Mitani Akinori, Komiyama Takaki
Neurobiology Section, Center for Neural Circuits and Behavior and Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.
Front Neuroinform. 2018 Dec 18;12:98. doi: 10.3389/fninf.2018.00098. eCollection 2018.
Two-photon calcium imaging has been extensively used to record neural activity in the brain. It has been long used solely with analysis, but the recent efforts began to include closed-loop experiments. Closed-loop experiments pose new challenges because they require fast, real-time image processing without iterative parameter tuning. When imaging awake animals, one of the crucial steps of image analysis is correction of lateral motion artifacts. In most of the closed-loop experiments, this step has not been implemented and ignored due to technical difficulties. We recently reported the first experiments with real-time processing of calcium imaging that included lateral motion correction. Here, we report the details of the implementation of fast motion correction and present performance analysis across several algorithms with different parameters. Additionally, we introduce a novel method to estimate baseline calcium signal using kernel density estimate, which reduces the number of parameters to be tuned. Combined, we propose a novel software pipeline of real-time image processing suited for closed-loop experiments. The pipeline is also useful for rapid image processing.
双光子钙成像已被广泛用于记录大脑中的神经活动。长期以来，它仅用于分析，但最近的研究开始包括闭环实验。闭环实验带来了新的挑战，因为它们需要快速、实时的图像处理，且无需迭代参数调整。在对清醒动物进行成像时，图像分析的关键步骤之一是校正横向运动伪影。在大多数闭环实验中，由于技术困难，这一步骤尚未实施且被忽略。我们最近报道了首次进行的钙成像实时处理实验，其中包括横向运动校正。在此，我们报告快速运动校正的实现细节，并针对具有不同参数的几种算法进行性能分析。此外，我们引入了一种使用核密度估计来估计基线钙信号的新方法，该方法减少了需要调整的参数数量。综合起来，我们提出了一种适用于闭环实验的实时图像处理新软件流程。该流程对于快速图像处理也很有用。
