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使用钙成像技术对神经网络和单细胞钙动力学进行自动定量分析。

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging.

作者信息

Patel Tapan P, Man Karen, Firestein Bonnie L, Meaney David F

机构信息

Department of Bioengineering, University of Pennsylvania, United States.

Department of Cell Biology and Neuroscience, Rutgers University, United States.

出版信息

J Neurosci Methods. 2015 Mar 30;243:26-38. doi: 10.1016/j.jneumeth.2015.01.020. Epub 2015 Jan 25.

Abstract

BACKGROUND

Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking.

NEW METHOD

Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge.

RESULTS

We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau.

COMPARISON WITH EXISTING METHOD(S): We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods.

CONCLUSIONS

We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease.

摘要

背景

基因工程钙指示剂和膜电位指示剂的最新进展为估计更大的中尺度网络(100 - 1000多个神经元)内单个神经元的激活动态提供了可能。然而,目前缺乏一个用于从高速荧光成像数据中分析和可视化神经微电路的完全集成的自动化工作流程。

新方法

在此,我们介绍FluoroSNNAP,即荧光单神经元和网络分析软件包。FluoroSNNAP是一款在MATLAB中开发的开源交互式软件,用于自动量化单细胞钙动力学和网络活动模式的众多生物学相关特征。FluoroSNNAP整合并改进了现有的尖峰检测、同步分析和功能连接推理工具,对几乎没有编程知识的实验人员非常有用。

结果

我们应用FluoroSNNAP来表征体外发育成熟过程中神经元微电路的活动模式。另外,我们突出了单细胞分析在对表达微管相关蛋白tau的人类突变变体和野生型tau的混合神经元群体进行表型分析方面的效用。

与现有方法的比较

我们展示了使用时空独立成分分析进行半自动细胞分割的性能,并且与基于峰值或小波的检测方法相比,使用基于模板的算法在检测钙瞬变方面有显著改进。我们的软件还能实现对微电路的自动分析,这是对现有方法的一种改进。

结论

我们预计该软件的传播将有助于对神经元网络进行全面分析,促进对健康和疾病状态下电路的快速研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e760/5553047/94206e07e042/nihms886628f1.jpg

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