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: 10231150
• 负责人: TIMOTHY D HARRIS
• 金额: $ 99.77万
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10231150
• 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 了解认知和行为的基础的神经机制需要 测量神经元种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的能力 以思想速度跨越浅层和深层结构的活动。最近的进步 电生理学大大增加了数据数量，质量和易用性， 从而有意义地减少了理解全球大脑电路的障碍 行为。剩下的重大挑战是优化设备特性，以便 进一步扩大效用，提高数据质量并加速研究的步伐。在 特别的，最先进的位点密度在空间上太粗糙，无法检测到某些细胞类型，并且 神经元过程；在大脑面前稳定记录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，以解决这些限制 > 10x录制网站的数量比最先进的数量，对应于 幅度更高的密度。因此，该设备的功能就像高分辨率电机摄像头 在大脑中，能够成像微小的电场并能够利用技术 从用于记录稳定性的图像注册之类的光学器件中。 我们将通过量化其增加来验证和开发新的探测特征 能够检测大量神经元类型的能力；通过测试和发展他们跟踪的能力 使用受控条件的神经元在大脑运动中跨越；通过改进算法向 数据预处理的自动化；并通过进行多模式地面真相实验。 这些探针将超出解决技术限制的范围，还提供了新类型的 数据：“电形式”形状的电成像将实现增强的细胞类型 体内神经元生物物理模型的鉴定和验证。 我们将传播新探针以及用户友好的软件以利用 它们的提高特征，以“β-tester”实验室，特别有兴趣研究密钥 科学机会的领域。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他们 对科学进步的影响。