Canadian Center for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Canada T1K 3M4.
Canadian Center for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Canada T1K 3M4.
Neuroimage. 2017 Jun;153:58-74. doi: 10.1016/j.neuroimage.2017.03.034. Epub 2017 Mar 25.
Wide-field optical imaging techniques constitute powerful tools to investigate mesoscale neuronal activity. The sampled data constitutes a sequence of image frames in which one can investigate the flow of brain activity starting and terminating at source and sink locations respectively. Approaches to the analyses of information flow include qualitative assessment to identify sources and sinks of activity as well as their trajectories, and quantitative measurements based on computing the temporal variation of the intensity of pixels. Furthermore, in a few studies estimates of wave motion have been reported using optical-flow techniques from computer vision. However, a comprehensive toolbox for the quantitative analyses of mesoscale brain activity data is still lacking. We present a graphical-user-interface toolbox based in Matlab® for investigating the spatiotemporal dynamics of mesoscale brain activity using optical-flow analyses. The toolbox includes the implementation of three optical-flow methods namely Horn-Schunck, Combined Local-Global, and Temporospatial algorithms for estimating velocity vector fields of flow of mesoscale brain activity. From the velocity vector fields we determined the locations of sources and sinks as well as the trajectories and temporal velocities of flow of activity. Using simulated data as well as experimentally derived sensory-evoked voltage and calcium imaging data from mice, we compared the efficacy of the three optical-flow methods for determining spatiotemporal dynamics. Our results indicate that the combined local-global method we employed, yields the best results for estimating wave motion. The automated approach permits rapid and effective quantification of mesoscale brain dynamics and may facilitate the study of brain function in response to new experiences or pathology.
宽场光学成像技术是研究介观神经元活动的有力工具。采样数据构成了一系列图像帧，可以从中研究分别从源和汇起始和终止的脑活动流。信息流分析的方法包括定性评估以识别活动的源和汇及其轨迹，以及基于计算像素强度的时间变化进行定量测量。此外，在一些研究中，已经使用计算机视觉中的光流技术报告了波运动的估计。然而，用于定量分析介观脑活动数据的综合工具包仍然缺乏。我们提出了一个基于 Matlab®的图形用户界面工具箱，用于使用光流分析研究介观脑活动的时空动力学。该工具箱包括 Horn-Schunck、联合局部-全局和时空算法的实现，用于估计介观脑活动流动的速度矢量场。从速度矢量场中，我们确定了源和汇的位置以及活动流的轨迹和时间速度。使用模拟数据以及从小鼠中得出的实验性感觉诱发电压和钙成像数据，我们比较了三种光流方法确定时空动力学的效果。我们的结果表明，我们使用的联合局部-全局方法在估计波运动方面产生了最佳结果。自动化方法允许快速有效地量化介观脑动力学，并可能促进对新经验或病理学反应的大脑功能的研究。
