Lu Z L, Dosher B A
Department of Psychology, University of Southern California, Los Angeles 90089-1061, USA.
J Opt Soc Am A Opt Image Sci Vis. 1999 Mar;16(3):764-78. doi: 10.1364/josaa.16.000764.
A widely used method for characterizing and comparing inefficiencies in perceptual processes is the method of equivalent internal noise--the amount of random internal noise necessary to produce the degree of inefficiency exhibited by the perceptual system in processing [J. Opt. Soc. Am. 46, 634 (1956)]. One normally estimates the amount of equivalent internal noise by systematically increasing the amount of external noise added to the signal stimulus and observing how threshold--signal stimulus energy required for an observer to maintain a given performance level--depends on the amount of external noise. In a variety of perceptual tasks, a simple noisy linear amplifier model [D. Pelli, Ph.D. dissertation (University of Cambridge, Cambridge, UK 1981)] has been utilized to estimate the equivalent internal noise Ninternal by fitting of the relation between threshold contrast c tau and external noise N(ext) at a single (d') performance level: c tau 2 =(d'/beta)2(N(ext)2 + Ninternal2). This model makes a strong prediction: Independent of observer and external noise contrast, the ratio between two thresholds at each external noise level is equal to the ratio of the two corresponding d' values. To our knowledge, this potential test for the internal consistency of the model had never been examined previously. In this study we estimated threshold ratios between multiple performance levels at various external noise contrasts in two different experiments: Gabor orientation identification, and Gabor detection. We found that, in both identification and detection, the observed threshold ratios between different performance levels departed substantially from the d' ratio predicted by the simple noisy linear amplifier model. An elaborated perceptual template model [Vision Res. 38, 1183 (1998)] with nonlinear transducer functions and multiplicative noise in addition to the additive noise in the simple linear amplifier model leads to a substantially better description of the data and suggests a reinterpretation of earlier results that relied on the simple noisy linear amplifier model. The relationship of our model and method to other recent parallel and independent developments [J. Opt. Soc. Am. A 14, 2406 (1997)] is discussed.
一种广泛用于表征和比较感知过程中低效性的方法是等效内部噪声法——即产生感知系统在处理过程中所表现出的低效程度所需的随机内部噪声量[《美国光学学会杂志》46, 634 (1956)]。通常通过系统地增加添加到信号刺激中的外部噪声量,并观察阈值——观察者维持给定性能水平所需的信号刺激能量——如何依赖于外部噪声量,来估计等效内部噪声量。在各种感知任务中,一个简单的噪声线性放大器模型[D. 佩利,博士论文(英国剑桥大学,剑桥,1981)]已被用于通过在单个(d')性能水平上拟合阈值对比度cτ与外部噪声N(ext)之间的关系来估计等效内部噪声Ninternal:cτ2 =(d'/β)2(N(ext)2 + Ninternal2)。该模型做出了一个强有力的预测:与观察者和外部噪声对比度无关,每个外部噪声水平下两个阈值的比值等于两个相应d'值的比值。据我们所知,此前从未对该模型内部一致性的这一潜在测试进行过检验。在本研究中,我们在两个不同的实验——Gabor方向识别和Gabor检测中,估计了各种外部噪声对比度下多个性能水平之间的阈值比值。我们发现,在识别和检测中,不同性能水平之间观察到的阈值比值与简单噪声线性放大器模型预测的d'比值有很大偏差。一个经过完善的感知模板模型[《视觉研究》38, 1183 (1998)],除了简单线性放大器模型中的加性噪声外,还具有非线性换能器函数和乘性噪声,能对数据进行更好得多的描述,并建议对依赖于简单噪声线性放大器模型的早期结果进行重新解释。我们还讨论了我们的模型和方法与其他近期平行且独立发展的成果[《美国光学学会杂志A》14, 2406 (1997)]之间的关系。