A Guide to Emerging Technologies for Large-Scale and Whole-Brain Optical Imaging of Neuronal Activity.

A Guide to Emerging Technologies for Large-Scale and Whole-Brain Optical Imaging of Neuronal Activity.
复制标题

DOI:
10.1146/annurev-neuro-072116-031458
复制
发表时间:
2018-07-08
影响因子:
13.9
通讯作者:
Vaziri A
Vaziri A
中科院分区:
医学1区
文献类型:
--
作者:
Weisenburger S;Vaziri A

文献摘要

参考文献

被引文献

相似文献

哺乳动物的大脑是一个密集互联的网络,由数百万到数十亿个神经元组成。要想解码这种神经回路是如何表达和处理信息的,就需要有能力在大脑的大面积上以高速和高分辨率捕捉和操纵大量人群的动态。虽然在过去的二十年里,神经科学界使用光学方法的人数迅速增加,但大多数显微镜方法缺乏以相关的时间和空间分辨率记录哺乳动物大脑中所有神经元(包括功能网络)活动的能力。在这篇综述中,我们调查的光学钙成像技术在这方面的最新发展,并提供了一个概述的优势和局限性,每种模式和它们的可扩展性的潜力。我们从生物学用户的角度提供指导,该角度由典型的生物学应用和样品条件驱动。我们还讨论了通过混合方法或其他模式可以获得的未来进展和协同增效的潜力。
The mammalian brain is a densely interconnected network that consists of millions to billions of neurons. Decoding how information is represented and processed by this neural circuitry requires the ability to capture and manipulate the dynamics of large populations at high speed and resolution over a large area of the brain. While there has been a rapid increase in use of optical approaches in the neuroscience community over the last two decades, most microscopy approaches lack the ability to record the activity of all neurons comprising a functional network across the mammalian brain at relevant temporal and spatial resolution. In this review, we survey the recent development in the optical calcium imaging technologies in this regard and provide an overview of the strengths and limitations of each modality and their potential for scalability. We provide a guidance from a biological user perspective that is driven by the typical biological applications and sample conditions. We also discuss the potential for future advances and synergies that could be obtained through hybrid approaches or other modalities.
DOI: 10.1038/nn.4593
发表时间: 2017-08
影响因子: 25
作者:
Chan KY;Jang MJ;Yoo BB;Greenbaum A;Ravi N;Wu WL;Sánchez-Guardado L;Lois C;Mazmanian SK;Deverman BE;Gradinaru V
通讯作者: Gradinaru V
DOI: 10.1038/nn1525
发表时间: 2005-09-01
影响因子: 25
作者:
Boyden, ES;Zhang, F;Deisseroth, K
通讯作者: Deisseroth, K
DOI: 10.1038/nrn3687
发表时间: 2014-04
影响因子: 34.7
作者:
Buzsaki, Gyoergy;Mizuseki, Kenji
通讯作者: Mizuseki, Kenji
DOI: 10.1016/j.jneumeth.2013.10.021
发表时间: 2014-01-30
影响因子: 3
作者:
Fernandez-Alfonso, Tomas;Nadella, K. M. Naga Srinivas;Silver, R. Angus
通讯作者: Silver, R. Angus
DOI: 10.7554/elife.25690
发表时间: 2017-07-27
期刊: ELIFE
影响因子: 7.7
作者:
Chamberland, Simon;Yang, Helen H.;St-Pierre, Francois
通讯作者: St-Pierre, Francois