Calcium Imaging and the Curse of Negativity.
Calcium Imaging and the Curse of Negativity.
复制标题
DOI：
10.3389/fncir.2020.607391
复制
发表时间：
2020
影响因子：
3.5
通讯作者：
Scott EK
中科院分区：
文献类型：
--
作者：
Vanwalleghem G;Constantin L;Scott EK
使用钙指示剂对神经元活动进行成像已经成为现代神经科学的主要内容。然而，如果没有实实在在的事实，就有可能错过很大一部分真实的回应。在这里，我们表明一个共同的假设，即钙指示剂检测到的神经元反应的非负性，对这些数据的频繁使用的分析方法的所有水平都有偏见。从提取有意义的荧光变化到尖峰信号推断和对推断尖峰信号的分析，每一步都有可能因为非负性假设而错过真实的反应。我们首先证明，在神经元活动的钙成像中可以存在与基线的负偏差。然后，我们使用模拟数据测试了三种流行的图像分析算法：CAIMAN、Suite2p和CellSort，发现Suite2p可能最适合大数据集。我们还测试了CAIMAN、Suite2p和Cellsort中包含的棘波推理算法，以及专用的推理算法MLSpike和Casade，发现每个算法在处理受抑制的神经元方面都有局限性。在这些棘波推断算法中，来自CAIMAN的FOOPSI在被抑制的神经元上表现最好，但即使是这个算法也在荧光信号恢复到基线时推断出虚假的棘波。因此，需要新的方法，才能敏感和准确地从受抑制神经元的钙数据中推断出尖峰信号。我们进一步建议避免数据分析方法，通过假设非负性，忽略抑制的反应。相反，我们建议第一个探索性步骤，例如使用k-均值或主成分分析来检测是否存在有意义的负偏差。采取这些步骤将确保在钙成像数据集中检测到抑制和兴奋。
The imaging of neuronal activity using calcium indicators has become a staple of modern neuroscience. However, without ground truths, there is a real risk of missing a significant portion of the real responses. Here, we show that a common assumption, the non-negativity of the neuronal responses as detected by calcium indicators, biases all levels of the frequently used analytical methods for these data. From the extraction of meaningful fluorescence changes to spike inference and the analysis of inferred spikes, each step risks missing real responses because of the assumption of non-negativity. We first show that negative deviations from baseline can exist in calcium imaging of neuronal activity. Then, we use simulated data to test three popular algorithms for image analysis, CaImAn, suite2p, and CellSort, finding that suite2p may be the best suited to large datasets. We also tested the spike inference algorithms included in CaImAn, suite2p, and Cellsort, as well as the dedicated inference algorithms MLspike and CASCADE, and found each to have limitations in dealing with inhibited neurons. Among these spike inference algorithms, FOOPSI, from CaImAn, performed the best on inhibited neurons, but even this algorithm inferred spurious spikes upon the return of the fluorescence signal to baseline. As such, new approaches will be needed before spikes can be sensitively and accurately inferred from calcium data in inhibited neurons. We further suggest avoiding data analysis approaches that, by assuming non-negativity, ignore inhibited responses. Instead, we suggest a first exploratory step, using k-means or PCA for example, to detect whether meaningful negative deviations are present. Taking these steps will ensure that inhibition, as well as excitation, is detected in calcium imaging datasets.
登录
查看更多内容
影响因子：
4.6
作者：
Förster D;Arnold-Ammer I;Laurell E;Barker AJ;Fernandes AM;Finger-Baier K;Filosa A;Helmbrecht TO;Kölsch Y;Kühn E;Robles E;Slanchev K;Thiele TR;Baier H;Kubo F
通讯作者：
Kubo F
影响因子：
16.2
作者：
Heap, Lucy A. L.;Vanwalleghem, Gilles;Scott, Ethan K.
通讯作者：
Scott, Ethan K.
DOI：
10.1126/science.aab0810
发表时间：
2015-12-11
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Gong Y;Huang C;Li JZ;Grewe BF;Zhang Y;Eismann S;Schnitzer MJ
通讯作者：
Schnitzer MJ
影响因子：
48
作者：
Akemann, Walther;Mutoh, Hiroki;Knoepfel, Thomas
通讯作者：
Knoepfel, Thomas
影响因子：
25
作者：
Daviu, Nuria;Fuzesi, Tamas;Bains, Jaideep S.
通讯作者：
Bains, Jaideep S.