Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow Glasgow, UK.
Front Psychol. 2011 May 23;2:107. doi: 10.3389/fpsyg.2011.00107. eCollection 2011.
Hundreds of studies have investigated the early ERPs to faces and objects using scalp and intracranial recordings. The vast majority of these studies have used uncontrolled stimuli, inappropriate designs, peak measurements, poor figures, and poor inferential and descriptive group statistics. These problems, together with a tendency to discuss any effect p < 0.05 rather than to report effect sizes, have led to a research field very much qualitative in nature, despite its quantitative inspirations, and in which predictions do not go beyond condition A > condition B. Here we describe the main limitations of face and object ERP research and suggest alternative strategies to move forward. The problems plague intracranial and surface ERP studies, but also studies using more advanced techniques - e.g., source space analyses and measurements of network dynamics, as well as many behavioral, fMRI, TMS, and LFP studies. In essence, it is time to stop amassing binary results and start using single-trial analyses to build models of visual perception.
数百项研究使用头皮和颅内记录来研究面孔和物体的早期 ERP。这些研究中的绝大多数都使用了不受控制的刺激、不适当的设计、峰值测量、较差的图形以及较差的推断和描述性群体统计数据。这些问题，以及倾向于讨论任何效应 p < 0.05 而不是报告效应大小的倾向，导致了一个非常定性的研究领域，尽管它受到了定量的启发，但在这个领域中，预测并不能超越条件 A > 条件 B。在这里，我们描述了面孔和物体 ERP 研究的主要局限性，并提出了替代策略以推动研究进展。这些问题困扰着颅内和表面 ERP 研究，也困扰着使用更先进技术的研究 - 例如，源空间分析和网络动态测量，以及许多行为学、fMRI、TMS 和 LFP 研究。从本质上讲，现在是停止积累二元结果并开始使用单试分析来建立视觉感知模型的时候了。
