Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity.
Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity.
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DOI：
10.3389/fncir.2017.00056
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发表时间：
2017
影响因子：
3.5
通讯作者：
Losert W
中科院分区：
文献类型：
--
作者：
Aghayee S;Winkowski DE;Bowen Z;Marshall EE;Harrington MJ;Kanold PO;Losert W
应用双光子激光扫描显微镜（TPLSM）技术来测量神经元群体中细胞钙信号的动态是表征中枢神经系统内神经活动的一种非常强大的技术。TPLSM在清醒和行为主体上的使用有望对神经回路元件如何协作交互以形成感官知觉和产生行为提供新的见解。在成像这样的准备的一个主要挑战是不可避免的动物和组织的运动，这导致在成像位置（抖动）的变化。图像运动的存在可能导致伪影，特别是因为TPLSM图像的量化涉及分析每个神经元的荧光强度波动，从小的感兴趣区域（ROI）确定。在这里，我们验证了一种新的运动校正方法，以补偿清醒小鼠听觉皮层浅层中TPLSM图像的运动。我们使用名义上均匀的荧光信号作为辅助信号，以补充来自遗传编码的钙指示剂的动态信号。我们测试了单平面延时成像以及多平面（即，体积）皮层组织的时间推移成像。我们的运动校正过程依赖于定位最亮的神经元，并使用已建立的粒子查找和跟踪技术随时间跟踪它们的位置。我们表明，我们的跟踪为基础的方法提供了亚像素分辨率，而不影响速度。与大多数已建立的方法不同，我们的算法还捕获视场的变形，因此可以补偿例如，用于旋转。因此，基于对象跟踪的运动校正提供了一种用于运动校正的替代方法，该方法非常适合于真实的时间尖峰推断分析和反馈控制，以及用于校正组织失真。
The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is unavoidable animal and tissue movement, which leads to shifts in the imaging location (jitter). The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs). Here, we validate a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging as well as multiplane (i.e., volume) time lapse imaging of cortical tissue. Our procedure of motion correction relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. We show that our tracking based approach provides subpixel resolution without compromising speed. Unlike most established methods, our algorithm also captures deformations of the field of view and thus can compensate e.g., for rotations. Object tracking based motion correction thus offers an alternative approach for motion correction, one that is well suited for real time spike inference analysis and feedback control, and for correcting for tissue distortions.
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