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An evidence accumulation model of perceptual discrimination with naturalistic stimuli.
Journal of Experimental Psychology: Applied ( IF 2.813 ) Pub Date : 2020-05-07 , DOI: 10.1037/xap0000272
Hector Palada 1 , Rachel A Searston 2 , Annabel Persson 1 , Timothy Ballard 1 , Matthew B Thompson 3
Affiliation  

Evidence accumulation models have been used to describe the cognitive processes underlying performance in tasks involving 2-choice decisions about unidimensional stimuli, such as motion or orientation. Given the multidimensionality of natural stimuli, however, we might expect qualitatively different patterns of evidence accumulation in more applied perceptual tasks. One domain that relies heavily on human decisions about complex natural stimuli is fingerprint discrimination. We know little about the ability of evidence accumulation models to account for the dynamic decision process of a fingerprint examiner resolving if 2 different prints belong to the same finger or different fingers. Here, we apply a dynamic decision-making model-the linear ballistic accumulator (LBA)-to fingerprint discrimination decisions to gain insight into the cognitive processes underlying these complex perceptual judgments. Across 3 experiments, we show that the LBA provides an accurate description of the fingerprint discrimination decision process with manipulations in visual noise, speed-accuracy emphasis, and training. Our results demonstrate that the LBA is a promising model for furthering our understanding of applied decision-making with naturally varying visual stimuli. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译:

具有自然刺激的知觉辨别证据积累模型。

证据积累模型已被用于描述在涉及关于一维刺激(例如运动或方向)的 2 选择决策的任务中表现的认知过程。然而,考虑到自然刺激的多维性,我们可能会期望在更多应用的感知任务中出现质量上不同的证据积累模式。一个严重依赖人类对复杂自然刺激做出决定的领域是指纹识别。我们对证据积累模型解释指纹检查员的动态决策过程的能力知之甚少,以确定 2 个不同的指纹是属于同一手指还是不同手指。这里,我们将动态决策模型——线性弹道累加器 (LBA)——应用于指纹识别决策,以深入了解这些复杂感知判断背后的认知过程。在 3 个实验中,我们表明 LBA 提供了对指纹识别决策过程的准确描述,其中包括视觉噪声、速度精度强调和训练方面的操作。我们的结果表明,LBA 是一种很有前景的模型,可以进一步加深我们对具有自然变化的视觉刺激的应用决策的理解。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。速度精度的强调和训练。我们的结果表明,LBA 是一种很有前景的模型,可以进一步加深我们对具有自然变化的视觉刺激的应用决策的理解。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。速度精度的强调和训练。我们的结果表明,LBA 是一种很有前景的模型,可以进一步加深我们对具有自然变化的视觉刺激的应用决策的理解。(PsycInfo 数据库记录 (c) 2020 APA,保留所有权利)。
更新日期:2020-05-07
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