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映射爆发性神经元网络的功能连接性。

Mapping functional connectivity of bursting neuronal networks.

作者信息

Nguyen Tuan D, O'Connor Kelly D, Sheth Krishna, Bolle Nick

机构信息

The College of New Jersey, Department of Physics, Ewing, 08628 NJ USA.

出版信息

Appl Netw Sci. 2017;2(1):15. doi: 10.1007/s41109-017-0037-0. Epub 2017 Jun 19.

DOI:10.1007/s41109-017-0037-0
PMID:30443570
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6214252/
Abstract

Using single-cell laser scanning photostimulation (LSPS) combined with broad-field calcium imaging, we measured the functional connectivity of neuronal cultures before and after the developmental appearance of network bursting. From these data, network properties were determined for these relatively large neuronal networks. Based on these properties, we found that although 'small-world' network behavior existed throughout this time period, only average node degree and global efficiency correlate with the development of network bursting while clustering and local efficiency remained relatively constant.

摘要

我们使用单细胞激光扫描光刺激（LSPS）结合宽视野钙成像技术，测量了网络爆发发育出现前后神经元培养物的功能连接性。从这些数据中，确定了这些相对较大神经元网络的网络特性。基于这些特性，我们发现，尽管在整个时间段内都存在“小世界”网络行为，但只有平均节点度和全局效率与网络爆发的发展相关，而聚类系数和局部效率则保持相对恒定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/da100c75dcf5/41109_2017_37_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/fc651bf2f31b/41109_2017_37_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/af4135b7275d/41109_2017_37_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/8795e25fceac/41109_2017_37_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/56cef592ff55/41109_2017_37_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/999805624755/41109_2017_37_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/b8d35704b18d/41109_2017_37_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/da100c75dcf5/41109_2017_37_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/fc651bf2f31b/41109_2017_37_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/af4135b7275d/41109_2017_37_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/8795e25fceac/41109_2017_37_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/56cef592ff55/41109_2017_37_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/999805624755/41109_2017_37_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/b8d35704b18d/41109_2017_37_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f91/6214252/da100c75dcf5/41109_2017_37_Fig7_HTML.jpg

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本文引用的文献

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Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.从神经元培养物钙成像信号的频谱分析中鉴定神经网络特性。
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Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals.
无模型重建钙成像信号中的兴奋性神经元连接
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