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Spatial scaling factors explain eccentricity
effects on face ERPs
McMaster University, Department of Psychology,
Neuroscience & Behaviour, Hamilton, Ontario, Canada
Guillaume A. Rousselet
McMaster University, Department of Psychology,
Neuroscience & Behaviour, Hamilton, Ontario, Canada
Jesse S. Husk
McMaster University, Department of Psychology,
Neuroscience & Behaviour, Hamilton, Ontario, Canada
Patrick J. Bennett
McMaster University, Department of Psychology,
Neuroscience & Behaviour, Hamilton, Ontario, Canada
Allison B. Sekuler
Event-related potential (ERP) studies consistently have described a strong, face-sensitive response termed the N170. This
component is maximal at the fovea and decreases strongly with eccentricity, a result that could suggest a foveal bias in the
cortical generators responsible for face processing. Here we demonstrate that scaling stimulus size according to V1
cortical magnification factor can virtually eliminate face-related eccentricity effects, indicating that eccentricity effects on
face ERPs are largely due to low-level visual factors rather than high-level cortical specialization for foveal stimuli.
Keywords: face processing, object recognition, ERP, N170, spatial scaling
Introduction
The degradation of visual performance with eccen-
tricity strongly limits our capacity to apprehend objects
such as faces in natural scenes (Rousselet, Thorpe, &
Fabre-Thorpe, 2004). Eccentricity effects might be the
direct consequence of low-level factors (Banks, Sekuler,
& Anderson, 1991; Bennett & Banks, 1991;M.kel.,
N.s.nen, Rovamo, & Melmoth, 2001). Alternatively, they
could reflect the specialization of object-selective cortical
areas for foveal stimuli (Levy, Hasson, Avidan, et al.,
2001; Hasson, Levy, Behrmann, Hendler, & Malach,
2002). In keeping with this last idea, the
early selective response of the visual cortex to faces
(time range 140Y200 ms), as indexed by central (VPP:
Jeffreys, 1996) and posterior (N170: Carmel & Bentin,
2002; Itier & Taylor, 2004a; Rossion et al., 2000;
Rousselet, Mac2, & Fabre-Thorpe, 2004) event-related
potentials (ERP), has been shown to decline dramatically
when stimuli are presented few degrees away from
fixation (Eimer, 2000; Jeffreys, Tukmachi, & Rockley,
1992). Such a decline is consistent with the notion of
selective tuning of face processing areas to foveally
presented faces. However, before we can accept the
theory of a foveal bias in face and object processing, we
first must rule out the possibility that eccentricity-based
effects may be a simple consequence of the reduced
cortical representation of peripherally presented stimuli
(M.kel. et al., 2001). One obvious manipulation to
control for reduced cortical representation is to magnify
stimulus size according to the cortical ma gnification
factor.
Jeffreys et al. (1992) manipulated stimulus size and
found that an eightfold size increase did influence the
degree to which the ERP response to faces (VPP) was at-
tenuated by eccentricity. However, even using such large
faces (9- in height) the VPP was very weak, if present at
all, when faces were centered at 4- of eccentricity and
more (Jeffreys, 1996; Jeffreys et al., 1992). This result led
Jeffreys to conclude that the VPP was an automatic re-
sponse to fixated faces. Eimer (2000) studied the effect
of eccentricity on the N170 and the VPP. Compared to
central presentations, Eimer found a reduced but reliable
N170 difference between faces and houses centered at
3.5- from the fixation point. The VPP, on the other hand,
was no longer present at 3.5-. Eimer did not manipulate
stimulus size.
In the present experiment, we examined the effect of
eccentricity on the N170, an ERP component very sen-
sitive to faces, controlling for the effect of cortical mag-
nification. Although there has been an extensive debate in
the literature as to whether the VPP and the N170 reflect
the activity of the same generators (e.g., Eimer, 2000),
there is now strong evidence that they reflect the oppo-
site sides of the same coin (e.g., George, Evans, Fiori,
Davidoff, & Renault, 1996; Itier & Taylor, 2002, 2004a;
Jemel et al., 2003; see particularly Joyce & Rossion,
2005). Fifteen subjects viewed a series of randomly
interleaved faces and houses presented either centrally
Journal of Vision (2005) 5, 755–763 http://journalofvision.org/5/10/1/ 755
doi: 10.1167/5.10.1 Received July 12, 2005; published November 7, 2005 ISSN 1534-7362 * ARVO
or centered at 5- or 10- to the left or right of fixation
(abbreviations: 0-,L5-,R5-, L10-, R10-). Stimuli were
matched for spatial frequency content by averaging their
amplitude spectrum. This manipulation was introduced to
rule out the hypothesis that the face eccentricity effect
might be due to low-level differences in the spatial
frequency content of houses and faces. Peripheral stimuli
were presented at one of two sizes: either matched to the
central presentation size, or scaled to compensate for
differences in V1 cortical representation (Figure 1). Our
results show that scaling stimulus size according to the V1
cortical magnification factor can virtually eliminate face-
related eccentricity effects. This demonstrates that eccen-
tricity effects on face ERPs are largely due to low-level
visual factors rather than to high-level cortical special-
ization for foveal stimuli.
Methods
Subjects
Fifteen subjects participated in this experiment. All
subjects gave written informed consent and had normal or
corrected-to-normal vision. Subjects ranged in age from
19 to 32 (mean age 25), and received $10/hour for their
participation. Twelve subjects were right handed, and
seven were female.
Stimuli
Stimulus construction
Faces were front-view photographs converted to grey-
scale, and cropped within a common oval frame that re-
moved both hair and face contour information. Each of
the 10 cropped faces was 3.0- high and 1.8- wide in the
nonscaled stimulus, and the face was centered in a 3.0-
3.0- background of average luminance (for more de-
tails, see Gold, Bennett, & Sekuler, 1999). The 10 house
stimuli were derived from front-view photographs of
houses converted to greyscale. The house set employed
in the experiment was designed to share the configural
homogeneity typical of faces (i.e., with key features found
in the same relative configuration across exemplars). To
replicate this homogeneity within the house set, one house
was chosen to act as a base house for all stimuli. This
house was cropped from the background scene informa-
tion (bushes, driveway, etc.) and placed on a light grey
background. The base house contained a door in the lower
left, a large window in the lower right, and a pair of upper
windows. To create the individual houses in the house set,
the windows and doors were replaced with new exemplars
from other photographs, placed in the same position as the
originals. As with faces, each individual house could be
discriminated based on any one of these individual fea-
tures. The faces and houses were then placed on back-
grounds of uniform grey (luminance ¼ 20:2 cd=m
2
).
These final stimuli were then equated in terms of spatial
frequency content by taking the average of the amplitude
Figure 1. Examples of two stimuli at different sizes used in the experiment. The size ratio has been respected in this figure.
Journal of Vision (2005) 5, 755–763 Rousselet et al. 756
spectra of all 20 stimuli and then combining that average
spectrum and the original phase spectra to reconstruct
each individual stimulus. Because form information is
largely carried by phase rather than amplitude (Oppenheim
& Lim, 1981; Sekuler & Bennett, 1996), ind ividual
houses and faces remain easily discriminable after this
manipulation. However, this manipulation ensures that
any eccentricity-related differences in the EEG to faces or
houses are not simply a function of differences in the
relative visibility of specific frequency components in the
stimuli.
Determining stimulus size
To determine the amount an image should be magnified
on the screen so that it stimulates a constant cortical area,
the ratio of cortical magnification (M) at fixation versus
magnification at eccentricity E needs to be determined.
To do so we used the following formula (Horton & Hoyt,
1991): M
linear
¼ A=ðE þ e2Þ, with E the eccentricity in
degrees, A the cortical scaling factor in mm, and e2 the
eccentricity in degrees at which a stimulus subtends half
the cortical distance that it subtends at the fovea. We used
A ¼ 29:2mm and e2 ¼ 3:67 - based on a recent re-
port of the cortical magnification factor in V1 (Dougherty
et al., 2003). For a stimulus presented at fixation, E ¼
0- and M ¼ 29:2=3:67 ¼ 7:96. For a stimulus presented
at 5- from fixation, E ¼ 5 and M ¼ 29:2=ð5 þ 3:67Þ¼
3:37. So, the image at fixation stimulates a cortical sur-
face area that is 7:96=3:37 ¼ 2:36 times larger than the
surface stimulated by the same image when it is presented
at 5-. Therefore, the image size had to be multiplied by
2.36 to compensate for the magnification factor when the
image was presented at 5-. Finally, for a stimulus pre-
sented at 10- from fixation, E ¼ 10 and M ¼ 29:2=ð10 þ
3:67Þ¼2:14. By the same reasoning, image size had to
be multiplied by 7:96=2:14 ¼ 3:72 when the image was
presented at 10-. Based on screen constraints, we choose
the largest face height to be 350 pixels (11.2-, the width
of the cropped stimuli being 6.8-). The size for a central
stimulus was thus 350=3:72 ¼ 94 pixels (3.0-, the width
of the cropped stimuli being 1.8-). At 5 - it was 94
2:36 ¼ 222 pixels (7.2-, the width of the cropped stimuli
being 4.4-). There were a total of 18 conditions in this
experiment: faces and houses were seen at five different
positions, and at four of these positions they could have
two different sizes.
Experimental design
Subjects sat in a dimly lit sound-attenuated booth.
Viewing distance was maintained at 70 cm by the use of a
chin rest. Stimuli were presented for 80 ms (six frames at
75 Hz) on a Sony Trinitron GDM-F520 monitor (1024
768 pixels, effective height and width: 40.5 30.5 cm).
Subjects had to respond by pressing one of two keys to
indicate whether a face or house appeared on the screen.
The button/categor y as sociat ion was counterbalanced
across subjects. An experiment was composed of two
sessions, each containing 1080 trials (90 trials 12
blocks). Each session used 5 of 10 exemplars from each
object category (order was counterbalanced across sub-
jects). Within each block, there was only one presentation
of each item (face or house) in each of the nine condi-
tions (0-,L5-, L10-,R5-, R10-, magL5-, magL10-,
magR5-, and magR10-). A trial was organized as fol-
lows: A blank screen was presented for about 200 ms,
followed by a small fixation cross (a 0.3-F+_ in the mid-
dle of the screen) for a random duration ranging from 500
to 900 ms). Then a stimulus was presented for 80 ms,
followed by a blank screen for 1000 ms during which time
subjects were allowed to make a response to the catego-
rization task (face or house). After that delay, responses
were considered incorrect. Trial durations thus ranged from
1780 to 2180 ms.
EEG data acquisition and processing
EEG data were acquired with a 256-channel Geodesic
Sensor Net (Electrical Geodesics Inc., Eugene, Oregon;
Tucker, 1993). Analog signal was amplified about 1000
times, digitized at 500 Hz, and band-pass filtered between
0.1 and 200 Hz. The ground electrode was placed along
the midline, ahead of Fz, and impedances were kept
below 50 kV. Subjects were asked to minimize blinking,
head movement, and swallowing. Subjects were then
given a description of the task. They were carefully
instructed about the importance of maintaining fixation
even when stimuli were peripherally presented. Electrode
positions were obtained by means of a Polhemus spatial
digitizer.
The main experiment was preceded and followed by a
short eye calibration procedure that was aimed at obtaining
ERP topographies for prototypical eye movements. These
topographies were used during data analysis to correct for
eye movement artifacts (see BESA artifact correction
manual). In randomly interleaved blocks, subjects were
asked to move their eyes left, right, up, and down, and to
blink. Each block was composed of 20 trials, providing
a total of 40 trials per condition across the two sessions.
In all conditions, a white point (0.1-, 112 cd/m
2
) was
presented against a black background. For eye move-
ments, a white point was alternatively presented in the
middle of the screen for 1000 ms and then 10- away from
the fixation point for 1000 ms. Subjects were instructed to
always maintain fixation on the point, to follow the point
with their eyes when it moved, but to avoid anticipatory
movements, and blinking during eye movements. In a
blink block, the point was presented for 1000 ms followed
by a blank screen for 1000 ms. Subjects were instructed to
blink once whenever the point flashed off.
Journal of Vision (2005) 5, 755–763 Rousselet et al. 757
EEG analysis was performed using BESA 5.0 (MEGIS
software GmbH). EEG data were referenced on-line to
electrode Cz and re-referenced off-line by subtracting the
average of all signals from each individual signal. The
signal was then band-pass filtered in the range 1Y30 Hz
and bad channels interpolated. Baseline correction was
performed using the 200-ms of prestimulus activity.
Two artifact rejections were applied on all electrodes
over the [j200 ms; +300 ms] time period, first with a
criterion of [j100; +100 AV] to reject trials with
excessive amplitude, second to reject trials in which the
differe nce between two consecutive time points was
greater than 75 AV. Only correct trials were averaged.
ERPs were corrected for blink and horizontal movement
artifacts before further analysis.
Source modeling in BESA
The actual location of the N170 sources is still
controversial and seems to correspond to the activity
of a distributed network including at least medial
temporal areas and ventral occipitalYtemporal areas
(BPtzel, Schulze, & Stodieck, 1995; Itier & Taylor,
2004b; Watanabe, Kakigi, & Puce, 2003). However, the
goal of our modeling was not to provide an accurate
estimate of the sources of the N170, but rather to provide
a compact description of the signal recorded over the
entire scalp. We used separate averages of the uncorrected
ERP and of the average artifacts to create independent
spatial components for the ERP and the artifacts (see
BESA artifact correction manual for details). The N170
was modeled using two symmetric regional sources over
the inte rval 140Y240 ms after stimulus onset. The
positions of the sources generally were compatible with
generators situated in extra-striate visual cortex, but there
was significant variability across subjects. Each source
was composed of three orthogonal vectors that were
squared and added together before measuring the mean
amplitude of the source waveforms over the time interval
140Y240 ms. We performed analyses on the residual
variance of the model for the different conditions. For
both scaled and nonscaled stimuli, an ANOVA revealed a
main position effect (both p G .005), but no category effect
and no interaction between category and position factors.
Figure 2. Mean reaction times as a function of eccentricity and
size.
Figure 3. Interpolated 2D topographical maps of the differential activity between face and house ERPs. Each map represents the average
activity over a time window indicated at the bottom of the figure. Nose is pointing upward. For each map, a cross is centered at electrode Cz
(situated at the apex of the scalp). The circle joins the glabella (brow ridge) and the occipital protuberance (back of the skull). The two holes
on the left and right sides of the maps correspond to the locations of the ears. In the left columns, all stimuli were the same size. In the right
columns, stimuli were cortically magnified, except central stimuli (C) whose maps are identical to those presented in the left columns. L5,
R5, L10, and R10 refer to stimuli presented in the left /right visual field at 5/10- of eccentricity. Interpolated ERP maps were made with the
CarTool data analysis software (3.1) developed by Denis Brunet at the Functional Brain Mapping Laboratory, Geneva, Switzerland.
Journal of Vision (2005) 5, 755–763 Rousselet et al. 758
For nonscaled stimuli, post hoc paired t tests revealed
significant differences between central presentations and
presentations at 10- (left and right) and 5- right. For
scaled stimuli, there were only significant differences
between central presentation and presentations at 10- (left
and right). Those effects were expected given the drop of
signal to noise ratio with increased eccentricity. Statistical
analysis on the 3D coordinates of the regional sources in
the face and house c onditions d id not reveal any
significant effect.
Results
At the behavioral level, subjects performed very well
in this task with a mean accuracy of 92.2% across
conditions (range 88.4Y94.7%). For reaction times
(mean 517 ms), there was an interaction between
eccentricity and scaling (Figure 2), with no effect of
eccentricity for scaled stimuli, but slower responses for
peripherally presented nonscaled stimuli, F(2.0,28.2) =
26.3, p G .0001.
As found p reviously (Eimer, 1998, 2000 ;Itier&
Taylor, 2004a; Rossion et al. 2000), the foveal N170
was larger in amplitude for faces than for houses and was
characterized by a central-positive and bilateral posterior-
negative topography (Figure 3). In keeping with the
broader literature, we refer to the amplitude difference
between faces and houses (Bthe face effect[) as a marker
for face processing. Notably, this is the first time the face
effect has been shown for stimuli equated in spatial
frequency content. Furthermore, contrary to Eimer (2000)
and Jeffreys et al. (1992; Jeffreys, 1996) who found no
VPP for faces centered respectively at 3.5- and 4-, our
data clearly show both an N170 and a VPP at all
eccentricities (Figure 3). This constitutes another argu-
ment in favor of a common origin of these two
components (Joyce & Rossion, 2005). However, a
complete discussion of the potential relationship between
the N170 and the VPP is beyond the scope of this paper.
The reason that Jeffreys did not record a VPP even for
large faces presented 4- or more from the fixation point
might be that the very few subjects he tested presented a
pattern we observed in some of our subjects, wherein the
VPP topography changes sli ghtly with ecce ntricity,
presenting a maximum over frontal and central electrodes
ipsilateral to the stimulation. Because Jeffreys recorded
only from central electrodes, he could have missed the
lateralized VPP.
The time course of the face effect was determined at
each eccentricity by comparing the global field power
(GFP) for faces and houses at each time point (Figure 4).
Figure 4. Time course of the global field power (GFP) for faces and houses in the different conditions. The GFP is the instantaneous spatial
standard deviation computed across electrodes at each time point (Lehmann & Skrandies, 1980). This measure is independent of the
reference electrode and the number of electrodes and thus provides a compact description of the signal across the head. Time points at
which signals for faces and houses diverged significantly (p G .01, 999 bootstrap permutations) are indicated by red points along the
horizontal axis.
Journal of Vision (2005) 5, 755–763 Rousselet et al. 759
GFP is a measure of changes in electric field strength and
is computed as the spatial standard deviation of the scalp
electric field (Lehmann & Skrandies, 1980). Stronger
electric fields lead to larger GFP values. It is assumed that
peaks of GFP coincide with maximum activation of the
underlying generators. Significant GFP differences
between two conditions were assessed at each time point
and at each scalp location using bootstrap methods (999
permutations, p G .01, corrected for multiple comparisons;
Figure 4). This analysis revealed a significant difference
starting at 166 ms for central presentations. For nonscaled
stimuli, the effect appeared slightly later in the L5- (184
ms) and R5- (170 ms) conditions and was no longer
significant at 10-. However, there was a dramatic change
in the results when faces and houses were enlarged to
compensate for cortical magnification differences. First,
the difference in GFP strength between faces and houses
presented at 5- appeared at about the same latency that
was observed at 0- (L5- = 156 ms; R5- = 164 ms).
Second, this effect re-emerged at 10-, with a similar time
course as that found at the other eccentricities (L10- =
160 ms; R10- = 158 ms).
The same pattern of results was obtained when
comparisons were performed on the ERP at individ-
ual electrodes rather than on the GFP. Significant
ERP differences between t wo conditions were
assessed at e ach time point and at each scalp
location using bootstrap methods (999 permutations,
p G .01, corrected for multiple comparisons). Clear
differences were observed in the 0-,L5-,andR5-
nonscaled conditions at posterior, central, and frontal
electrodes (Figures 5 and 6). Only very few of those
electrodes presented significant differences at 10- , and
those differences were very brief in time with onsets after
200 ms. Scaling stimulus size again virtually eliminated
the eccentricity effect.
To estimate the activity of the brain sources in the
different conditions, without biasing the analysis toward
specific electrodes, the ERP signal was modeled in BESA
by using two regional sources constrained in symmetry
over the time window 140Y240 ms (Figure 7). The model
accounted for 85.4Y91.7% of the variance in each
condition and the goodness-of-fit did not vary signifi-
cantly between faces and houses. For nonscaled stimuli,
there was a strong decrease in the amplitude of the
modeled sources with eccentricity for both faces and
houses, and a decrease in the differential amplitude
between faces and houses. Indeed, whereas there was a
strong difference between faces and houses at the fovea,
this diffe rence was already reduced at 5- and not
significant at 10-. For scaled stimuli, differences between
faces and houses were similar at all positions, indicating
Figure 5. Grand average ERPs averaged across a cluster of nine neighboring posterior electrodes at which the signal was maximal. Left
electrodes = 83-84-85-94-95-96-104-105-106; right electrodes = 162-163-170-171-172-178-179-180-190. Face and house ERPs are
depicted in red and blue traces respectively. Left (L) and right (R) hemisphere ERPs are depicted in dotted and solid lines, respectively.
The N170 decreased dramatically in amplitude with eccentricity and progressively lost its face specificity, an effect that could be restored
by scaling stimulus size. Note also the clear lateralization of the N170, first recorded at electrodes over the hemisphere contralateral to
stimulus presentation.
Journal of Vision (2005) 5, 755–763 Rousselet et al. 760
that scaling stimulus size eliminated the eccentricity
effect.
Conclusions
The present ERP results rule out the hypothesis that the
face eccentricity effect is due to low-level differences in
the global spatial frequency content of houses and faces.
Furthermore, we find no evidence that there is a foveal
bias for face processing (as indexed by the N170) per se.
Rather, eccentricity-based differences in face processing
appear to be largely attributable to cortical magnification,
in keeping with recent results from the monkey literature
(Rolls, Aggelopoulos, & Zheng, 2003; Rousselet et al.,
2004). However, even after magnification, the onset of the
face effect was still slightly delayed for stimuli presented
at 10- of eccentricity compared to the foveal condition
(Figure 6; although note that the GFP results show, if
anything, an earlier onset for scaled peripheral stimuli
compared to central stimuli; Figure 4). Of course, the
magnification factor we used was appropriate for V1, and
so likely was not a precise match for the locus of the
N170. Moreover, because other factors like contrast
sensitivity and phase discrimination also change with
eccentricity (Banks et al., 1991; Bennett & Banks, 1991;
M.kel. et al., 2001) and might affect face and object
ERPs, a single spatial scaling factor is unlikely to account
for all differences between object ERPs at the fovea and
in the periphery. Also, stimulus scaling was not sufficient
to compensate completely for the decrease of the absolute
amplitude of the N170 and other ERP components. This
result is difficult to interpret bas ed on the monke y
literature because, to our knowledge, no study comparable
to the present experiment has yet been performed. But in
keeping with the monkey literature, we believe it is more
instructive to focus on differential activities, which might
be a good indicator of the capacity of a large neuronal
population (in the cas e of the ERP) to discriminate
between two sets of stimuli. In addition, the difference
in the P2 range was almost nonexistent at 10- for scaled
Figure 6. Significant differences at each electrode over time between face and house ERPs. Differences were assessed at each time
point and each electrode using 999 bootstrap permutations (p G .01, corrected for multiple comparisons). Significant time points are
indicated in red (|face ERP| 9 |house ERP|) and blue (|house ERP| 9 |face ERP|) while nonsignificant time points are indicated in grey.
Electrodes are stacked along the vertical axis. The horizontal black lines separate the different groups of electrodes organized in frontal,
central, and posterior electrodes (F/C/P) and subdivided into left hemisphere, median, and right hemisphere electrodes (L/M/R).
Journal of Vision (2005) 5, 755–763 Rousselet et al. 761
stimuli (about 200Y250 ms; Figures 4 and 6). This might
indicate that late res ponding mechanisms, potentially
related to face recognition rather than simple object
discrimination (Halit, de Hann, & Johnson, 2000), are
still perturbed after image scaling. However, any interpre-
tation regarding the later component is necessarily tenta-
tive, as the current study examined discrimination rather
than recognition.
Overall, though, in the present experiment cortical
magnification accounts for most of the eccentricity-related
differences in the ERP response amplitudes to faces and
houses. It is not yet clear whether these results contradict
the model of Levy et al., which suggests that in fMRI the
cortical areas responding more strongly to faces have a
bias toward the central visual field while areas responding
more strongly to houses have a bias toward the peripheral
visual field (Hasson et al., 2002; Levy et al. 2001). Here
we found a similar drop of ERP activity with eccentricity
for both categories (Figure 7), whereas the model by Levy
et al. would actually predict an increase of the response
for houses in the periphery. However, the sources of the
N170 are still debated (Itier & Taylor, 2004b; Watanabe
et al., 2003) and fMRI has a relatively poor temporal
resolution. Thus, the results by Levy et al. could reflect a
later part of the neuronal response. In any case, our results
strongly suggest that a high-level cortical specialization
for foveal stimuli is not likely to be a rule applying to all
face processing cortical areas.
Finally, the present ERP results rule out the
hypothesis that the face eccentricity effect is due to
low-level differences in the global spatial frequency
content of houses and faces. Because amplitude spectra
were equated across all stimuli, the eccentricity-related
differences in the EEG to unscaled faces and houses
cannot simply be a function of differences in the rela-
tive visibility of specific frequency components in the two
stimulus sets. As well, our results demonstrate that face
and house processing is eccentricity and size dependent.
This strong constraint needs to be taken into account by
models of object processing in natural scenes, which
typically ignore such low-level constraints (Rousselet
et al., 2004). Our data are also in keeping with the idea
that, at least in terms of face processing, the dif ferences
between the peripheral and the central visual fields are
quantitative rather than qualitative in nature (M.kel. et al.,
2001).
Acknowledgments
We acknowledge support from NSERC Discovery
Grants 42133 and 105494, the CIHR fellowship program,
and the Canada Research Chair program. McMaster
University Research Ethics Board approved this work.
Commercial relationships: none.
Corresponding author: Guillaume A. Rousselet.
Email: rousseg@mcmaster.ca.
Address: 1280 Main Street West, Hamilton, ON L8S4K1.
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