In-vivo circuit activity measurement at single cell, sub-threshold resolution

单细胞体内电路活动测量,亚阈值分辨率

基本信息

  • 批准号:
    8935946
  • 负责人:
  • 金额:
    $ 50.25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-26 至 2017-05-31
  • 项目状态:
    已结题

项目摘要

 DESCRIPTION (provided by applicant): Neurons communicate information through fluctuations in the electrical potentials across their cellular membranes. Whole-cell patch clamping, the gold standard technique for measuring these fluctuations, is something of an art form, requiring great skill to perform on only a few cells per day. Thus, it has been primarily limited to in vitro experiments, a few in vivo experiments, and very limited applications in the awake brain. Dr. Forest (and collaborator Dr. Boyden at MIT) developed a robot that automatically performs patch clamping in the living brains of mice by algorithmically detecting cells through analysis of a temporal sequence of electrode impedance changes. Using it, they have demonstrated good yield, throughput, and quality of recording in mouse cortex and hippocampus. With this 'autopatching' robot enabling routine access to electrical and molecular properties of neurons, systematic and scalable in vivo experiments as well as fundamentally new kinds of single-cell analyses have become possible. In the past 12 months, the team has installed 15 autopatchers in academic research laboratories, garnered worldwide media coverage, and led to Dr. Forest's and Dr. Boyden's invitations to President Barack Obama's announcement of the BRAIN Initiative. There are currently no published experiments demonstrating in vivo intracellular recordings of two or more neurons that are synaptically connected. We propose to utilize the autopatcher to target anatomically well-studied sub-circuits to significantly increase the odds of identifying synaptically connected pairs. Specifically, we wil utilize the thalamocortical circuit in the mouse vibrissa/whisker pathway as a model experimental system, where there is a substantial convergence of projections from the thalamus to the input layer in the somatosensory (tactile) cortex. The Stanley Laboratory has extensive experience with stimulation and electrophysiological recordings in this circuit, and is one of only a few laboratories that has successfully recorded from synaptically connected pairs of neurons using extracellular techniques. Thus we aim to demonstrate and characterize the first simultaneous intracellular recording of a functional circuit in the anesthetized and awake living mouse brain to reveal its neural network dynamics. In this 36 month program, the labs of Prof. Stanley and Forest, supported by two postdoctoral researchers, two graduate research assistants, a research engineer and five undergraduates, with assistance from ten graduate students working on related projects, will develop single (Aim 1) and dual (Aim 2,3) autopatching robots for the anesthetized and awake brain. Success will allow, for the first time, quantification of synaptic efficacy in the living brain, crucial for understanding normal and pathological function. Just as molecular biology has greatly benefited from the revolution in in vitro automation, we believe that neuroscience will greatly benefit from the revolution in in vivo automation that we have launched, and here propose to extend.
 描述(申请人提供):神经元通过其细胞膜上的电势波动来传递信息。全细胞膜片钳是测量这些波动的黄金标准技术,它是一种艺术形式,每天只对几个细胞进行操作需要很高的技能。因此,它主要局限于体外实验,少数体内实验,在清醒的大脑中的应用非常有限。福里斯特博士(和他的合作者,麻省理工学院的博伊登博士)开发了一种机器人,通过分析电极阻抗变化的时间序列,通过算法检测细胞,自动在小鼠的活脑中执行膜片钳。使用它,它们在小鼠皮质和海马区表现出了良好的产量、吞吐量和记录质量。有了这个“自动配对”机器人,能够常规地获取神经元的电学和分子特性,系统和可扩展的活体实验以及从根本上说新型的单细胞分析已经成为可能。在过去的12个月里,该团队在学术研究实验室安装了15个自动配置器,获得了全球媒体的报道,并邀请福里斯特博士和博伊登博士参加巴拉克·奥巴马总统宣布的大脑倡议。目前还没有发表的实验证明体内细胞内记录了两个或更多突触连接的神经元。我们建议利用自动配置器来定位解剖学上研究得很好的子回路,以显著增加识别突触连接对的几率。具体地说,我们将利用小鼠触须/胡须通路中的丘脑皮质回路作为模型实验系统,在该系统中,从丘脑到躯体感觉(触觉)皮质的输入层有大量的投射汇聚。斯坦利实验室在这一回路的刺激和电生理记录方面拥有丰富的经验,是仅有的 一些实验室已经使用细胞外技术成功地记录了突触连接的神经元对。因此,我们的目标是展示和表征第一次在麻醉和清醒的活体小鼠脑中同时记录功能电路的细胞内记录,以揭示其神经网络动力学。在这个为期36个月的项目中,斯坦利教授和福里斯特教授的实验室将在两名博士后研究人员、两名研究生研究助理、一名研究工程师和五名本科生的支持下,在十名从事相关项目的研究生的帮助下,为麻醉和清醒的大脑开发单(目标1)和双(目标2,3)自动匹配机器人。成功将首次量化活着的大脑中的突触效能,这对理解正常和病理功能至关重要。就像分子生物学从体外自动化革命中受益匪浅一样,我们相信神经科学也将从我们发起的体内自动化革命中受益匪浅,并在此提议扩展。

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(1)

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Craig Forest其他文献

Craig Forest的其他文献

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{{ truncateString('Craig Forest', 18)}}的其他基金

Automated cell-type-specific electrophysiology for understanding circuit dysregulation in Alzheimer's Disease
自动化细胞类型特异性电生理学用于了解阿尔茨海默氏病的电路失调
  • 批准号:
    10525870
  • 财政年份:
    2022
  • 资助金额:
    $ 50.25万
  • 项目类别:

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