quantifying the time course of visual object processing using erps: it’s time to up the game

Abstract

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 behavioural, 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.