Is the Homunculus "Aware" of Sensory Adaptation?
Is the Homunculus "Aware" of Sensory Adaptation?
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DOI：
10.1162/neco.2009.09-08-869
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发表时间：
2009-12-01
影响因子：
2.9
通讯作者：
Simoncelli, Eero P.
中科院分区：
文献类型：
--
作者：
Series, Peggy;Stocker, Alan A.;Simoncelli, Eero P.
神经活动和知觉都受到感觉历史的影响。这里介绍的工作探讨了适应的生理效应和它们的感知后果之间的关系。感知被建模为产生于编码器-解码器级联，其中编码器由神经元群体的概率响应定义，并且解码器将该群体活动转换为感知估计。自适应假设产生的变化在编码器中，我们研究的条件下，解码器的行为是一致的观察到的感知效果的偏见和可辨别性。我们表明，对于所有的解码器，辨别力是有界的从下面的逆Fisher信息。另一方面，估计偏差可能由于各种不同的原因而产生，范围可以从零到很大。我们专门研究了当解码器固定时出现的偏差，“不知道”编码群体的变化（与“知道”适应并相应地改变相反）。我们模拟两个良好的研究感官属性，运动方向和对比度的适应的影响，假设编码器适应的增益变化描述。虽然我们不能唯一地约束解码器偏差的来源，我们发现运动和对比度，一个“不知道”的解码器，最大限度地提高了预适应编码器给出的预测的可能性，导致预测与行为数据是一致的。这个模型意味着，自适应引起的偏见出现的解码器的临时次优的结果。
Neural activity and perception are both affected by sensory history. The work presented here explores the relationship between the physiological effects of adaptation and their perceptual consequences. Perception is modeled as arising from an encoder-decoder cascade, in which the encoder is defined by the probabilistic response of a population of neurons, and the decoder transforms this population activity into a perceptual estimate. Adaptation is assumed to produce changes in the encoder, and we examine the conditions under which the decoder behavior is consistent with observed perceptual effects in terms of both bias and discriminability. We show that for all decoders, discriminability is bounded from below by the inverse Fisher information. Estimation bias, on the other hand, can arise for a variety of different reasons and can range from zero to substantial. We specifically examine biases that arise when the decoder is fixed, "unaware" of the changes in the encoding population (as opposed to "aware" of the adaptation and changing accordingly). We simulate the effects of adaptation on two well-studied sensory attributes, motion direction and contrast, assuming a gain change description of encoder adaptation. Although we cannot uniquely constrain the source of decoder bias, we find for both motion and contrast that an "unaware" decoder that maximizes the likelihood of the percept given by the preadaptation encoder leads to predictions that are consistent with behavioral data. This model implies that adaptation-induced biases arise as a result of temporary suboptimality of the decoder.