Maximizing flexibility: Optimized neural probes and electronics for long term, high bandwidth recordings

最大限度地提高灵活性：优化的神经探针和电子设备可实现长期、高带宽记录

• 批准号: 10473539
• 负责人: Loren M Frank
• 金额: $ 101.74万
• 依托单位: RICE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10473539
• 关键词: 3-Dimensional; Address; Anatomy; Animal Model; Animals; Area; Behavior; Brain; Brain region; Callithrix; Characteristics; Chronic; Cicatrix; Cognition; Collection; Communities; Complex; Computer software; Development; Devices; Dimensions; Disease; Electrodes; Electronics; Electrophysiology (science); Feedback; Heterogeneity; Hour; Image; Imaging Techniques; Implant; Individual; Laboratories; Longevity; Macaca mulatta; Measurement; Mission; Modality; Modeling; Mus; Nerve Degeneration; Neurologic; Neurons; Neurosciences; Operative Surgical Procedures; Optical Methods; Optics; Pattern; Perception; Performance; Polymers; Population; Public Health; Rattus; Research; Research Personnel; Resolution; Site; Spices; Structure; System; Techniques; Technology; Testing; Thick; Time; Tissues; United States National Institutes of Health; Utah; Work; biomaterial compatibility; cell type; density; design; disorder prevention; experience; flexibility; imaging modality; implantation; improved; in vivo; in vivo evaluation; information processing; innovation; instrumentation; lithography; millisecond; minimally invasive; nanoelectronics; neural circuit; neuromechanism; new technology; optical imaging; relating to nervous system; scale up; success; temporal measurement; tool; user-friendly

The brain is a massively interconnected network of specialized circuits. Three characteristics of these circuits make them particularly challenging: diversity of time scales, diversity of spatial scales, and heterogeneity. Understanding the brain therefore requires spanning these temporal and spatial scales and providing information about cell-types. We need to be able to record the activity of individual neurons across time to understand activity patterns on a millisecond timescale and how those patterns evolve with experience across hours, days, months and even years. We need to be able to record throughout a cortical region, spanning both different parts of the region as well as all layers, to understand both local and distributed information processing. We also need to be able to combine these dense and distributed recordings with imaging to take advantage of the complementary strengths of electrical and optical measurements. This is hindered by multiple challenges: 1) Current approaches lack the spatial extent (spanning multiple structures) required to examine three-dimensional or distributed networks in detail. 2) Current electrophysiological approaches (which do provide the millisecond resolution) typically lack the necessary lifetime to follow long-term dynamics. 3) Current electrophysiological approaches use rigid electrodes that are ill-suited to use with imaging techniques. The overall objective of this project is to optimize a suite of complementary technologies that can address these challenges for the community and make them ready for common use by the neuroscience community. Our central hypothesis is that our recently developed nanoelectronic thread (NET) devices, which have demonstrated biocompatibility, in vivo function longevity, high quality unit recording and compatibility with optical methods, are a potentially ideal candidate for understanding patterns of brain activity. We plan to develop a selection of NET probes and high-density arrays that are suitable for multiple brain regions in different spices. We will engage expert neuroscientists, allowing us to develop and optimize NETs that work across mouse, rat and marmoset, and to expedite the delivery of resulting technologies to the scientific community. We will pursue the following three specific aims: 1) To optimize NET probes for various brain regions and species.; 2) To optimize NET probes for high-density regional and distributed recordings; and 3) To determine the best devices for each species and brain regions. The approach is innovative, because the technology we will develop and put into common use has the potential to drive innovation throughout the field, enabling new, very high density recording studies and allowing investigators to track large ensembles of neurons in unprecedented details and time duration.

大脑是一个由专门电路组成的大规模互连网络。这些电路的三个特点 使它们特别具有挑战性：时间尺度的多样性、空间尺度的多样性和异质性。 因此，了解大脑需要跨越这些时间和空间尺度并提供信息 关于细胞类型。我们需要能够记录各个神经元随时间的活动以了解活动 毫秒时间尺度上的模式，以及这些模式如何随着小时、天、月的经验而演变 甚至几年。我们需要能够记录整个皮质区域，跨越大脑的不同部分 区域以及所有层，以了解本地和分布式信息处理。我们也需要成为 能够将这些密集且分布式的记录与成像相结合，以利用互补的优势 电学和光学测量的优势。这受到多重挑战的阻碍：1) 当前的方法 缺乏检查三维或分布式所需的空间范围（跨越多个结构） 网络详细。 2) 当前的电生理学方法（确实提供了毫秒分辨率） 通常缺乏必要的生命周期来遵循长期动态。 3）当前的电生理学方法 使用不适合与成像技术一起使用的刚性电极。该项目的总体目标是 优化一套补充技术，可以解决社区的这些挑战，并使 它们可供神经科学界共同使用。我们的中心假设是我们最近 开发了纳米电子线（NET）设备，该设备已证明生物相容性、体内功能 寿命长、高质量单元记录以及与光学方法的兼容性，是潜在的理想候选者 了解大脑活动的模式。我们计划开发一系列 NET 探针和高密度阵列 适合不同香料中的多个大脑区域。我们将聘请神经科学家专家，使我们能够 开发和优化适用于小鼠、大鼠和狨猴的 NET，并加快交付 向科学界提供所产生的技术。我们将追求以下三个具体目标： 1）优化 NET 探针用于不同的大脑区域和物种。 2) 优化高密度区域和网络探针 分布式录音； 3) 确定适合每个物种和大脑区域的最佳设备。方法 是创新的，因为我们将开发并投入普遍使用的技术有潜力推动 整个领域的创新，实现新的、非常高密度的记录研究，并允许研究人员 以前所未有的细节和持续时间跟踪大型神经元集合。