Bayesian binning beats approximate alternatives: estimating peristimulus time histograms

机译：贝叶斯装箱节拍的近似选择：估计刺激时间直方图

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The peristimulus time histogram (PSTH) and its more continuous cousin, the spike density function (SDF) are staples in the analytic toolkit of neurophysiol-ogists. The former is usually obtained by binning spike trains, whereas the standard method for the latter is smoothing with a Gaussian kernel. Selection of a bin width or a kernel size is often done in an relatively arbitrary fashion, even though there have been recent attempts to remedy this situation [1, 2]. We develop an exact Bayesian, generative model approach to estimating PSTHs and demonstate its superiority to competing methods. Further advantages of our scheme include automatic complexity control and error bars on its predictions.

机译：刺激周围时间直方图（PSTH）及其更连续的表亲，峰密度函数（SDF）是神经生理学家分析工具包中的主要内容。前者通常是通过对峰值序列进行分档获得的，而后者的标准方法是使用高斯核进行平滑。尽管最近有尝试纠正这种情况的方法，但是通常以相对任意的方式选择bin宽度或内核大小。我们开发了一种精确的贝叶斯生成模型方法来估算PSTH，并证明了其在竞争方法中的优越性。我们方案的其他优点包括自动复杂性控制和预测中的误差条。

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《Annual Conference on Neural Information Processing Systems》|2007年|153-160|共8页
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Dominik Endres; Mike Oram; Johannes Schindelin; Peter Foeldiak;
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中图分类信息处理（信息加工）;
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入库时间 2022-08-26 14:56:36

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3. Peristimulus time histograms (PSTHs) - a marker for upper motor neuron involvement in ALS? [J] . Markus Weber, Andrew Eisen Amyotrophic lateral sclerosis and other motor neuron disorders: Official publication of the World Federation of Neurology, Research Group on Motor Neuron Diseases . 2000,第Suppla2期

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Bayesian binning beats approximate alternatives: estimating peristimulus time histograms

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