡同步有助于我们理解复杂的大脑网络和潜在的病理状态。通过锁相脑深部刺激(DBS)改变跨区域同步(作为脑网络连接的一种测量方法)可能为各种神经系统[1]和精神疾病[2]提供新的治疗方案。目前的神经调节设备缺少这一特性,需要在芯片上精确、节能地计算振荡相位和跨区域同步。传统的基于CORDIC[3]的迭代矢量处理方法可以准确地提取瞬时相位和锁相值(PLV),但功耗高(400µW)。因此,它不能应用于大规模(> - 100-CH)神经元网络。此外,在没有过高时钟速度的情况下,流水线CORDIC处理器中的延迟可能会妨碍及时的锁相刺激。另外,[4]和[5]中的PLV提取器使用简单的近似算法,如1位量化和局部最小检测。这些方法虽然有效,但会损害PLV的精度,并且无法提取神经元信号的瞬时相位。为了提供一个高效、灵活、准确的锁相DBS平台,本文集成了一个16通道低噪声AFE,一个节能的多模式相位同步处理器,以及一个锁定特定神经元振荡相位(即固定或随机相位,PLV或PAC)的4通道神经刺激器。通过包络和多频带频谱能量提取,可以进一步实现锁幅控制,用于癫痫等常见用例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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