NeuropixelsUltra: Dense arrays for stable, unbiased, and cell type-specific electrical imaging

NeuropixelsUltra：用于稳定、无偏且细胞类型特异性电成像的密集阵列

• 批准号: 10016865
• 负责人: TIMOTHY D HARRIS
• 金额: $ 111.12万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10016865
• 关键词: Action Potentials; Address; Algorithms; Anatomy; Area; Automation; BRAIN initiative; Back; Behavior; Biophysics; Brain; Brain region; Characteristics; Cognition; Collaborations; Communities; Computer software; Data; Data Set; Detection; Devices; Disease; Electrodes; Electrophysiology (science); Elements; Ensure; Event; Funding; Goals; Image; Image Enhancement; Individual; Industrialization; Infrastructure; Leadership; Learning; Measurement; Measures; Methods; Morphology; Motion; Nature; Nerve Degeneration; Neurons; Optics; Population; Process; Production; Psyche structure; Research; Resolution; Resources; Sampling; Sampling Biases; Science; Shapes; Site; Software Tools; Sorting - Cell Movement; Speed; Structure; System; Techniques; Testing; Training; Validation; Work; base; biophysical model; cell type; cost; cost efficient; data quality; density; design; disability; electric field; excitatory neuron; experimental study; flexibility; granule cell; hippocampal pyramidal neuron; image registration; imaging modality; improved; improved outcome; in vivo; in vivo Model; inhibitory neuron; innovation; interest; multimodality; neuromechanism; next generation; novel; open source; programs; temporal measurement; tool; two-photon; user friendly software; user-friendly; voltage

Summary/Abstract Understanding the neural mechanisms underpinning cognition and behavior requires the ability to measure the dynamics and interactions of populations of neurons spread across many brain regions. Electrophysiological techniques provide the ability to measure this activity across superficial and deep structures at the speed of thought. Recent advances in electrophysiology have massively increased data quantity, quality, and ease of acquisition, thereby meaningfully reducing barriers to understanding the global brain circuits underlying behavior. A significant remaining challenge is to optimize device characteristics in order to further broaden utility, improve data quality, and accelerate the pace of research. In particular, state of the art site density is spatially too coarse to detect some cell types and neuronal processes; it remains challenging to record neurons stably in the face of brain motion; and data preprocessing is still a major limiting factor in the pace of experiments. This proposal will address these limitations by producing and evaluating a new device with >10x the number of recording sites than state-of-the-art, corresponding to an order of magnitude higher density. This device thus functions like a high-resolution electrical camera in the brain, able to image tiny electrical fields and capable of capitalizing on techniques from optics such as image registration for recording stability. We will validate and develop the new probe's characteristics by quantifying their increased ability to detect a large range of neuron types; by testing and developing their ability to track neurons across brain motion using controlled conditions; by improving algorithms towards automation of data preprocessing; and by conducting multi-modal ground-truth experiments. These probes will go beyond solving technical limitations, additionally providing new types of data: electrical imaging of `electro-morphological' shapes will enable enhanced cell-type identification and validation of neuronal biophysical models in vivo. We will disseminate the new probes, along with user-friendly software to take advantage of their improved characteristics, to `beta-tester' labs specifically interested in studying key areas of scientific opportunity. These areas include dendritic computation, freely-moving behavior, and cerebellar function, and this direct dissemination will rapidly accelerate their impact on scientific advancement.

摘要/摘要 了解支撑认知和行为的神经机制需要 测量分布在各处的神经元群的动态和相互作用的能力 许多大脑区域。电生理技术提供了测量这一点的能力 以思维的速度跨越表层和深层结构的活动。最近的进展 电生理学极大地提高了数据的数量、质量和获取的便利性， 从而有意义地减少理解全球大脑回路的障碍 行为。剩下的一个重大挑战是优化器件特性，以便 进一步拓宽效用，提高数据质量，加快研究步伐。在 特别是，最先进的位点密度在空间上太粗糙，无法检测某些细胞类型，并且 神经元过程；稳定地记录大脑面部的神经元仍然具有挑战性 运动;数据预处理仍然是实验速度的主要限制因素。 该提案将通过生产和评估新设备来解决这些限制 > 记录站点数量是最先进技术的 10 倍，相当于 密度更高。因此，该设备的功能类似于高分辨率电子相机 在大脑中，能够对微小的电场进行成像并能够利用技术 来自光学器件，例如用于记录稳定性的图像配准。 我们将通过量化新探针增加的特性来验证和开发新探针的特性。 检测多种神经元类型的能力；通过测试和发展他们的跟踪能力 使用受控条件进行跨大脑运动的神经元；通过改进算法 数据预处理自动化；并进行多模态地面实况实验。 这些探测器将超越解决技术限制，此外还提供新型 数据：“电形态”形状的电成像将增强细胞类型 体内神经元生物物理模型的识别和验证。 我们将传播新的探测器以及用户友好的软件以利用 他们改进的特性，以“测试测试”实验室特别有兴趣研究关键 科学机会领域。这些领域包括树突计算、自由移动 行为和小脑功能，这种直接传播将迅速加速它们 对科学进步的影响。