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

基本信息

  • 批准号:
    10016865
  • 负责人:
  • 金额:
    $ 111.12万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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.
总结/摘要 理解认知和行为的神经机制需要 测量神经元群体的动力学和相互作用的能力 许多脑区。电生理学技术提供了测量这一点的能力 以思维的速度在表层和深层结构中活动。的最新进展 电生理学已经大大增加了数据的数量、质量和采集的容易性, 从而有意义地减少了理解全球大脑回路的障碍, 行为一个重要的剩余挑战是优化器件特性, 进一步拓宽利用面,提高数据质量,加快研究步伐。在 特别地,现有技术的位点密度在空间上太粗糙而不能检测某些细胞类型, 神经元过程;在大脑中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。 本提案将通过生产和评估一种新器械来解决这些局限性, > 10倍于现有技术的记录位点数量,对应于 密度更高。因此,该装置的功能类似于高分辨率电子照相机 在大脑中,能够成像微小的电场,并能够利用技术 从光学器件,如图像配准记录稳定性。 我们将通过量化新探头的增加来验证和开发新探头的特性 检测大量神经元类型的能力;通过测试和发展他们的跟踪能力 神经元在大脑运动中使用受控条件;通过改进算法, 数据预处理的自动化;以及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,还提供新型的 数据:“电形态学”形状的电成像将能够增强细胞类型 体内神经元生物物理模型的鉴定和验证。 我们将分发新的探头,沿着用户友好的软件,以利用 他们改进的特性,"测试“实验室特别感兴趣的研究关键 科学机遇的领域。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的行为, 影响科学进步。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

TIMOTHY D HARRIS其他文献

TIMOTHY D HARRIS的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('TIMOTHY D HARRIS', 18)}}的其他基金

Neuropixels NXT: Integrated Silicon Probes for Large Scale Extracellular Recording in Rodents and Primates
Neuropixels NXT:用于啮齿动物和灵长类动物大规模细胞外记录的集成硅探针
  • 批准号:
    10475277
  • 财政年份:
    2020
  • 资助金额:
    $ 111.12万
  • 项目类别:
Neuropixels NXT: Integrated Silicon Probes for Large Scale Extracellular Recording in Rodents and Primates
Neuropixels NXT:用于啮齿动物和灵长类动物大规模细胞外记录的集成硅探针
  • 批准号:
    9924965
  • 财政年份:
    2020
  • 资助金额:
    $ 111.12万
  • 项目类别:
Neuropixels NXT: Integrated Silicon Probes for Large Scale Extracellular Recording in Rodents and Primates
Neuropixels NXT:用于啮齿动物和灵长类动物大规模细胞外记录的集成硅探针
  • 批准号:
    10240456
  • 财政年份:
    2020
  • 资助金额:
    $ 111.12万
  • 项目类别:
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
  • 财政年份:
    2019
  • 资助金额:
    $ 111.12万
  • 项目类别:
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:
    10469690
  • 财政年份:
    2019
  • 资助金额:
    $ 111.12万
  • 项目类别:
High Accuracy Single Molecule DNA Sequencing by Synthesis
高精度单分子 DNA 合成测序
  • 批准号:
    7192686
  • 财政年份:
    2006
  • 资助金额:
    $ 111.12万
  • 项目类别:

相似海外基金

Rational design of rapidly translatable, highly antigenic and novel recombinant immunogens to address deficiencies of current snakebite treatments
合理设计可快速翻译、高抗原性和新型重组免疫原,以解决当前蛇咬伤治疗的缺陷
  • 批准号:
    MR/S03398X/2
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Fellowship
Re-thinking drug nanocrystals as highly loaded vectors to address key unmet therapeutic challenges
重新思考药物纳米晶体作为高负载载体以解决关键的未满足的治疗挑战
  • 批准号:
    EP/Y001486/1
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Research Grant
CAREER: FEAST (Food Ecosystems And circularity for Sustainable Transformation) framework to address Hidden Hunger
职业:FEAST(食品生态系统和可持续转型循环)框架解决隐性饥饿
  • 批准号:
    2338423
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Continuing Grant
Metrology to address ion suppression in multimodal mass spectrometry imaging with application in oncology
计量学解决多模态质谱成像中的离子抑制问题及其在肿瘤学中的应用
  • 批准号:
    MR/X03657X/1
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Fellowship
CRII: SHF: A Novel Address Translation Architecture for Virtualized Clouds
CRII:SHF:一种用于虚拟化云的新型地址转换架构
  • 批准号:
    2348066
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Standard Grant
The Abundance Project: Enhancing Cultural & Green Inclusion in Social Prescribing in Southwest London to Address Ethnic Inequalities in Mental Health
丰富项目:增强文化
  • 批准号:
    AH/Z505481/1
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Research Grant
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
  • 批准号:
    10107647
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    EU-Funded
BIORETS: Convergence Research Experiences for Teachers in Synthetic and Systems Biology to Address Challenges in Food, Health, Energy, and Environment
BIORETS:合成和系统生物学教师的融合研究经验,以应对食品、健康、能源和环境方面的挑战
  • 批准号:
    2341402
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Standard Grant
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
  • 批准号:
    10106221
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    EU-Funded
Recite: Building Research by Communities to Address Inequities through Expression
背诵:社区开展研究,通过表达解决不平等问题
  • 批准号:
    AH/Z505341/1
  • 财政年份:
    2024
  • 资助金额:
    $ 111.12万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了