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High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopy
Nature Methods ( IF 36.1 ) Pub Date : 2021-08-30 , DOI: 10.1038/s41592-021-01239-8
Jeffrey Demas 1, 2 , Jason Manley 1, 2 , Frank Tejera 1 , Kevin Barber 1 , Hyewon Kim 1 , Francisca Martínez Traub 1 , Brandon Chen 1 , Alipasha Vaziri 1, 2
Affiliation  

Two-photon microscopy has enabled high-resolution imaging of neuroactivity at depth within scattering brain tissue. However, its various realizations have not overcome the tradeoffs between speed and spatiotemporal sampling that would be necessary to enable mesoscale volumetric recording of neuroactivity at cellular resolution and speed compatible with resolving calcium transients. Here, we introduce light beads microscopy (LBM), a scalable and spatiotemporally optimal acquisition approach limited only by fluorescence lifetime, where a set of axially separated and temporally distinct foci record the entire axial imaging range near-simultaneously, enabling volumetric recording at 1.41 × 108 voxels per second. Using LBM, we demonstrate mesoscopic and volumetric imaging at multiple scales in the mouse cortex, including cellular-resolution recordings within ~3 × 5 × 0.5 mm volumes containing >200,000 neurons at ~5 Hz and recordings of populations of ~1 million neurons within ~5.4 × 6 × 0.5 mm volumes at ~2 Hz, as well as higher speed (9.6 Hz) subcellular-resolution volumetric recordings. LBM provides an opportunity for discovering the neurocomputations underlying cortex-wide encoding and processing of information in the mammalian brain.



中文翻译:

使用光珠显微镜以细胞分辨率对神经活动进行高速、全皮层体积记录

双光子显微镜能够对散射脑组织内深度的神经活动进行高分辨率成像。然而,它的各种实现并没有克服速度和时空采样之间的权衡,这对于以细胞分辨率和与解析钙瞬变兼容的速度实现神经活动的中尺度体积记录是必要的。在这里,我们介绍了光珠显微镜 (LBM),这是一种可扩展且时空优化的采集方法,仅受荧光寿命限制,其中一组轴向分离且时间上不同的焦点几乎同时记录整个轴向成像范围,实现 1.41 × 的体积记录10 8每秒体素。使用 LBM,我们在小鼠皮层中展示了多个尺度的介观和体积成像,包括在 ~3 × 5 × 0.5 mm 体积内的细胞分辨率记录,在 ~5 Hz 下包含 >200,000 个神经元,以及在 ~5 Hz 内记录约 100 万个神经元群。 5.4 × 6 × 0.5 mm 体积,约 2 Hz,以及更高速度 (9.6 Hz) 的亚细胞分辨率体积记录。LBM 为发现哺乳动物大脑中皮层范围编码和信息处理的神经计算提供了机会。

更新日期:2021-08-30
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