Early ERPs to faces and objects are driven by phase, not amplitude spectrum information: Evidence from parametric, test-retest, single-subject analyses

被引:18
作者
Bieniek, Magdalena M. [1 ]
Pernet, Cyril R. [2 ]
Rousselet, Guillaume A. [1 ]
机构
[1] Univ Glasgow, Inst Neurosci & Psychol, Coll Med Vet & Life Sci, Glasgow, Lanark, Scotland
[2] Univ Edinburgh, Western Gen Hosp, Brain Res Imaging Ctr, Div Clin Neurosci, Edinburgh, Midlothian, Scotland
关键词
phase spectrum; amplitude spectrum; object categorization; face categorization; event-related potentials; general linear model; TIME-COURSE; DECISION-MAKING; CATEGORIZATION; SCENE; REPRESENTATION; ECCENTRICITY; SENSITIVITY; PERCEPTION; FEATURES; NOISE;
D O I
10.1167/12.13.12
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
One major challenge in determining how the brain categorizes objects is to tease apart the contribution of low-level and high-level visual properties to behavioral and brain imaging data. So far, studies using stimuli with equated amplitude spectra have shown that the visual system relies mostly on localized information, such as edges and contours, carried by phase information. However, some researchers have argued that some event-related potentials (ERP) and blood-oxygen-level-dependent (BOLD) categorical differences could be driven by nonlocalized information contained in the amplitude spectrum. The goal of this study was to provide the first systematic quantification of the contribution of phase and amplitude spectra to early ERPs to faces and objects. We conducted two experiments in which we recorded electroencephalograms (EEG) from eight subjects, in two sessions each. In the first experiment, participants viewed images of faces and houses containing original or scrambled phase spectra combined with original, averaged, or swapped amplitude spectra. In the second experiment, we parametrically manipulated image phase and amplitude in 10% intervals. We performed a range of analyses including detailed single-subject general linear modeling of ERP data, test-retest reliability, and unique variance analyses. Our results suggest that early ERPs to faces and objects are due to phase information, with almost no contribution from the amplitude spectrum. Importantly, our results should not be used to justify uncontrolled stimuli; to the contrary, our results emphasize the need for stimulus control (including the amplitude spectrum), parametric designs, and systematic data analyses, of which we have seen far too little in ERP vision research.
引用
收藏
页数:24
相关论文
共 49 条
[1]   Systematic biases in early ERP and ERF components as a result of high-pass filtering [J].
Acunzo, David J. ;
MacKenzie, Graham ;
van Rossum, Mark C. W. .
JOURNAL OF NEUROSCIENCE METHODS, 2012, 209 (01) :212-218
[2]   Electrophysiological studies of human face perception. I: Potentials generated in occipitotemporal cortex by face and non-face stimuli [J].
Allison, T ;
Puce, A ;
Spencer, DD ;
McCarthy, G .
CEREBRAL CORTEX, 1999, 9 (05) :415-430
[3]   Selectivity for low-level features of objects in the human ventral stream [J].
Andrews, Timothy J. ;
Clarke, Alex ;
Pell, Philip ;
Hartley, Tom .
NEUROIMAGE, 2010, 49 (01) :703-711
[4]   The effects of display time and eccentricity on the detection of amplitude and phase degradations in textured stimuli [J].
Clarke, Alasdair D. F. ;
Green, Patrick R. ;
Chantler, Mike J. .
JOURNAL OF VISION, 2012, 12 (03)
[5]   Low-level cues and ultra-fast face detection [J].
Crouzet, Sebastien M. ;
Thorpe, Simon J. .
FRONTIERS IN PSYCHOLOGY, 2011, 2
[6]   EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis [J].
Delorme, A ;
Makeig, S .
JOURNAL OF NEUROSCIENCE METHODS, 2004, 134 (01) :9-21
[7]   EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing [J].
Delorme, Arnaud ;
Mullen, Tim ;
Kothe, Christian ;
Acar, Zeynep Akalin ;
Bigdely-Shamlo, Nima ;
Vankov, Andrey ;
Makeig, Scott .
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2011, 2011
[8]  
DREWES J, 2006, J VISION, V6, P561, DOI DOI 10.1167/6.6.561.
[9]   How do amplitude spectra influence rapid animal detection? [J].
Gaspar, Carl M. ;
Rousselet, Guillaume A. .
VISION RESEARCH, 2009, 49 (24) :3001-3012
[10]   Diagnostic colours contribute to the early stages of scene categorization: Behavioural and neurophysiological evidence [J].
Goffaux, V ;
Jacques, C ;
Mouraux, A ;
Oliva, A ;
Schyns, PG ;
Rossion, B .
VISUAL COGNITION, 2005, 12 (06) :878-892