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A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging

机译：用于双光子钙成像的快速，准确的峰值检测的有限创新算法

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摘要

Objective. Inferring the times of sequences of action potentials (APs) (spike trains) from neurophysiological data is a key problem in computational neuroscience. The detection of APs from two-photon imaging of calcium signals offers certain advantages over traditional electrophysiological approaches, as up to thousands of spatially and immunohistochemically defined neurons can be recorded simultaneously. However, due to noise, dye buffering and the limited sampling rates in common microscopy configurations, accurate detection of APs from calcium time series has proved to be a difficult problem. Approach. Here we introduce a novel approach to the problem making use of finite rate of innovation (FRI) theory (Vetterli et al 2002 IEEE Trans. Signal Process. 50 1417-28). For calcium transients well fit by a single exponential, the problem is reduced to reconstructing a stream of decaying exponentials. Signals made of a combination of exponentially decaying functions with different onset times are a subclass of FRI signals, for which much theory has recently been developed by the signal processing community. Main results. We demonstrate for the first time the use of FRI theory to retrieve the timing of APs from calcium transient time series. The final algorithm is fast, non-iterative and parallelizable. Spike inference can be performed in real-time for a population of neurons and does not require any training phase or learning to initialize parameters. Significance. The algorithm has been tested with both real data (obtained by simultaneous electrophysiology and multiphoton imaging of calcium signals in cerebellar Purkinje cell dendrites), and surrogate data, and outperforms several recently proposed methods for spike train inference from calcium imaging data.
机译：目的。从神经生理学数据推断动作电位（AP）（尖峰序列）序列的时间是计算神经科学中的关键问题。与传统的电生理方法相比，通过双光子钙信号成像检测AP具有某些优势，因为可以同时记录数千个空间和免疫组织化学定义的神经元。但是，由于噪声，染料缓冲作用和普通显微镜配置中有限的采样率，从钙时间序列中准确检测AP已被证明是一个难题。方法。在这里，我们介绍一种利用有限创新率（FRI）理论解决问题的新颖方法（Vetterli等人，2002 IEEE Trans。Signal Process。50 1417-28）。对于通过单个指数非常适合的钙瞬态，该问题被简化为重建衰减指数流。由具有不同开始时间的指数衰减函数的组合构成的信号是FRI信号的子类，信号处理社区最近已针对其开发了许多理论。主要结果。我们首次证明了使用FRI理论从钙瞬态时间序列中检索AP的时间。最终算法是快速，非迭代和可并行化的。峰值推断可以针对大量神经元实时执行，不需要任何训练阶段或学习初始化参数。意义。该算法已通过真实数据（通过小脑浦肯野细胞树突中钙信号的同时电生理学和多光子成像获得）和替代数据进行了测试，并且优于其他最近提出的从钙成像数据推断出穗序列的方法。

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  • 来源
    《Journal of neural engineering》 |2013年第4期|046017.1-046017.14|共14页
  • 作者

    Jon Onativia; Simon R Schultz; Pier Luigi Dragotti;

  • 作者单位

    Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK;

    Department of Bioengineering, Imperial College London, South Kensington, London SW7 2AZ, UK;

    Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK;

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