Wade Alex R, Baker Daniel H
Department of Psychology and York Biomedical Research Institute, University of York, UK.
Vision Res. 2025 Jun;231:108614. doi: 10.1016/j.visres.2025.108614. Epub 2025 May 2.
Contrast is the currency of the early visual system. Measuring the way that the computations underlying contrast processing depend on factors such as spatial and temporal frequency, age, clinical conditions, eccentricity, chromaticity and the presence of other stimuli has been a focus of vision science for over a century. One of the most productive experimental approaches in this field has been the use of the 'steady-state visually-evoked potential' (SSVEP): a technique where contrast modulating inputs are 'frequency tagged' (presented at well-defined frequencies and phases) and the electrical signals that they generate in the brain are analyzed in the temporal frequency domain. SSVEPs have several advantages over conventional measures of visually-evoked responses: they have relatively unambiguous ouput measures, a high signal to noise ratio (SNR), and they allow us to analyze interactions between stimulus components using a convenient mathematical framework. Here we describe how SSVEPs have been used to study visual contrast over the past 70 years. Because our thinking about SSVEPs is well-described by simple mathematical models, we embed code that illustrates key steps in the modelling and analysis. This paper can therefore be used both as a review of the use of SSVEP in measuring human contrast processing, and as an interactive learning aid.
对比度是早期视觉系统的核心要素。测量对比度处理背后的计算方式如何依赖于空间和时间频率、年龄、临床状况、偏心率、色度以及其他刺激的存在等因素,在一个多世纪以来一直是视觉科学的研究重点。该领域最富有成效的实验方法之一是使用“稳态视觉诱发电位”(SSVEP):一种将对比度调制输入进行“频率标记”(以明确的频率和相位呈现)并在时间频率域中分析其在大脑中产生的电信号的技术。与传统的视觉诱发反应测量方法相比,SSVEP具有多个优点:它们具有相对明确的输出测量、高信噪比(SNR),并且允许我们使用方便的数学框架分析刺激成分之间的相互作用。在这里,我们描述了在过去70年中SSVEP是如何被用于研究视觉对比度的。由于我们对SSVEP的理解可以通过简单的数学模型很好地描述,我们嵌入了说明建模和分析关键步骤的代码。因此,本文既可以作为对SSVEP在测量人类对比度处理中的应用的综述,也可以作为一种交互式学习工具。