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首页> 外文期刊>Journal of Computational Neuroscience >Effects of stimulus transformations on estimates of sensory neuron selectivity
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Effects of stimulus transformations on estimates of sensory neuron selectivity

机译：刺激转换对感觉神经元选择性估计的影响

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摘要

Stimulus selectivity of sensory systems is often characterized by analyzing response-conditioned stimulus ensembles. However, in many cases these response-triggered stimulus sets have structure that is more complex than as-sumed. If not taken into account, when present it will bias the estimates of many simple statistics, and distort the estimated stimulus selectivity of a neural sensory system. We present an approach that mitigates these problems by modeling some of the response-conditioned stimulus structure as being generated by a set of transformations acting on a simple stimulus distribution. This approach corrects the estimates of key statistics and counters biases introduced by the transformations. In cases involving temporal spike jitter or spatial jitter of images, the main observed effects of transformations are blurring of the conditional mean and introduction of artefacts in the spectral decomposition of the conditional covariance matrix. We illustrate this approach by analyzing and correcting a set of model stimuli perturbed by temporal and spatial jitter. We apply the approach to neuro-physiological data from the cricket cereal sensory system to correct the effects of temporal jitter.
机译：感觉系统的刺激选择性通常通过分析响应条件的刺激集合来表征。但是，在许多情况下，这些由响应触发的刺激集的结构比假定的要复杂。如果不考虑的话，当存在时，它将使许多简单统计的估计值产生偏差，并使神经感觉系统的估计刺激选择性失真。我们提出了一种通过对一些响应条件的刺激结构进行建模来减轻这些问题的方法，这些结构是由一组作用于简单刺激分布的转换生成的。这种方法纠正了关键统计数据的估计，并抵消了转换带来的偏差。在涉及图像的时间尖峰抖动或空间抖动的情况下，观察到的主要变换效果是条件均值模糊以及在条件协方差矩阵的频谱分解中引入伪影。我们通过分析和校正一组受时空抖动扰动的模型刺激来说明这种方法。我们将这种方法应用于板球谷物感觉系统的神经生理数据，以纠正时间抖动的影响。

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