Comparing models of contrast gain using psychophysical experiments
Comparing models of contrast gain using psychophysical experiments
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DOI：
10.1167/16.9.1
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发表时间：
2016-07-01
影响因子：
1.8
通讯作者：
DiMattina, Christopher
中科院分区：
文献类型：
--
作者：
DiMattina, Christopher
在各种神经系统中，调整到感兴趣的主要维度的神经元通常会产生由刺激强度或对比度等其他特征以乘法方式调节的反应。在这项方法学研究中，我们展示了可以使用心理物理学实验来比较神经群体中乘法增益调制的竞争假设，并使用方向调整视觉神经元中对比增益调制的具体示例。我们证明，将生物学可解释的模型与心理物理学数据进行拟合可以产生对比度调整参数的生理学准确估计，并使我们能够比较对比度调整的竞争假设。我们展示了一种使用自适应生成的心理物理刺激来比较竞争性神经模型的强大方法，并证明这种刺激对于区分性质相似的假设非常有效。我们将我们的工作与不断增长的文献联系起来，这些文献使用神经模型与行为数据的拟合来深入了解神经编码并为未来的研究提出方向。
In a wide variety of neural systems, neurons tuned to a primary dimension of interest often have responses that are modulated in a multiplicative manner by other features such as stimulus intensity or contrast. In this methodological study, we present a demonstration that it is possible to use psychophysical experiments to compare competing hypotheses of multiplicative gain modulation in a neural population, using the specific example of contrast gain modulation in orientation-tuned visual neurons. We demonstrate that fitting biologically interpretable models to psychophysical data yields physiologically accurate estimates of contrast tuning parameters and allows us to compare competing hypotheses of contrast tuning. We demonstrate a powerful methodology for comparing competing neural models using adaptively generated psychophysical stimuli and demonstrate that such stimuli can be highly effective for distinguishing qualitatively similar hypotheses. We relate our work to the growing body of literature that uses fits of neural models to behavioral data to gain insight into neural coding and suggest directions for future research.