Cerebral Physiology Laboratory, Université Paris-Descartes, CNRS, UMR 8118, 45 rue des Saints-Pères, 75006 Paris, France.
Cell Calcium. 2013 Aug;54(2):71-85. doi: 10.1016/j.ceca.2013.04.005. Epub 2013 Jun 18.
Calcium imaging has become a routine technique in neuroscience for subcellular to network level investigations. The fast progresses in the development of new indicators and imaging techniques call for dedicated reliable analysis methods. In particular, efficient and quantitative background fluorescence subtraction routines would be beneficial to most of the calcium imaging research field. A background-subtracted fluorescence transients estimation method that does not require any independent background measurement is therefore developed. This method is based on a fluorescence model fitted to single-trial data using a classical nonlinear regression approach. The model includes an appropriate probabilistic description of the acquisition system's noise leading to accurate confidence intervals on all quantities of interest (background fluorescence, normalized background-subtracted fluorescence time course) when background fluorescence is homogeneous. An automatic procedure detecting background inhomogeneities inside the region of interest is also developed and is shown to be efficient on simulated data. The implementation and performances of the proposed method on experimental recordings from the mouse hypothalamus are presented in details. This method, which applies to both single-cell and bulk-stained tissues recordings, should help improving the statistical comparison of fluorescence calcium signals between experiments and studies.
钙成像技术已经成为神经科学中用于亚细胞到网络水平研究的常规技术。新指示剂和成像技术的快速发展需要专门的可靠分析方法。特别是,高效和定量的背景荧光扣除程序将有益于大多数钙成像研究领域。因此,开发了一种不需要任何独立背景测量的背景扣除荧光瞬变估计方法。该方法基于使用经典非线性回归方法拟合单次试验数据的荧光模型。该模型包括对采集系统噪声的适当概率描述,当背景荧光均匀时,导致对所有感兴趣的量(背景荧光、归一化背景扣除荧光时程)的准确置信区间。还开发了一种自动程序来检测感兴趣区域内的背景非均匀性,并且在模拟数据上表现出高效性。详细介绍了该方法在小鼠下丘脑的实验记录中的实现和性能。该方法适用于单细胞和整体染色组织的记录,应该有助于提高实验和研究之间荧光钙信号的统计学比较。