CAREER: Resolving action potentials and high-density neural signals from the surface of the brain
职业:解析来自大脑表面的动作电位和高密度神经信号
基本信息
- 批准号:1752274
- 负责人:
- 金额:$ 55万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-05-01 至 2024-04-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The surface of the brain remains an unexplored frontier in brain/neural interface design, despite the fact that it is simpler and safer to place electrodes ?onto? the brain than ?into? the brain. The research goal of this project is to build and optimize an innovative electrode array device that will improve the resolution of brain interface devices by more than 1000-fold. This goal is now considered possible due to the PI?s breakthrough success in developing electronics that can support more than 650 electrodes with a single wire. The array, which can both record brain activity and stimulate the brain, will enable research into the subtle brain signals that generate seizures in people with epilepsy and unlock new treatment options. The technology will also dramatically improve the performance of motor prosthetic devices for the paralyzed, visual prosthetic devices for the blind, and facilitate new treatments for other neurological disorders. The educational goal is to engage students and teachers in understanding brain-machine interfaces and increase interest among students in pursuing STEM undergraduate degrees and careers. In collaboration with several local high schools, a high-school written science module on neuroengineering, meeting state and national science standards, will be created. The PI will develop materials for high school biology and physics teachers to introduce the field of neuroengineering with a hands-on laboratory exercise. The PI will host an annual workshop for 20 science teachers from around the state to introduce the field of neuroengineering and to give the teachers a chance to try out the lab materials.The project's research objective, driven by the PI's recent breakthrough development of active, flexible electronics that will enable implanted neural interfaces in which greater than 65,000 electrodes can be sampled using fewer than 100 wires, is to advance and optimize these brain interfaces by measuring fundamental neural interface design parameters. These design parameters critically influence the signal to noise ratio, total information content, and long-term reliability of electrode implants. Leveraging both computational models and experimental results related to audio responses in rats and comparisons to nonhuman primate data made available by a collaborator, three aspects critical to the performance of neural interface devices will be investigated: 1) electrode material and contact size, 2) electrode spacing, and 3) array geometry. The implant design uses the same electronics that permit a digital camera to have millions of pixels without millions of wires and will improve the resolution of brain interface devices by more than 1000-fold. The Research Plan is organized under 3 objectives: 1) Measure the effect of cortical surface contact size, material, and impedance on the properties of the recorded neural signals, including the recording of action potentials (APs); 2) Determine the surface electrode spacing required to satisfy Nyquist-Shannon spatial sampling by measuring the information content of neural signals from varying length scales and 3) Understand the biological and non-biological factors that influence the long-term reliability of surface electrode arrays by chronically implanting surface electrode arrays in freely behaving rats and evaluating long-term function and biocompatibility. The project's educational objective, to create a high-school science module, involves development and dissemination of curricular resources and a lab exercise using Arduino microcontrollers that will allow students to record and display their own electromyographic(EMG) signals and use them to control a video game.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
大脑的表面仍然是大脑/神经接口设计的一个未开发的前沿,尽管事实上放置电极更简单,更安全?上?大脑比?变成什么大脑 该项目的研究目标是构建和优化一种创新的电极阵列设备,将大脑接口设备的分辨率提高1000倍以上。 这个目标现在被认为是可能的,由于PI?在开发电子产品方面取得了突破性的成功,这种电子产品可以用一根电线支持650多个电极。 该阵列既可以记录大脑活动,又可以刺激大脑,将有助于研究癫痫患者癫痫发作的微妙大脑信号,并开启新的治疗选择。 该技术还将大大提高瘫痪者的运动假肢设备的性能,盲人的视觉假肢设备,并促进其他神经系统疾病的新治疗。 教育目标是让学生和教师参与理解脑机接口,并提高学生攻读STEM本科学位和职业的兴趣。与当地几所高中合作,将创建一个符合州和国家科学标准的关于神经工程的高中书面科学模块。PI将为高中生物和物理教师开发材料,通过动手实验练习介绍神经工程领域。PI将为来自全州的20名科学教师举办年度研讨会,介绍神经工程领域,并让教师有机会试用实验室材料。该项目的研究目标是由PI最近突破性开发的有源柔性电子器件驱动,该器件将使植入的神经接口超过65,000个电极可以使用少于100根导线进行采样,是通过测量基本的神经接口设计参数来推进和优化这些大脑接口。这些设计参数严重影响电极植入物的信噪比、总信息量和长期可靠性。利用与大鼠音频响应相关的计算模型和实验结果,以及与合作者提供的非人灵长类动物数据的比较,将研究对神经接口设备性能至关重要的三个方面:1)电极材料和接触尺寸,2)电极间距和3)阵列几何形状。植入物设计使用相同的电子器件,允许数码相机具有数百万像素而无需数百万电线,并将大脑接口设备的分辨率提高1000倍以上。研究计划有3个目标:1)测量皮质表面接触尺寸、材料和阻抗对记录的神经信号特性的影响,包括记录动作电位(AP); 2)通过测量来自不同长度尺度的神经信号的信息内容来确定满足Nyquist-Shannon空间采样所需的表面电极间距,以及通过在自由行为大鼠体内长期植入表面电极阵列,并评价长期功能和生物相容性,了解影响表面电极阵列长期可靠性的生物和非生物因素。该项目的教育目标是创建一个高中科学模块,涉及课程资源的开发和传播,以及使用Arduino微控制器的实验室练习,允许学生记录和显示自己的肌电图(EMG)该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准。
项目成果
期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Flexible electronic/optoelectronic microsystems with scalable designs for chronic biointegration
- DOI:10.1073/pnas.1907697116
- 发表时间:2019-07
- 期刊:
- 影响因子:0
- 作者:E. Song;Chia-Han Chiang;Rui Li;Xin Jin;Jianing Zhao;Mackenna Hill;Yu Xia;Lizhu Li;Yuming Huang
- 通讯作者:E. Song;Chia-Han Chiang;Rui Li;Xin Jin;Jianing Zhao;Mackenna Hill;Yu Xia;Lizhu Li;Yuming Huang
Development of a neural interface for high-definition, long-term recording in rodents and nonhuman primates
- DOI:10.1126/scitranslmed.aay4682
- 发表时间:2020-04-08
- 期刊:
- 影响因子:17.1
- 作者:Chiang, Chia-Han;Won, Sang Min;Viventi, Jonathan
- 通讯作者:Viventi, Jonathan
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Jonathan Viventi其他文献
Artefact-free wireless closed-loop device
无伪迹无线闭环装置
- DOI:
10.1038/s41551-018-0340-9 - 发表时间:
2019-01-08 - 期刊:
- 影响因子:26.600
- 作者:
Chia-Han Chiang;Jonathan Viventi - 通讯作者:
Jonathan Viventi
Jonathan Viventi的其他文献
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{{ truncateString('Jonathan Viventi', 18)}}的其他基金
CIF: Medium: Collaborative Research: Scalable Learning of Nonlinear Models in Large Neural Populations
CIF:媒介:协作研究:大型神经群体中非线性模型的可扩展学习
- 批准号:
1564051 - 财政年份:2016
- 资助金额:
$ 55万 - 项目类别:
Continuing Grant
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