Optimal speed estimation in natural image movies predicts human performance
Optimal speed estimation in natural image movies predicts human performance
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DOI：
10.1038/ncomms8900
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发表时间：
2015-08-01
影响因子：
16.6
通讯作者：
Geisler, Wilson S.
中科院分区：
文献类型：
--
作者：
Burge, Johannes;Geisler, Wilson S.
运动的准确感知关键取决于视网膜运动速度的准确估计。在这里，我们首先分析自然图像电影，以确定最佳的时空感受野（RF）编码局部运动速度在一个特定的方向，给定的早期视觉系统的约束。接下来，从对自然刺激的RF响应中，我们确定了最佳的神经计算，用于将响应组合和解码为速度估计。这些计算显示了神经系统是如何构建选择性的、不变的速度调节单元的。然后，在心理物理实验中使用匹配的刺激，我们表明，人类的表现是接近最佳的。事实上，一个单一的效率参数准确地预测了大量的人类心理测量功能的详细形状。我们的结论是，速度选择性神经元和人类速度歧视性能的许多属性预测的最佳计算，自然刺激的变化影响最佳和人类观察员几乎相同。
Accurate perception of motion depends critically on accurate estimation of retinal motion speed. Here we first analyse natural image movies to determine the optimal space-time receptive fields (RFs) for encoding local motion speed in a particular direction, given the constraints of the early visual system. Next, from the RF responses to natural stimuli, we determine the neural computations that are optimal for combining and decoding the responses into estimates of speed. The computations show how selective, invariant speed-tuned units might be constructed by the nervous system. Then, in a psychophysical experiment using matched stimuli, we show that human performance is nearly optimal. Indeed, a single efficiency parameter accurately predicts the detailed shapes of a large set of human psychometric functions. We conclude that many properties of speed-selective neurons and human speed discrimination performance are predicted by the optimal computations, and that natural stimulus variation affects optimal and human observers almost identically.