Monitoring activity in neural circuits with genetically encoded indicators.
Monitoring activity in neural circuits with genetically encoded indicators.
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DOI：
10.3389/fnmol.2014.00097
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发表时间：
2014
影响因子：
4.8
通讯作者：
Tian L
中科院分区：
文献类型：
--
作者：
Broussard GJ;Liang R;Tian L
神经活动的遗传编码指标（GINAs）的最新发展极大地推进了系统神经科学领域。由于它们由DNA编码，GINA可以靶向遗传定义的细胞群体。与荧光显微镜相结合，最值得注意的是多光子成像，GINA允许从清醒的行为哺乳动物，特别是啮齿动物中的大量神经元或神经胶质细胞中进行慢性同时光学记录。这种在多个时间和空间尺度上对神经活动的大规模记录极大地促进了我们对行为背后的神经回路动力学的理解，这是理解大脑功能复杂性的关键第一步，例如感觉运动整合和学习。本文综述了近年来几类GINA的发展和应用。特别是，我们深入研究了现有GINA家族的设计，特别关注遗传编码的钙指标（GCaMP），探测突触活动的传感器和遗传编码的电压指标。使用家庭的GCaMP作为一个例子，我们审查建立传感器优化管道。我们还讨论了GINA最终用户关于实验方法的实际考虑，包括基因递送方法，成像系统要求和数据分析技术。随着GINA工具箱的不断增长，以及新的显微镜技术突破了当前的极限，光的时代最终可以实现跨时间和大脑结构对神经元活动进行广泛而密集的采样，以获得大脑功能的动态图像。
Recent developments in genetically encoded indicators of neural activity (GINAs) have greatly advanced the field of systems neuroscience. As they are encoded by DNA, GINAs can be targeted to genetically defined cellular populations. Combined with fluorescence microscopy, most notably multi-photon imaging, GINAs allow chronic simultaneous optical recordings from large populations of neurons or glial cells in awake, behaving mammals, particularly rodents. This large-scale recording of neural activity at multiple temporal and spatial scales has greatly advanced our understanding of the dynamics of neural circuitry underlying behavior—a critical first step toward understanding the complexities of brain function, such as sensorimotor integration and learning. Here, we summarize the recent development and applications of the major classes of GINAs. In particular, we take an in-depth look at the design of available GINA families with a particular focus on genetically encoded calcium indicators (GCaMPs), sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the GCaMP as an example, we review established sensor optimization pipelines. We also discuss practical considerations for end users of GINAs about experimental methods including approaches for gene delivery, imaging system requirements, and data analysis techniques. With the growing toolbox of GINAs and with new microscopy techniques pushing beyond their current limits, the age of light can finally achieve the goal of broad and dense sampling of neuronal activity across time and brain structures to obtain a dynamic picture of brain function.
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影响因子：
12.4
作者：
Cearley, CN;Wolfe, JH
通讯作者：
Wolfe, JH
影响因子：
5.3
作者：
Andermann ML;Kerlin AM;Reid RC
通讯作者：
Reid RC
影响因子：
3
作者：
Baker, B. J.;Lee, H.;Kosmidis, E. K.
通讯作者：
Kosmidis, E. K.
DOI：
10.1073/pnas.0707574105
发表时间：
2007-12-18
影响因子：
11.1
作者：
Balaji, J.;Ryan, T. A.
通讯作者：
Ryan, T. A.
影响因子：
48
作者：
Akemann, Walther;Mutoh, Hiroki;Knoepfel, Thomas
通讯作者：
Knoepfel, Thomas