Testing the odds of inherent vs. observed overdispersion in neural spike counts.

Testing the odds of inherent vs. observed overdispersion in neural spike counts.
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测试神经尖峰计数固有与观察到的过度分散的几率。

DOI:
10.1152/jn.00194.2015
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发表时间:
2016
影响因子:
2.5
通讯作者:
Perrinet,LaurentU
Perrinet,LaurentU
中科院分区:
医学3区
文献类型:
--
作者:
Taouali,Wahiba;Benvenuti,Giacomo;Wallisch,Pascal;Chavane,Frédéric;Perrinet,LaurentU

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在神经元的感受野中重复呈现相同的视觉刺激,可能会在每次试验中引起不同的尖峰模式。概率方法对于理解这种变异在神经活动中的功能作用是必不可少的。在这种情况下,泊松过程是试验之间可变性的最常见模型。对于泊松过程,尖峰计数的方差被约束为等于平均值,而与测量的持续时间无关。大量研究表明,这种关系通常并不成立。具体地说,大多数电生理记录显示出“过度离散”效应:反应表现出比仅从泊松过程中预期的更大的试验间变异性。一个特别适合于量化过度分散的模型是负二项分布模型。这个模型得到了很好的研究和广泛的应用,但直到最近才被应用到神经科学中。在本文中,我们将讨论三个主要问题。首先,我们描述负二项分布如何提供一个易于解释过度分散的尖峰计数的模型。其次,我们通过提出一种统计检验来量化该模型对任何神经生理学数据的重要性,该检验量化了由于重复(试验)次数有限而导致过度分散的几率。我们将这项测试应用于视觉通路沿线的三个神经生理学数据集。最后,我们将该模型与泊松模型在种群解码任务上的性能进行了比较。结果表明,在考虑过色散的情况下,译码精度得到了提高,特别是在调谐过色散的假设下。
The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at each trial. Probabilistic methods are essential to understand the functional role of this variance within the neural activity. In that case, a Poisson process is the most common model of trial-to-trial variability. For a Poisson process, the variance of the spike count is constrained to be equal to the mean, irrespective of the duration of measurements. Numerous studies have shown that this relationship does not generally hold. Specifically, a majority of electrophysiological recordings show an “overdispersion” effect: responses that exhibit more intertrial variability than expected from a Poisson process alone. A model that is particularly well suited to quantify overdispersion is the Negative-Binomial distribution model. This model is well-studied and widely used but has only recently been applied to neuroscience. In this article, we address three main issues. First, we describe how the Negative-Binomial distribution provides a model apt to account for overdispersed spike counts. Second, we quantify the significance of this model for any neurophysiological data by proposing a statistical test, which quantifies the odds that overdispersion could be due to the limited number of repetitions (trials). We apply this test to three neurophysiological data sets along the visual pathway. Finally, we compare the performance of this model to the Poisson model on a population decoding task. We show that the decoding accuracy is improved when accounting for overdispersion, especially under the hypothesis of tuned overdispersion.
受精包膜阻止精子进入非洲爪蟾卵的证据:精子与孤立包膜的相互作用。
DOI: 10.1016/0012-1606(76)90285-2
发表时间: 1976
影响因子: 2.7
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发表时间: 1987
影响因子: 2.7
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影响因子: 2.7
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发表时间: 1980-01-01
期刊: GAMETE RESEARCH
影响因子: --
作者:
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影响因子: 11.1
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