Parametric study of EEG sensitivity to phase noise during face processing

Guillaume A Rousselet,Patrick J Bennett,Allison B Sekuler,Cyril R Pernet

doi:10.1186/1471-2202-9-98

Abstract

BackgroundThe present paper examines the visual processing speed of complex objects, here faces, by mapping the relationship between object physical properties and single-trial brain responses. Measuring visual processing speed is challenging because uncontrolled physical differences that co-vary with object categories might affect brain measurements, thus biasing our speed estimates. Recently, we demonstrated that early event-related potential (ERP) differences between faces and objects are preserved even when images differ only in phase information, and amplitude spectra are equated across image categories. Here, we use a parametric design to study how early ERP to faces are shaped by phase information. Subjects performed a two-alternative force choice discrimination between two faces (Experiment 1) or textures (two control experiments). All stimuli had the same amplitude spectrum and were presented at 11 phase noise levels, varying from 0% to 100% in 10% increments, using a linear phase interpolation technique. Single-trial ERP data from each subject were analysed using a multiple linear regression model.ResultsOur results show that sensitivity to phase noise in faces emerges progressively in a short time window between the P1 and the N170 ERP visual components. The sensitivity to phase noise starts at about 120–130 ms after stimulus onset and continues for another 25–40 ms. This result was robust both within and across subjects. A control experiment using pink noise textures, which had the same second-order statistics as the faces used in Experiment 1, demonstrated that the sensitivity to phase noise observed for faces cannot be explained by the presence of global image structure alone. A second control experiment used wavelet textures that were matched to the face stimuli in terms of second- and higher-order image statistics. Results from this experiment suggest that higher-order statistics of faces are necessary but not sufficient to obtain the sensitivity to phase noise function observed in response to faces.ConclusionOur results constitute the first quantitative assessment of the time course of phase information processing by the human visual brain. We interpret our results in a framework that focuses on image statistics and single-trial analyses.

Highlights

IntroductionIntroduction to Robust Estimation and HypothesisTesting. 2nd edition. Academic Press; 2005. 50
Introduction to Robust Estimation and HypothesisTesting. 2nd edition
When contrasting face stimuli to noise textures created by complete randomization of the phase information while keeping the amplitude information constant, the earliest event-related potential (ERP) differences occur at about 120–140 ms after stimulus onset [28,30,31,37,42,43]. This might be the time at which object-related global phase information is extracted by the visual system, the precise time course of this process is still unknown, as is the way phase information influences early cortical responses to objects. We addressed these questions by manipulating phase information systematically along a continuum while subjects discriminated between two faces briefly presented on a screen (Figure 1)

Summary

Introduction

Introduction to Robust Estimation and HypothesisTesting. 2nd edition. Academic Press; 2005. 50. At the other end of the visual cortical hierarchy, in higher order visual areas, no such debate exists since those areas are mostly responsive to complex objects, and not to simple patterns [6,7,8,9,10] In those areas, the emphasis has been put on object categories and their relative specificity [11]. The category-related parcelling of the visual cortex ignores the question of the transformation mechanisms taking place along the visual hierarchy Because these processes occur very fast, critical information processing events may be observed at the time-scale of EEG (electroencephalography) [3,12,13,14]. In the time window of the P1 component (80–120 ms), has been discussed as a potential marker of complex object processing [25,26,27]

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