Modeling visual performance differences "around' the visual field: A computational observer approach
Modeling visual performance differences "around' the visual field: A computational observer approach
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DOI：
10.1371/journal.pcbi.1007063
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发表时间：
2019-05-01
影响因子：
4.3
通讯作者：
Winawer, Jonathan
中科院分区：
文献类型：
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作者：
Kupers, Eline R.;Carrasco, Marisa;Winawer, Jonathan
即使偏心率保持恒定，视觉性能也取决于极角；在许多心理物理任务中，当刺激出现在水平子午线上时，观察者表现最好，在上垂直子午线上表现最差，在下垂直子午线上表现中等。视野周围的这种性能变化与刺激偏心率加倍时的变化一样明显。这些性能不对称的原因在很大程度上尚不清楚。眼睛的一些因素，例如锥体密度与所报告的视觉性能随极角的变化呈正相关。然而，问题仍然是这些相关性是否可以定量解释在视野周围观察到的感知差异。为了研究视觉的最早阶段（光学质量和视锥密度）对极角性能差异的影响程度，我们创建了一个计算观察者模型。该模型使用开源软件包ISETBIO来模拟视觉性能随极角而变化的方向辨别任务。该模型从显示器发射的光子开始，这些光子通过具有固定眼球运动的模拟人类光学系统，然后在视网膜中发生锥体异构化。最后，我们使用支持向量机对刺激方向进行分类，以学习光子吸收的线性分类器。为了解释与水平子午线相比，上部垂直线的对比度阈值增加了 30%（正如在同一任务中心理物理学所观察到的那样），我们的计算观察者模型需要增加大约 7 个散焦屈光度，或者将视锥细胞密度减少 500%。这些值远远超过了人眼观察到的作为极角函数的实际变化。因此，我们得出结论，眼睛中的这些因素仅占极角视觉性能差异的一小部分。在后来的视网膜和/或皮质处理中必定会出现大量额外的不对称性。 作者摘要 计算神经科学的一个基本目标是将生物学中的已知事实与行为联系起来。在这里，我们考虑了视觉行为，特别是与在相同距离的注视中心上方或下方相比，人们更擅长在注视中心左侧或右侧执行视觉任务。我们试图了解生物学的哪些方面控制着视觉行为的这种基本模式。为此，我们实现了一个计算观察者模型，该模型结合了有关人类视觉系统前端的已知事实，包括光学、眼球运动和视网膜中的感光器阵列。我们发现，尽管其中一些属性与性能相关，但它们远远无法对其进行定量解释。我们得出的结论是，神经系统处理的后期阶段极大地放大了眼睛采样视觉世界的方式的微小差异，从而导致视野周围的表现显着不同。
Visual performance depends on polar angle, even when eccentricity is held constant; on many psychophysical tasks observers perform best when stimuli are presented on the horizontal meridian, worst on the upper vertical, and intermediate on the lower vertical meridian. This variation in performance around' the visual field can be as pronounced as that of doubling the stimulus eccentricity. The causes of these asymmetries in performance are largely unknown. Some factors in the eye, e.g. cone density, are positively correlated with the reported variations in visual performance with polar angle. However, the question remains whether these correlations can quantitatively explain the perceptual differences observed around' the visual field. To investigate the extent to which the earliest stages of vision-optical quality and cone density-contribute to performance differences with polar angle, we created a computational observer model. The model uses the open-source software package ISETBIO to simulate an orientation discrimination task for which visual performance differs with polar angle. The model starts from the photons emitted by a display, which pass through simulated human optics with fixational eye movements, followed by cone isomerizations in the retina. Finally, we classify stimulus orientation using a support vector machine to learn a linear classifier on the photon absorptions. To account for the 30% increase in contrast thresholds for upper vertical compared to horizontal meridian, as observed psychophysically on the same task, our computational observer model would require either an increase of similar to 7 diopters of defocus or a reduction of 500% in cone density. These values far exceed the actual variations as a function of polar angle observed in human eyes. Therefore, we conclude that these factors in the eye only account for a small fraction of differences in visual performance with polar angle. Substantial additional asymmetries must arise in later retinal and/or cortical processing.Author summary A fundamental goal in computational neuroscience is to link known facts from biology with behavior. Here, we considered visual behavior, specifically the fact that people are better at visual tasks performed to the left or right of the center of gaze, compared to above or below at the same distance from gaze. We sought to understand what aspects of biology govern this fundamental pattern in visual behavior. To do so, we implemented a computational observer model that incorporates known facts about the front end of the human visual system, including optics, eye movements, and the photoreceptor array in the retina. We found that even though some of these properties are correlated with performance, they fall far short of quantitatively explaining it. We conclude that later stages of processing in the nervous system greatly amplify small differences in the way the eye samples the visual world, resulting in strikingly different performance around the visual field.