Optimal stimulus encoders for natural tasks
Optimal stimulus encoders for natural tasks
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DOI：
10.1167/9.13.17
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发表时间：
2009-01-01
影响因子：
1.8
通讯作者：
Ing, Almon D.
中科院分区：
文献类型：
--
作者：
Geisler, Wilson S.;Najemnik, Jiri;Ing, Almon D.
确定对特定自然任务最有用的自然刺激的特征对于理解感知系统至关重要。描述了一种新的方法，该方法涉及找到感兴趣的自然任务的最佳编码器，给定编码器和解码器之间的噪声“神经元”的相对较小的人口。最佳的编码器，它必须指定最有用的功能，发现通过最大限度地提高精度的自然任务，其中解码器是贝叶斯理想的观察员对人口的反应。该方法被示出用于块识别任务，其中目标是识别自然图像的块，并且用于前景识别任务，其中目标是识别自然表面边界的哪一侧属于前景对象。最佳特征（感受野）是直观的，在两个任务中表现良好。该方法还提供了对神经编码和解码的一般原理的洞察。
Determining the features of natural stimuli that are most useful for specific natural tasks is critical for understanding perceptual systems. A new approach is described that involves finding the optimal encoder for the natural task of interest, given a relatively small population of noisy "neurons" between the encoder and decoder. The optimal encoder, which necessarily specifies the most useful features, is found by maximizing accuracy in the natural task, where the decoder is the Bayesian ideal observer operating on the population responses. The approach is illustrated for a patch identification task, where the goal is to identify patches of natural image, and for a foreground identification task, where the goal is to identify which side of a natural surface boundary belongs to the foreground object. The optimal features (receptive fields) are intuitive and perform well in the two tasks. The approach also provides insight into general principles of neural encoding and decoding.