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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:可自由的软件包,以处理从两光子钙成像以每帧的速度下降到几毫秒的数据

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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中的多功能,即用的和自由可用的软件包,以在体内两光核钙成像中处理数据。 TPP包括用于在全帧中搜索小区体的例程(搜索神经单元加速;塞内卡)和线路扫描采集,钙信号计算的例程,滤波,尖峰挖掘以及构建参数场的例程。在体内数据中搜索Somata,我们的算法比人类注释者实现了更好的性能。塞内卡与不均匀的背景亮度和面内运动伪影保持良好,是简单分割方法的主要问题。在快速模式中,具有256×256像素的分辨率的Vivo图像中的体内图像可以以高达175帧的速率处理(在英特尔I7,8线,磁性硬盘驱动器上测试)。这种分割算法的这种速度可以将新的可能性带入体内optophysophysoology的领域。通过如此短的延迟(普通个人计算机上的5-6毫秒)并使用一些现代的致光学工具,它将允许实验,其中控制程序可以连续地评估特定空间活动的发生(可能的相关性记忆或认知)并随后抑制/刺激电路的整个区域或抑制/刺激神经元系统的不同部分。 TPP将在我们的公共网站上自由提供。尚未发布类似的一体化和自由的软件。

著录项

  • 来源
    《Journal of Neurophysiology》 |2013年第1期|共14页
  • 作者

    TomekJ.; NovakO.; SykaJ.;

  • 作者单位

    Department of Auditory Neuroscience Institute of Experimental Medicine Academy of Sciences of the;

    Department of Auditory Neuroscience Institute of Experimental Medicine Academy of Sciences of the;

    Department of Auditory Neuroscience Institute of Experimental Medicine Academy of Sciences of the;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人体生理学;
  • 关键词

    Algorithm; Calcium imaging; Processing; Segmentation;

    机译:算法;钙成像;处理;分割;

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