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首页> 外文期刊>Journal of Neurophysiology >Two-Photon Processor and SeNeCA: A freely available software package to process data from two-photon calcium imaging at speeds down to several milliseconds per frame
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Two-Photon Processor and SeNeCA: A freely available software package to process data from two-photon calcium imaging at speeds down to several milliseconds per frame

机译:双光子处理器和SeNeCA:免费提供的软件包,用于处理双光子钙成像中的数据,每帧速度可降低至几毫秒

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摘要

Two-Photon Processor (TPP) is a versatile, ready-to-use, and freely available software package in MATLAB to process data from in vivo two-photon calcium imaging. TPP includes routines to search for cell bodies in full-frame (Search for Neural Cells Accelerated; SeNeCA) and line-scan acquisition, routines for calcium signal calculations, filtering, spike-mining, and routines to construct parametric fields. Searching for somata in artificial in vivo data, our algorithm achieved better performance than human annotators. SeNeCA copes well with uneven background brightness and in-plane motion artifacts, the major problems in simple segmentation methods. In the fast mode, artificial in vivo images with a resolution of 256 × 256 pixels containing ~100 neurons can be processed at a rate up to 175 frames per second (tested on Intel i7, 8 threads, magnetic hard disk drive). This speed of a segmentation algorithm could bring new possibilities into the field of in vivo optophysiology. With such a short latency (down to 5-6 ms on an ordinary personal computer) and using some contemporary optogenetic tools, it will allow experiments in which a control program can continuously evaluate the occurrence of a particular spatial pattern of activity (a possible correlate of memory or cognition) and subsequently inhibit/stimulate the entire area of the circuit or inhibit/stimulate a different part of the neuronal system. TPP will be freely available on our public web site. Similar all-in-one and freely available software has not yet been published.
机译:双光子处理器(TPP)是MATLAB中的一种通用,立即可用且免费提供的软件包,用于处理来自体内双光子钙成像的数据。 TPP包括在全帧中搜索细胞体的例程(“搜索加速的神经细胞”; SeNeCA)和线扫描采集,用于钙信号计算的例程,过滤,尖峰挖掘以及用于构建参数场的例程。在人工体内数据中搜索躯体,我们的算法取得了比人类注释者更好的性能。 SeNeCA很好地解决了背景亮度不均匀和面内运动伪影的问题,这是简单分割方法中的主要问题。在快速模式下,可以以高达175帧/秒的速度处理分辨率为256×256像素的人造体内图像,其中包含约100个神经元(在Intel i7、8线程,磁性硬盘驱动器上测试)。分割算法的这种速度可能为体内光生理学领域带来新的可能性。如此短的等待时间(在普通个人计算机上为5-6毫秒),并使用一些当代的光遗传学工具,它将允许实验,其中控制程序可以连续评估活动的特定空间模式的发生(可能的相关性(记忆力或认知力),然后抑制/刺激电路的整个区域,或抑制/刺激神经系统的不同部分。 TPP将在我们的公共网站上免费提供。相似的多合一且免费提供的软件尚未发布。

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