Background

Ca²⁺-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-electrode arrays or sophisticated imaging. Although such approaches allow detailed network analyses, multi-electrode arrays lack single-cell precision, whereas optical physiology generally requires advanced instrumentation that may not be universally available.

New method

Here we developed a simple, stimulation-free protocol with associated Matlab algorithms that enables scalable analyses of spontaneous network activity in cultured human and mouse neurons. The approach allows analysis of the overall network activity and of single-neuron dynamics, and is amenable to screening purposes.

Results

We validated the new protocol by assessing human neurons with a heterozygous conditional deletion of Munc18-1, and mouse neurons with a homozygous conditional deletion of neurexins. The approach described enabled identification of differential changes in these mutant neurons, allowing quantifications of the synchronous firing rate at the network level and of the amplitude and frequency of Ca²⁺-spikes at the single-neuron level. These results demonstrate the utility of the approach.

Comparision with existing methods

Compared with current imaging platforms, our method is simple, scalable, accessible, and easy to implement. It enables quantification of more detailed parameters than multi-electrode arrays, but does not have the resolution and depth of more sophisticated yet labour-intensive methods, such as patch-clamp electrophysiology.

Conclusion

The method reported here is scalable for a rapid direct assessment of neuronal function in culture, and can be applied to both human and mouse neurons. Thus, the method can serve as a basis for phenotypical analysis of mutations and for drug discovery efforts.

中文翻译：

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一种简单的 Ca2+ 成像方法在培养的神经元中进行神经网络分析

背景

Ca ²⁺成像是测量神经元动力学和网络活动的有力工具。为了监测培养神经元的网络水平变化，神经元活动通常由电或光遗传学刺激诱发，并使用多电极阵列或复杂成像进行评估。尽管此类方法允许进行详细的网络分析，但多电极阵列缺乏单细胞精度，而光学生理学通常需要可能无法普遍使用的先进仪器。

新方法

在这里，我们开发了一个简单、无刺激的协议以及相关的 Matlab 算法，可以对培养的人类和小鼠神经元中的自发网络活动进行可扩展的分析。该方法允许分析整体网络活动和单神经元动力学，并且适合筛选目的。

结果

我们通过评估具有 Munc18-1 杂合条件缺失的人类神经元和具有纯合条件缺失 neurexins 的小鼠神经元来验证新协议。所描述的方法能够识别这些突变神经元中的差异变化，从而可以量化网络级别的同步放电率以及单个神经元级别的 Ca ^{2+峰值的幅度和频率。}这些结果证明了该方法的实用性。

与现有方法的比较

与当前的成像平台相比，我们的方法简单、可扩展、可访问且易于实现。它可以量化比多电极阵列更详细的参数，但不具备更复杂但劳动密集型方法的分辨率和深度，例如膜片钳电生理学。

结论

此处报告的方法可扩展，可用于快速直接评估培养中的神经元功能，并可应用于人类和小鼠神经元。因此，该方法可以作为突变表型分析和药物发现工作的基础。