Suppr超能文献

二项迫选对比度辨别中的固定噪声与可变噪声:来自心理测量函数的经验教训

Fixed vs. variable noise in 2AFC contrast discrimination: lessons from psychometric functions.

作者信息

García-Pérez Miguel A, Alcalá-Quintana Rocío

机构信息

Departamento de Metodología, Facultad de Psicología, Universidad Complutense, Campus de Somosaguas, 28223 Madrid, Spain.

出版信息

Spat Vis. 2009;22(4):273-300. doi: 10.1163/156856809788746309.

Abstract

Recent discussion regarding whether the noise that limits 2AFC discrimination performance is fixed or variable has focused either on describing experimental methods that presumably dissociate the effects of response mean and variance or on reanalyzing a published data set with the aim of determining how to solve the question through goodness-of-fit statistics. This paper illustrates that the question cannot be solved by fitting models to data and assessing goodness-of-fit because data on detection and discrimination performance can be indistinguishably fitted by models that assume either type of noise when each is coupled with a convenient form for the transducer function. Thus, success or failure at fitting a transducer model merely illustrates the capability (or lack thereof) of some particular combination of transducer function and variance function to account for the data, but it cannot disclose the nature of the noise. We also comment on some of the issues that have been raised in recent exchange on the topic, namely, the existence of additional constraints for the models, the presence of asymmetric asymptotes, the likelihood of history-dependent noise, and the potential of certain experimental methods to dissociate the effects of response mean and variance.

摘要

最近关于限制二择一迫选辨别性能的噪声是固定的还是可变的讨论,要么集中在描述可能区分反应均值和方差影响的实验方法上,要么集中在重新分析已发表的数据集上,目的是通过拟合优度统计来确定如何解决这个问题。本文表明,通过将模型拟合到数据并评估拟合优度无法解决这个问题,因为当每种噪声与换能器函数的一种方便形式相结合时,关于检测和辨别性能的数据可以由假设任何一种噪声类型的模型进行难以区分的拟合。因此,拟合换能器模型的成功或失败仅仅说明了换能器函数和方差函数的某种特定组合解释数据的能力(或缺乏这种能力),但它无法揭示噪声的本质。我们还评论了最近关于该主题的交流中提出的一些问题,即模型的额外约束的存在、不对称渐近线的存在、历史依赖噪声的可能性以及某些实验方法区分反应均值和方差影响的潜力。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验