Recording from one million neurons
来自一百万个神经元的记录
基本信息
- 批准号:BB/W019884/1
- 负责人:
- 金额:$ 37.41万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2022
- 资助国家:英国
- 起止时间:2022 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Brain function is organized through the collective activity of a myriad neurons: about 10 million of them in a mouse brain, and about 90 billion in our brain. This collective activity is called the neural code. Our ability to decipher this code is very limited, largely because we have been able to access only small fragments of it. The best technologies available today allow us to read at most the activity of a few thousand neurons at a time.A new technology that appeared in the USA this year, the Light Beads Microscope, allows for a major increase in the number of neurons that we can record at the same time: one million neurons. This microscope was developed at Rockefeller University in New York, and will next be deployed in key laboratories across the United States. Thanks to our close collaboration with the inventors, we have the opportunity to deploy the first such device outside the USA. We will install it in our laboratory in London, where we will provide ample access to colleagues across the United Kingdom to perform, pilot, or observe experiments that would not have been possible even a year ago. The Light Beads Microscope is a particularly powerful version of a technology called two-photon imaging. A traditional two-photon microscope focuses light from a laser on a single point in the brain and moves this point along a plane, revealing the activity of the neurons in that plane. If a volume is desired, the acquisition must be repeated across multiple planes, greatly limiting the rate of acquisition. Moreover, the time required to move within a plane and across planes is much longer than the time required to image a point, so most of the imaging time is wasted. In a Light Beads Microscope, instead, the light is patterned in a line of beads separated in time by minuscule intervals, so while the microscope is scanning one point, it is imaging an entire line below it. By scanning a single plane, the microscope acquires a whole volume, with no wasted time. This technology requires a combination of three components. The first is a specialized source of powerful light pulses that are extraordinarily brief and frequent. The second is a module that sequentially focuses these pulses into a line of "light beads" separated in both space and time. The third is a traditional two-photon microscope that scans this line through a horizontal plane. We have already secured the second and third items thanks to separate funding, and are here requesting funds to purchase the first item, the light source. With this light source, we will obtain a uniquely advanced new microscope that will allow unprecedented measurements of the activity of ~1 million neurons in the living brain. At higher magnification, the microscope will also provide unprecedented measurements of brain activity in smaller structures, for instance to reveal the activity of the entire extent of a single neuron.
大脑功能是通过无数神经元的集体活动来组织的:其中约1000万个在小鼠大脑中,在我们的大脑中约为900亿。这种集体活动称为神经代码。我们破译该代码的能力非常有限,这主要是因为我们只能访问其小片段。当今可用的最佳技术使我们最多可以阅读数千个神经元的活动。今年美国出现的一项新技术,即Light Beads显微镜,可以使我们可以同时记录的神经元数量大量增加:一百万个神经元。该显微镜是在纽约的洛克菲勒大学开发的,接下来将部署在美国的主要实验室中。由于我们与发明人的密切合作,我们有机会在美国以外部署第一个此类设备。我们将安装在伦敦的实验室中,在那里我们将提供足够的访问英国同事的访问权限,以表演,试点或观察一年前甚至是不可能的实验。光珠显微镜是一种称为“两光子成像”的技术的特别强大的版本。传统的两光子显微镜将来自激光的光聚焦在大脑的单个点上,并沿着平面移动这一点,从而揭示了该平面中神经元的活性。如果需要数量,则必须在多个飞机上重复采集,从而极大地限制了采集率。此外,在平面和飞机上移动所需的时间要比成像点所需的时间长得多,因此大多数成像时间都浪费了。相反,在光珠显微镜中,将光线图案化在按小节间隔内分离的一条珠子中,因此,当显微镜扫描一个点时,它在其下方的整个线上成像。通过扫描单个平面,显微镜将获得整个体积,没有浪费时间。该技术需要组合三个组件。第一个是强大的光脉冲的专业来源,它们非常简短且频繁。第二个是一个模块,将这些脉冲依次聚焦于空间和时间分开的“光珠”线。第三是传统的两光子显微镜,它通过水平面扫描这条线。由于分开的资金,我们已经确保了第二和第三件物品,并且在这里要求资金购买第一个物品,即灯源。使用此光源,我们将获得一个独特的高级新显微镜,该显微镜将允许对活大脑中约100万个神经元的活性进行前所未有的测量。在更高的放大倍率下,显微镜还将提供较小结构中脑活动的前所未有的测量,例如揭示单个神经元的整个范围的活性。
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)
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Matteo Carandini其他文献
Matteo Carandini的其他文献
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Coding and wiring in a million cortical neurons
一百万个皮质神经元的编码和连接
- 批准号:
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$ 37.41万 - 项目类别:
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