Optical-flow analysis toolbox for characterization of spatiotemporal dynamics in mesoscale optical imaging of brain activity
Optical-flow analysis toolbox for characterization of spatiotemporal dynamics in mesoscale optical imaging of brain activity
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DOI：
10.1016/j.neuroimage.2017.03.034
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发表时间：
2017-06-01
期刊：
影响因子：
5.7
通讯作者：
Mohajerani, Majid H.
中科院分区：
文献类型：
--
作者：
Afrashteh, Navvab;Inayat, Samsoon;Mohajerani, Majid H.
广域光学成像技术构成了研究中尺度神经元活动的强大工具。采样数据构成一系列图像帧，在其中可以研究分别在源位置和汇位置开始和终止的大脑活动流。信息流分析的方法包括识别活动源和汇及其轨迹的定性评估，以及基于计算像素强度的时间变化的定量测量。此外，在一些研究中，已经报道了使用计算机视觉的光流技术对波动的估计。然而，仍然缺乏用于中尺度脑活动数据定量分析的综合工具箱。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中尺度大脑活动的时空动力学。该工具箱包括三种光流方法的实现，即 Horn-Schunck、局部-全局组合和时空算法，用于估计中尺度大脑活动流的速度矢量场。根据速度矢量场，我们确定了源和汇的位置以及活动流的轨迹和时间速度。使用模拟数据以及实验得出的小鼠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功效。我们的结果表明，我们采用的局部-全局组合方法可以产生估计波浪运动的最佳结果。自动化方法可以快速有效地量化中尺度大脑动力学，并可能有助于研究大脑功能对新体验或病理的反应。
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.