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A wireless closed-loop sleep modulation system-on-chip

A wireless closed-loop sleep modulation system-on-chip
无线闭环睡眠调制片上系统
批准号:
10733872
负责人:
Xilin Liu
金额:
$46.24万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-01 至 2027-05-31

项目摘要

项目成果

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中文摘要
翻译
项目摘要 睡眠在一系列生理和病理生理过程中起着至关重要的作用, 脑功能、免疫和代谢功能以及神经退行性疾病。更好地了解 睡眠机制对开发新的治疗策略很重要。睡眠回路可以被操纵 用许多技术来推断与生理和行为的因果关系。成效 操作通常依赖于睡眠阶段或大脑状态。因此,闭环询问提供了 强大的范例,从而时间上精确的操纵(光遗传学,电,或感官刺激) 是以大脑状态依赖的方式传递的。这种模式已成功地用于小鼠和人类 系于数据采集、状态分类和刺激硬件。然而,系留可能会不利地 影响自然睡眠行为,并阻止在较大的动物模型中使用。在这里,我们建议全面发展一个 集成的无线睡眠调制片上系统(SoC),能够提供状态相关的, 时间上精确的光、电和听觉刺激。在目标1和2中,共同主要研究者Liu博士将反复 开发用于多导睡眠图(PSG)信号采集和多模态闭环的超低功耗SoC 刺激.最终的SoC将有五个模块:(1)低噪声,高精度PSG采集模块,(2) 可编程混合信号数据压缩模块,以提高能效;(3)低功耗超宽带 无线发射器,(4)基于机器学习的睡眠阶段分类模块,以及(5)完全睡眠阶段分类模块。 可编程多模态刺激器。该系统的完全集成将导致小(2立方厘米),轻(2克) 电池供电的设备,一次充电可连续工作10小时以上。在目标3中, 在实现前两个目标的同时,共同研究者Richardson博士将通过睡眠研究验证SoC的性能 在小型(大鼠)和大型(猕猴)动物模型中。来自无线SoC的交叉记录和 系留商业系统将评估压缩PSG采集的保真度以及系留对 睡眠结构实时2阶段和所有阶段分类器将与离线地面真实标签进行比较。 最后,将使用同相闭环听觉刺激来增强慢波活动。我们的团队是 由于我们在开发关键模块方面拥有丰富的经验, 提出的SoC和使用无线电子设备进行动物自由行为电生理实验 模型一旦开发完成,两个行业合作伙伴,CMC微系统公司和开放的Ephys公司,将促进 将SoC分发给全球社区。闭环SoC将实现前所未有的假设- 对睡眠阶段特定神经回路的研究和对从小鼠到 猴子,从而加速对睡眠的机械理解和睡眠障碍的治疗。
英文摘要
PROJECT SUMMARY Sleep plays a critical role in a vast array of physiological and pathophysiological processes, including executive brain functions, immune and metabolic functions, and neurodegenerative diseases. An improved understanding of sleep mechanisms is important to developing new treatment strategies. Sleep circuits can be manipulated with numerous techniques to infer causal relationships to physiology and behavior. Effects of these manipulations are generally sleep stage or brain state dependent. Thus, closed-loop interrogation provides a powerful paradigm, whereby a temporally precise manipulation (optogenetic, electrical, or sensory stimulation) is delivered in a brain-state dependent manner. This paradigm has been used successfully in mice and humans tethered to data acquisition, state classification, and stimulation hardware. However, tethering can adversely affect natural sleep behavior and prevents use in larger animal models. Here, we propose to develop a fully integrated, wireless, sleep modulation system-on-chip (SoC) with the capability to deliver state-dependent, temporally-precise optical, electrical, and auditory stimulation. In Aims 1 and 2, Co-PI Dr. Liu will iteratively develop an ultra-low-power SoC for polysomnography (PSG) signal acquisition and multi-modal closed-loop stimulation. The final SoC will have five modules: (1) a low-noise, high-precision PSG acquisition module, (2) a programmable mixed-signal data compression module for energy efficiency, (3) a low-power ultra-wideband wireless transmitter, (4) a machine learning-based sleep stage classification module, and (5) a fully programmable multi-modal stimulator. Full integration of the system will result in a small (2 cm3), light (2 g) battery-powered device able to operate continuously for over 10 h on a single charge. In Aim 3, running concurrently with the first two aims, Co-PI Dr. Richardson will validate performance of the SoC with sleep studies in both small (rats) and large (macaques) animal models. Interleaved recordings from the wireless SoC and a tethered commercial system will assess fidelity of compressed PSG acquisition and the impact of tethering on sleep architecture. Real-time 2-stage and all-stage classifiers will be compared to offline ground truth labels. Finally, in-phase closed-loop auditory stimulation will be used to enhance slow wave activity. Our team is uniquely qualified for this proposal since we have extensive experience developing the key modules in the proposed SoC and using wireless electronics for free behavior electrophysiological experiments in both animal models. Once developed, two industry partners, CMC Microsystems and Open Ephys, Inc., will facilitate distribution of the SoC to the worldwide community. The closed-loop SoC will enable unprecedented hypothesis- driven research on sleep-stage specific neural circuits and interventions in models spanning from mice to monkeys, thereby accelerating the mechanistic understanding of sleep and treatment of sleep disorders.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Design of a Sleep Modulation System with FPGA-Accelerated Deep Learning for Closed-loop Stage-Specific In-Phase Auditory Stimulation.
采用 FPGA 加速深度学习的睡眠调制系统设计,用于闭环特定阶段同相听觉刺激。
DOI: 10.1109/iscas46773.2023.10181356
发表时间: 2023
期刊: IEEE International Symposium on Circuits and Systems proceedings. IEEE International Symposium on Circuits and Systems
影响因子: --
作者: [Sun,Mingzhe, Zhou,Aaron, Yang,Naize, Xu,Yaqian, Hou,Yuhan, Richardson,AndrewG, Liu,Xilin]
通讯作者: Liu,Xilin
海外基金