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 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.
Highlights
Visual cognition depends on fast and progressive transformations of retinal inputs into higher-order representations useful for decision-making (Rousselet et al, 2004a; DiCarlo and Cox, 2007; Schyns et al, 2009a)
A theory of visual cognition must specify the information content of brain activity from retinal input to decision-making, and the operations performed on this information – the mechanisms
ERP research has matured its techniques and theories since the first reports of larger ERPs to faces compared to objects
Summary
Visual cognition depends on fast and progressive transformations of retinal inputs into higher-order representations useful for decision-making (Rousselet et al, 2004a; DiCarlo and Cox, 2007; Schyns et al, 2009a). Clear operational definitions of specific, selective, and preferential responses have been described, providing a useful framework to interpret task effects and compare them across studies (Pernet et al, 2007).
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