Institute of Photonics, Dept. of Physics, University of Strathclyde, G1 1RD, Glasgow, UK.
Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA, United States.
Sci Rep. 2017 Nov 13;7(1):15395. doi: 10.1038/s41598-017-15741-7.
Understanding the role of neurons in encoding and transmitting information is a major goal in neuroscience. This requires insight on the data-rich neuronal spiking patterns combined, ideally, with morphology and genetic identity. Electrophysiologists have long experienced the trade-offs between anatomically-accurate single-cell recording techniques and high-density multi-cellular recording methods with poor anatomical correlations. In this study, we present a novel technique that combines large-scale micro-electrode array recordings with genetic identification and the anatomical location of the retinal ganglion cell soma. This was obtained through optogenetic stimulation and subsequent confocal imaging of genetically targeted retinal ganglion cell sub-populations in the mouse. With the many molecular options available for optogenetic gene expression, we view this method as a versatile tool for matching function to genetic classifications, which can be extended to include morphological information if the density of labelled cells is at the correct level.
了解神经元在编码和传递信息中的作用是神经科学的主要目标。这需要深入了解数据丰富的神经元尖峰模式，理想情况下，还需要结合形态和遗传身份。电生理学家长期以来一直面临着在解剖学上精确的单细胞记录技术和具有较差解剖相关性的高密度多细胞记录方法之间进行权衡取舍。在这项研究中，我们提出了一种新的技术，该技术将大规模微电极阵列记录与遗传鉴定以及视网膜神经节细胞体的解剖位置相结合。这是通过光遗传学刺激和随后对小鼠中遗传靶向视网膜神经节细胞亚群的共聚焦成像获得的。由于光遗传学基因表达有许多分子选择，我们认为这种方法是将功能与遗传分类相匹配的通用工具，如果标记细胞的密度达到正确水平，则可以扩展到包括形态信息。
