Department of Neurobiology, Duke University Medical Center, Duke University, Durham, NC 27710, USA.
Department of Electrical and Computer Engineering, Duke University, Durham, NC 27710, USA.
Cell Rep. 2018 Jun 19;23(12):3673-3684. doi: 10.1016/j.celrep.2018.05.062.
In vivo calcium imaging using a 1-photon-based miniscope and a microendoscopic lens enables studies of neural activities in freely behaving animals. However, the high and fluctuating background, the inevitable movements and distortions of imaging field, and the extensive spatial overlaps of fluorescent signals emitted from imaged neurons inherent in this 1-photon imaging method present major challenges for extracting neuronal signals reliably and automatically from the raw imaging data. Here, we develop a unifying algorithm called the miniscope 1-photon imaging pipeline (MIN1PIPE), which contains several stand-alone modules and can handle a wide range of imaging conditions and qualities with minimal parameter tuning and automatically and accurately isolate spatially localized neural signals. We have quantitatively compared MIN1PIPE with other existing partial methods using both synthetic and real datasets obtained from different animal models and show that MIN1PIPE has superior efficiency and precision in analyzing noisy miniscope calcium imaging data.
基于单光子的微型显微镜和微内窥镜镜头的活体钙成像技术可用于研究自由活动动物的神经活动。然而,这种单光子成像方法存在固有问题,如高且波动的背景、成像视野不可避免的运动和变形,以及成像神经元发出的荧光信号的广泛空间重叠,这些都对从原始成像数据中可靠且自动地提取神经元信号提出了重大挑战。在这里,我们开发了一种称为微型显微镜单光子成像管道(MIN1PIPE)的统一算法,它包含几个独立的模块,可以在最小参数调整的情况下处理广泛的成像条件和质量,并自动且准确地分离空间局部化的神经信号。我们使用来自不同动物模型的合成和真实数据集,对 MIN1PIPE 与其他现有部分方法进行了定量比较,结果表明 MIN1PIPE 在分析噪声较大的微型显微镜钙成像数据方面具有更高的效率和精度。