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一眼就能认出突触。

Knowing a synapse when you see one.

作者信息

Burette Alain, Collman Forrest, Micheva Kristina D, Smith Stephen J, Weinberg Richard J

机构信息

Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill Chapel Hill, NC, USA.

Allen Institute for Brain Science Seattle, WA, USA.

出版信息

Front Neuroanat. 2015 Jul 28;9:100. doi: 10.3389/fnana.2015.00100. eCollection 2015.

Abstract

Recent years have seen a rapidly growing recognition of the complexity and diversity of the myriad individual synaptic connections that define brain synaptic networks. It has also become increasingly apparent that the synapses themselves are a major key to understanding the development, function and adaptability of those synaptic networks. In spite of this growing appreciation, the molecular, structural and functional characteristics of individual synapses and the patterning of their diverse characteristics across functional networks have largely eluded quantitative study with available imaging technologies. Here we offer an overview of new computational imaging methods that promise to bring single-synapse analysis of synaptic networks to the fore. We focus especially on the challenges and opportunities associated with quantitative detection of individual synapses and with measuring individual synapses across network scale populations in mammalian brain.

摘要

近年来,人们越来越迅速地认识到,构成大脑突触网络的无数个突触连接具有复杂性和多样性。同样日益明显的是,突触本身是理解这些突触网络的发育、功能和适应性的关键所在。尽管人们对此的认识不断加深,但利用现有成像技术对单个突触的分子、结构和功能特征及其在功能网络中的多样特征模式进行定量研究,在很大程度上仍难以实现。在此,我们概述了有望将突触网络的单突触分析推向前沿的新计算成像方法。我们特别关注与单个突触的定量检测以及在哺乳动物大脑的网络规模群体中测量单个突触相关的挑战和机遇。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44a0/4517447/d1ce46942d25/fnana-09-00100-g0001.jpg

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