Toward reliable measurements of perceptual scales in multiple contexts
Toward reliable measurements of perceptual scales in multiple contexts
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DOI：
10.1167/jov.20.4.19
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发表时间：
2020-04-01
影响因子：
1.8
通讯作者：
Maertens, Marianne
中科院分区：
文献类型：
--
作者：
Aguilar, Guillermo;Maertens, Marianne
心理物理学研究的一个核心问题是刺激之间的感知差异如何转化为物理差异，反之亦然。描述这样的心理物理量表将揭示刺激是如何转化为感知事件的，特别是在观看条件（如照明）变化的情况下。存在各种方法来获得感知尺度，但在实践中，尺度估计往往被评估外观匹配所绕过。然而，匹配只能反映潜在的感知尺度，而不能直接揭示它们。最近发展的两种方法，MLDS（最大似然差异尺度）和MLCM（最大似然联合测量），有望可靠地估计感知尺度。在这里，我们比较了两种方法在他们的能力估计感知尺度跨上下文变化在亮度感知领域。在模拟中，我们采用亮度常数、对比度和基于亮度的观察者模型来生成感知尺度的差异模式。MLCM正确恢复了所有模型。MLDS只正确地恢复了亮度常数观测器模型。我们还用两种类型的刺激对这两种方法进行了实证探索：(a)支持亮度恒定的杂色棋盘和(b)不支持亮度恒定的中心环绕刺激。与模拟结果一致，MLDS和MLCM在第一种情况下提供了相似的规模估计，而在第二种情况下提供了不同的估计。此外，来自mlcm的量表——而不是来自mlcm的量表——准确地预测了两种刺激的不对称匹配。将实验和模拟结果结合起来，MLCM似乎更倾向于提供一种有效的感知尺度估计，这种感知尺度是跨观看条件下亮度判断的基础。
A central question in psychophysical research is how perceptual differences between stimuli translate into physical differences and vice versa. Characterizing such a psychophysical scale would reveal how a stimulus is converted into a perceptual event, particularly under changes in viewing conditions (e.g., illumination). Various methods exist to derive perceptual scales, but in practice, scale estimation is often bypassed by assessing appearance matches. Matches, however, only reflect the underlying perceptual scales but do not reveal them directly. Two recently developed methods, MLDS (Maximum Likelihood Difference Scaling) and MLCM (Maximum Likelihood Conjoint Measurement), promise to reliably estimate perceptual scales. Here we compared both methods in their ability to estimate perceptual scales across context changes in the domain of lightness perception. In simulations, we adopted a lightness constant, a contrast, and a luminance-based observer model to generate differential patterns of perceptual scales. MLCM correctly recovered all models. MLDS correctly recovered only the lightness constant observer model. We also empirically probed both methods with two types of stimuli: (a) variegated checkerboards that support lightness constancy and (b) center-surround stimuli that do not support lightness constancy. Consistent with the simulations, MLDS and MLCM provided similar scale estimates in the first case and divergent estimates in the second. In addition, scales from MLCM-and not from MLDS-accurately predicted asymmetric matches for both types of stimuli. Taking experimental and simulation results together, MLCM seems more apt to provide a valid estimate of the perceptual scales underlying judgments of lightness across viewing conditions.