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适应光学三光子显微镜实现高分辨率的结构和功能深层大脑成像
作者:小柯机器人 发布时间:2021/10/9 16:09:00

近日,德国欧洲分子生物学实验室Robert Prevedel团队使用自适应光学三光子显微镜实现高分辨率的结构和功能深层大脑成像。相关论文于2021年9月30日在线发表在《自然—方法学》杂志上。

研究人员开发了一种基于三光子激发、间接自适应光学(AO)和主动心电门控的微创眼内成像方法,用于推进深层组织成像。研究人员基于模态的无传感器AO方法对深层散射组织(如小鼠大脑)常见的低信噪比有很强的适应性,并能够在大的轴向视场进行AO校正。研究人员展示了深层皮质棘突和(亚)皮质树突的近衍射限制成像,深度达1.4毫米(小鼠CA1海马体的边缘)。此外,研究人员还展示了星形细胞深层钙成像的应用,包括驻留在高散射胼胝体中的纤维星形细胞。

据悉,多光子显微镜已经成为一个强大的工具,用来观察完整的哺乳动物大脑中的神经细胞和电路的形态和功能。然而,组织散射、光学畸变和运动伪影降低了深度成像的性能。

附:英文原文

Title: High-resolution structural and functional deep brain imaging using adaptive optics three-photon microscopy

Author: Streich, Lina, Boffi, Juan Carlos, Wang, Ling, Alhalaseh, Khaleel, Barbieri, Matteo, Rehm, Ronja, Deivasigamani, Senthilkumar, Gross, Cornelius T., Agarwal, Amit, Prevedel, Robert

Issue&Volume: 2021-09-30

Abstract: Multiphoton microscopy has become a powerful tool with which to visualize the morphology and function of neural cells and circuits in the intact mammalian brain. However, tissue scattering, optical aberrations and motion artifacts degrade the imaging performance at depth. Here we describe a minimally invasive intravital imaging methodology based on three-photon excitation, indirect adaptive optics (AO) and active electrocardiogram gating to advance deep-tissue imaging. Our modal-based, sensorless AO approach is robust to low signal-to-noise ratios as commonly encountered in deep scattering tissues such as the mouse brain, and permits AO correction over large axial fields of view. We demonstrate near-diffraction-limited imaging of deep cortical spines and (sub)cortical dendrites up to a depth of 1.4mm (the edge of the mouse CA1 hippocampus). In addition, we show applications to deep-layer calcium imaging of astrocytes, including fibrous astrocytes that reside in the highly scattering corpus callosum.

DOI: 10.1038/s41592-021-01257-6

Source: https://www.nature.com/articles/s41592-021-01257-6

期刊信息

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:28.467
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex