Turning the Face Inversion Effect on Its Head:
Violated Expectations of Orientation, Lighting,
and Gravity Enhance N170 Amplitudes
Yasmin Allen-Davidian1 , Manuela Russo1, Naohide Yamamoto1
Jordy Kaufman2
, Alan J. Pegna3
, and Patrick Johnston1
,
Abstract
■ Face inversion effects occur for both behavioral and electro-
physiological responses when people view faces. In EEG,
inverted faces are often reported to evoke an enhanced ampli-
tude and delayed latency of the N170 ERP. This response has
been attributed to the indexing of specialized face processing
mechanisms within the brain. However, inspection of the litera-
ture revealed that, although N170 is consistently delayed to a
variety of face representations, only photographed faces invoke
enhanced N170 amplitudes upon inversion. This suggests that
the increased N170 amplitudes to inverted faces may have other
origins than the inversion of the face’s structure. We hypothesize
that the unique N170 amplitude response to inverted photo-
graphed faces stems from multiple expectation violations, over
and above structural inversion. For instance, rotating an image
of a face upside–down not only violates the expectation that faces
appear upright but also lifelong priors about illumination and
gravity. We recorded EEG while participants viewed face stimuli
(upright vs. inverted), where the faces were illuminated from
above versus below, and where the models were photographed
upright versus hanging upside–down. The N170 amplitudes
were found to be modulated by a complex interaction between
orientation, lighting, and gravity factors, with the amplitudes
largest when faces consistently violated all three expectations.
These results confirm our hypothesis that face inversion effects
on N170 amplitudes are driven by a violation of the viewer’s ex-
pectations across several parameters that characterize faces,
rather than a disruption in the configurational disposition of its
features. ■
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INTRODUCTION
Early behavioral studies uncovered a phenomenon in
which recognition of a face was delayed and less accurate
when a face was turned upside–down, compared to when
it was upright ( Yin, 1969). Because this phenomenon
has not been observed with similar intensity for non-face
stimuli (c.f., Johnston, Molyneux, & Young, 2015), this
phenomenon was termed the face inversion effect (FIE;
Bentin, Allison, Puce, Perez, & McCarthy, 1996). The exis-
tence of the FIE is widely supported by subsequent studies
using a variety of different face stimuli. For example,
Rossion et al. (1999) found that participants were slower
and significantly less accurate at determining if a new face
image matched an upright face target image when that
new image was inverted compared to when it was upright.
Similarly, another matching-task study using intact and
scrambled photographed faces, presented both upright
and inverted, found that participant responses were most
inaccurate and delayed when faces were scrambled and
inverted (Bauser & Suchan, 2013).
Moreover, the FIE is also supported by studies using
“Thatcherized” faces (i.e., images of faces in which the
1Queensland University of Technology, 2Swinburne University
of Technology, Melbourne, Australia, 3University of Queensland
© 2020 Massachusetts Institute of Technology
mouth and eyes have been rotated 180°). Thatcherized
faces appear grotesque when presented in an upright orien-
tation, but not when inverted (Thompson, 1980), indicating
that expectations of the structural composition of a face are
more recognizably violated in an upright orientation,
whereas, in a less commonly experienced upside–down
face, violations of structural expectations are harder to
discern. For example, inverted and “Thatcherized” familiar
faces induce slower and less accurate responses, when
participants are asked to determine whether the face was
Thatcherized or normative on a matching task (Carbon,
Grüter, Weber, & Lueschow, 2007). Overall, these studies
among others evaluating behavioral responses to face
inversion have led to the suggestion that the visual modality
has developed orientation-specific face representations,
which are disrupted upon the inversion of a face (Bentin
et al., 1996).
Electrophysiological Response to Face Inversion
A wealth of data has now accumulated in the field of
EEG/ERP, suggesting that an important early step in
the stream of neural events involved in face processing
occurs between 130 and 200 msec. Indeed, the first ERP
Journal of Cognitive Neuroscience 33:2, pp. 303–314
https://doi.org/10.1162/jocn_a_01656
component differentiating faces from other objects peaks
at 170 msec and is characterized by greater negativity over
the lateral-occipital scalp, leading to its designation as the
N170. This component, initially described by Bentin et al.
(1996), was found to be greater for faces compared to
scrambled faces, or to other object categories such as cars,
furniture, hands, or animal faces (although ape faces were
later reported to produce an N170 of similar amplitude;
Carmel & Bentin, 2002). Subsequent investigations com-
paring a broader set of categories, including mushrooms,
flowers, houses, lions, tools, road signs, and textures (Itier
& Taylor, 2004), further confirmed the enhanced N170 for
faces (Johnston et al., 2015).
Surprisingly, face inversion is found to produce a rather
counterintuitive effect. Indeed, one might plausibly expect
face inversion to lead to a decrease in the N170 amplitude,
to the extent that this component reflects the appropriate
encoding of the face stimulus. However, the reverse phe-
nomenon is commonly observed, namely, that inverting
a face elicits an increase in N170 amplitude (e.g., Sadeh
& Yovel, 2010; Itier, Alain, Sedore, & McIntosh, 2007;
Jacques, d’Arripe, & Rossion, 2007; Marzi & Viggiano,
2007; Caharel, Fiori, Bernard, Lalonde, & Rebaï, 2006; Itier,
Latinus, & Taylor, 2006; Righart & de Gelder, 2006; Itier &
Taylor, 2004; de Haan, Pascalis, & Johnson, 2002; Eimer,
2000; Rossion et al., 1999, 2000; Bentin et al., 1996).
N170 latency has also been found to be sensitive to the
orientation of face stimuli, with the ERP peaking signifi-
cantly later for inverted than upright faces (Rousselet, Husk,
Bennett, & Sekuler, 2008; Itier & Taylor, 2004; Rossion et al.,
2000; Bentin et al., 1996). The latency FIE is consistent
across varying face stimuli, such as naturally photographed
faces (Eimer, 2000; Rossion et al., 1999), two-tone Mooney
faces preceded by a training period (George, Jemel, Fiori,
Chaby, & Renault, 2005), and simple line drawn schematic
faces (Latinus & Taylor, 2005, 2006). Rossion et al. (1999)
proposed that inversion may disrupt the configural infor-
mation of the face, which subsequently increases the diffi-
culty of face processing and contributes to a delayed
N170. Thus, the delay of the N170 peak to inverted faces
may stem from the disruption of orientation-specific, struc-
tural encoding processes, driven by configural features of
the face.
Interestingly though, the finding of an enhanced N170
amplitude to inversion is not consistently evident across
different types of stimuli, with discrepancies in amplitudes
elicited by schematic, photographed, and Mooney faces. A
significantly enlarged N170 upon inversion has been consis-
tently found for naturally photographed faces (Itier &
Taylor, 2002; Rossion et al., 2000; Bentin et al., 1996). In
contrast, when participants are presented with schematic
faces, inversion has the opposite effect—reducing N170
amplitude (Henderson, McCulloch, & Herbert, 2003; Sagiv
& Bentin, 2001). Similar findings have been found in studies
using Mooney faces. When two-tone, high-contrast Mooney
images with incomplete features were perceived as faces,
they elicited a larger N170 in response to an upright image
than to an inverted image (Latinus & Taylor, 2005, 2006;
George et al., 2005). Latinus and Taylor (2006)’s compara-
tive study of photographic, schematic, and Mooney faces
further demonstrated that, when the three types of face
stimuli were inverted, only photographed faces elicited a
significantly enhanced N170 amplitude (Latinus & Taylor,
2006). Taking these findings together, it appears that, al-
though N170 latency delays occur to inversion of all face
stimuli, the increased N170 amplitude-to-face inversion
appears to be unique to photographed face stimuli, which
reflect how faces naturally appear in the world.
Several ideas have been offered to explain why the FIE is
unique to naturally photographed faces. Itier et al. (2007)
suggested that the enhancement of the N170 reflects the
additional activation of eye selective neurons within the
STS, which occurs when face stimuli are inverted. As sche-
matic and Mooney faces lack the complex eye information
within naturally photographed faces, Itier et al. (2007) sug-
gested that they do not sufficiently activate the eye selective
neurons and, in turn, elicit a reduced N170. Some support
the importance of the eye region; this comes from Kloth,
Itier, and Schweinberger (2013), who showed that N170
amplitude enhancements to inverted faces only occurred
when the eye region was intact. Alternatively, Sagiv and
Bentin (2001) posited that when a naturally photographed
face is inverted, holistic processing is disrupted, so physiog-
nomic feature processing is recruited. Because schematic
faces are not perceived as containing physiognomic compo-
nents, they are processed with the holistic pathway (Sagiv &
Bentin, 2001). Therefore, Sagiv and Bentin (2001) pro-
posed that the smaller N170 amplitude to inverted sche-
matic faces reflects the inhibition of both the holistic and
featural pathways within a face-specific processing system.
These face-specific processing theories, which propose
the enhanced N170 to inversion stems from the activation
of eye selective neurons (Itier et al., 2007) or the recruit-
ment of physiognomic feature processes (Sagiv & Bentin,
2001), are not wholly supported by the literature. As
although the N170 has been described as a face-sensitive
component, it has been found to be sensitive to a number
of other non-face-related factors, including contrast (Itier &
Taylor, 2002), spatial frequency (Goffaux, Gauthier, &
Rossion, 2003), Gaussian noise (Jemel et al., 2003), atten-
tion (Holmes, Vuilleumier, & Eimer, 2003), and interstimu-
lus variance (Thierry, Martin, Downing, & Pegna, 2007).
A recent study by Johnston et al. (2017) also demonstrated
that the N170 was sensitive to expectancy violations across a
range of stimulus categories and attributes. In their study,
the authors presented a sequence of five static images, with
the first four images establishing an implied trajectory of
either facial expression change, head or body rotation, or
face and shape location within the visual field (Johnston
et al., 2017). The final image in each sequence either con-
formed to the expected trajectory or deviated from the
trajectory predicted, subsequently violating contextually
induced expectations. Johnston et al. (2017) found that,
across all three experiments, irrespective of stimulus type,
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the N170 amplitude was robustly greater to violated trajecto-
ries, than predictable trajectories. These findings suggest that
the N170 is a surprise signal, which is responsive to the pres-
ence or absence of expectation violations. Further studies,
using a similar experimental paradigm, showed that the
N170 amplitude was dose dependent as a function of both
the strength of prior expectations and the degree to which
those expectations are violated (Robinson, Breakspear,
Young, & Johnston, 2018) and that N170 latency surprise
error signals were generated in different regions of the
visual cortex when different attributes (head orientation
and person identity) of the same stimulus faces violated
expectations (Robinson et al., 2020). These findings suggest
that the scalp N170 may (at least in part) reflect prediction
error signals across a range of predicted stimulus attributes.
In line with these findings, we propose that the enhanced
N170-to-face inversion may stem from surprising violations
of contextual expectations, which inform daily visual per-
ception, that faces appear upright, light comes from above,
and gravity pulls downward. When a naturally occurring face
appears upside–down, it is subject to the contextual influ-
ences of lighting and gravity, with the face (usually) lit from
above by overhead lighting or the sun, and earth’s gravity
pulling the loose components of the face downward.
Contrastingly, when an upright photograph of a face is
inverted to appear upside–down, expectations of how faces
commonly appear in the world are not met. As upon inver-
sion, the face appears to be illuminated from below and as
though gravity is pulling upward on the face. Thus, the
N170 may be enhanced in response to unmet or violated
expectations of contextual influences, such as orientation,
direction of lighting, and effect of gravity. This proposed
explanation stems from research that suggests that humans
have developed an upright orientation, light from above,
and gravity bias.
Orientation
As faces are regularly viewed upright and very rarely
upside–down, it is plausible that the brain generates upright
expectations of how faces are orientated in the external
world. This suggestion is supported by Itier and Taylor’s
(2004) developmental behavioral and EEG study, which
found a progressive tuning throughout childhood and late
adolescence to upright faces. A behavioral matching task
revealed that, from 8 to 16 years of age, children grew pro-
gressively faster and more accurate at recognizing upright
faces, over inverted faces (Itier & Taylor, 2004). This FIE
was further supported by EEG recorded across temporal-
parietal electrode sites, demonstrating that the N170
latency was delayed for inverted faces, over upright faces,
consistently for all ages (Itier & Taylor, 2004). Differences
in N170 amplitude size, elicited in adolescents and adults,
suggested that, with age, there is a progressive enhance-
ment of the N170 amplitudes to inverted faces and a grad-
ual reduction in the amplitudes evoked by upright faces
(Itier & Taylor, 2004). These findings suggest a gradual
consolidation of upright expectations, with the N170 pre-
diction error signal progressively enhanced with age, to in-
verted face stimuli, which violated orientation expectations.
This may be attributed to consistent exposure to faces
throughout development and establishment of mature
contextual expectations within adulthood. Thus, we would
surmise that, when a face is inverted, expectations of orien-
tation are violated, resulting in the enhanced N170 com-
ponent of the ERP.
Lighting
Inversion of a photographed face violates a lifelong contex-
tual bias that illumination comes from above. In the field
of object recognition, seminal studies have demonstrated
the expectation in viewers that light must originate from
above. For example, Kleffner and Ramachandran (1992)
modified the shading of two-dimensional stimuli (disks)
producing subjective impressions of perspective and depth,
where light sources would be situated to the left or right
sides, or vertically, below or above. Their findings revealed
that the visual system assumes the presence of a single
light source illuminating the visual scene and, importantly,
the constraint that this source must be situated above the
object. In the field of face processing, behavioral studies
have found that recognition of faces illuminated from below
are significantly less accurate than faces illuminated from
above, which suggests that we expect faces will be illumi-
nated from above, as they are regularly top lit by the sun
or overhead lighting ( Johnston, Hill, & Carman, 2013;
McMullen, Shore, & Henderson, 2000).
A magnetoencephalography study by Brodski, Paasch,
Helbling, and Wibral (2015) provided insight into the effect
of lighting violations on prediction error signaling. They
examined the response in gamma-band activity (GBA) to
Mooney faces, which appeared upright illuminated from
above, upright illuminated from below, inverted illumi-
nated from above, and inverted illuminated from below.
Brodski et al. (2015) found that, within the high-frequency
range (68–144 Hz), GBA was increased when faces
appeared to be illuminated from below and when faces
were inverted. Indicating surprise signaling within GBA is
responsive to violations of lighting and orientation expecta-
tions (Brodski et al., 2015). While also confirming that visual
experience with illumination from above generates expec-
tations of how a face is illuminated, these observations
demonstrate how violated light direction expectations
activate surprise signaling within the brain when lighting
is directed from below, leading to an enhanced N170.
Gravity
Gravity constitutes a prevailing contextual influence on the
way faces appear, with the consistent gravitational pull of
earth pulling the loose components of the face downward.
From lifelong exposure to earth’s gravitational environment,
it is suggested humans have established strong priors of how
Allen-Davidian et al.
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gravity influences visual perception ( Jörges & López-
Moliner, 2017). A virtual reality study that manipulated the
trajectory of a ball, to comply with normal gravity accelera-
tion (1 g) or without gravitational influence (0 g), found
that, for 0-g trials, participants chose a consistently incorrect
point of intercept, which was consistent with that of the
intercept point for 1 g (Russo et al., 2017). Suggesting, an in-
ternal model of earth’s gravitational effects is influential in
predicting intercept location, with consistent exposure to
earth’s gravitational pull generating top–down driven
predictions of trajectory (Russo et al., 2017). Furthermore,
an EEG study conducted aboard the international space
station found that, without a gravitational reference, the
perception of 3-D images within a virtual reality navigation
task evoked significantly different EEG signals than the same
task performed without weightlessness on earth (Cheron
et al., 2014). This suggested that gravity influences multi-
sensory perception inherently on earth, with top–down
engagement of gravitational expectations evident, whereas,
in space, there is evidence to suggest some degree of adap-
tion to weightlessness (Cheron et al., 2014). Anecdotally,
astronauts have reported that the familiar faces of fellow
astronauts look odd in space (de Schonen, Leone, & Lipshits,
1998). This may be attributed to the absence of earth’s
gravity effects, which we have grown accustomed to pulling
the loose components of the face toward the earth.
Although the influence of gravity has not been formally
examined with faces, from the available research, it is a
reasonable assumption that prior beliefs about the direction
pull of gravity might possibly influence perception. Although
we acknowledge that viewing other people hanging upside–
down is rare, we offer the following observation. It is our
belief that a casual viewer observing, side-by-side, two people
who were hanging upside–down, one of whom was subject
to normal effects of gravity on the face (i.e., pulling down-
ward toward the center of the earth), the other of whom
was subject to “inverted gravity” (i.e., pulling skyward) would
easily be able to (1) observe a difference between the two
faces and (2) understand which face was versus was not
subject to normal physical laws. We expect that prior knowl-
edge about gravity will impact the way faces are processed,
with violation of expectations enhancing the N170.
In this study, we examined how the direction of lighting
and gravity influence the processing of upright and inverted
faces, and whether these contextual cues influence the FIE
on the N170 amplitudes. Full front photographs of faces
were taken of models positioned either upright or hanging
upside–down, to vary the effect of gravity systematically. In
addition, light sources were varied with lighting directed to
illuminate the face from above or below. The photographs
themselves were then presented upright or inverted. By
examining the event-related responses to faces in this 2 ×
2 × 2 design, we aimed to determine whether the N170
was affected by inversion alone, or whether, as we surmised,
gravity and lighting cues also might play a role.
Moreover, we further hypothesized that these factors
would interact such that faces violating expectations of
orientation, lighting, and gravity would evoke a larger
N170 amplitude, and faces that conformed to expecta-
tions would evoke a smaller amplitude. In addition, as re-
search has shown the latency of the N170 is consistently
delayed to inverted faces across stimulus types (Latinus &
Taylor, 2006; Rossion et al., 1999), we hypothesized that
the latency of the N170 would be influenced solely by
orientation effects, with the latency significantly more
delayed to inverted faces than upright faces.
METHODS
Participants
Twenty-eight participants met inclusion criteria and were
tested. Two participants were excluded from analyses,
one because of high impedance and the other because of
extreme outlying scores, resulting in 25 participants contrib-
uting to the analyses, of which 21 were women, age ranged
from 18 to 30 years (M = 22.1, SD = 4.3). Participants were
recruited through Queensland University of Technology’s
online research recruitment system SONA. Participants were
allocated either a $10 Coles Myer gift card or 2% of course
credit for their participation. Participants were required to
have normal or corrected-to-normal vision and no history
of neurological disorders. Before the experiment, partici-
pants were asked to read an information document outlining
the study’s design and associated risks and provide written
consent to take part. Ethical approval for the study was
granted by Queensland University of Technology’s Human
Research Ethics Committee (Approval No. 1500000236).
Experimental Design
A three-way repeated-measures design was applied to in-
vestigate the N170 response to photographed face stimuli
that violated or did not violate prior expectations of orien-
tation, lighting, and gravity. Each of the three independent
variables had two levels of manipulation: Orientation was
normal (depicted upright) or violated (inverted), lighting
was normal (illuminated from above) or violated (illumi-
nated from below), and gravity was normal (pulling down-
ward) or violated (pulling upward). Each participant was
exposed to a randomized presentation of faces, whereas
the evoked fluctuations in postsynaptic potentials emitted
by the brain and detectable at the scalp were recorded using
EEG. The dependent variables were the amplitude and
latency of the N170, a minimum peak occurring between
140 and 220 msec post stimulus onset and measured at left
electrode sites (P7, P9) and right electrode sites (P8, P10).
Stimuli
The face stimuli were derived from static images of four
male and four female models, photographed with a closed
mouth, neutral expression, and from a frontal viewpoint.
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The photographs were taken against a black backdrop
within four varied settings: illuminated from above with
the model standing upright, illuminated from below with
the model standing upright, illuminated from above
with the model hanging upside–down, and illuminated
from below with the model hanging upside–down. Soft box
lights with a diffuse filter and 135W bulb were positioned at
an equidistance within each setting, 110 cm from the face
at a 45° angle. Photographs were taken at eye level using a
Canon E05 SLR with an 18- to 55-mm lens, positioned on
an adjustable height tripod 150 cm from the face.
A series of photo manipulations were undertaken using
Adobe Photoshop CC 2018. The four types of images were
converted to grayscale, and a black oval frame was placed
over each face to remove the ears, neck, and hair. The im-
ages were scaled to size (W = 481 pixels, H = 500 pixels),
and the resolution altered to 72 pixels per inch. Each image
was aligned by the inner eye cornice to ensure the faces did
not deviate during the sequence and contribute to a pop
out effect. Faces were intensity normalized to ensure equal
mean and variance of grayscale scores. Because of discrep-
ancies in appearance after intensity normalizing, each
image was normalized to each other’s image to yield four
intensities for each setting, resulting in 256 total images.
All four versions of intensity were used in the study to
ensure it was correctly balanced. The four image types were
also rotated 180° to produce a reciprocal upright or inverted
image, creating eight conditions composed of different ori-
entation, lighting, and gravity interactions (see Figure 1). A
second set of duplicate images was produced with a small
red dot in the center of each face, to form the stimuli for
the red dot attention task.
Procedure
Each participant was fitted with an electrode cap, and an
electro-conductive gel was applied at each of the 64 scalp
sites. To allow the brain’s electrophysiological response to
the stimuli to be recorded, electrodes were then applied at
each of the 64 corresponding points on the cap. Participants
were instructed to remain still and fixate their gaze at the
center of the screen while they passively viewed a random-
ized sequence of stimuli. To ensure visual attention was
maintained, participants were required to complete a red
dot vigilance task. When a red dot was visible on the screen,
participants were instructed to respond by pressing the
space bar.
The randomized sequence of stimuli was presented in
two blocks, with an intervening 60-sec break provided
between the two blocks of images to allow the participant
to rest their eyes. Each block contained 288 images, com-
posed of 256 trial images (32 images for each condition)
and 32 red dot task image, which were later excluded from
analysis. Each image was presented for 600 msec, preceded
by a 400-msec interstimulus fixation point (see Figure 2).
PsychoPy software (Version 2) was used to deliver the task,
with the stimuli sequence presented on an HP widescreen
monitor with 1920 × 1080 pixel resolution. Participants
were seated in a darkened room approximately 100 cm
from the monitor.
EEG Recording and Data Analysis
A BioSemi Active Two Acquisition System (ActiView Version
7.06, BioSemi, 2013) with 64 channels and a sample rate of
1024 Hz was used to collect the EEG recordings. The inter-
national 10–20 electrode montage system was implemented
to determine scalp sites, with common mode sense and
driven right leg used as reference channels.
Brain Vision Analyzer 2.0 software was used to process
data. A bandpass filter from 0.1 to 40 Hz was applied to
remove high-frequency and low-frequency artifacts. A
Notch filter at 50 Hz was also applied to remove Australian
power-line noise. The detection and attenuation of eye
blinks was accomplished with independent component
analysis. Topographic interpolation was also carried out
on channels with high impedance to remove and replace
the noisy signal with a weighted average from other
Figure 1. An example of the
eight types of stimuli presented
for one of the eight models. The
three-letter labels provided
denote whether expectations of
orientation (first letter), lighting
(second letter), and gravity
(third letter) were normative
(N) or violated ( V). Labels were
not used during the
experiment.
Allen-Davidian et al.
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Figure 2. An example of three
consecutive stimuli presented
in a randomized sequence.
surrounding electrodes. Data for each of the eight condi-
tions was then divided into segmented epochs, which were
time-locked from −100 to 600 msec, with the period pre-
ceding stimuli presentation (−100 to 0 msec) functioning
as a baseline. An averaged ERP waveform was created for
each participant at each of the eight conditions across a left
hemisphere electrode cluster (P7, P9) and a right hemi-
sphere electrode cluster (P8, P10). These electrodes were
selected as they corresponded to lateral occipitotemporal
electrode sites commonly reported within the literature when
considering the N170 (Robinson et al., 2020; Johnston,
Overell, Kaufman, Robinson, & Young, 2016; Rossion &
Caharel, 2011). The N170 was calculated as an average
value across ±10 msec around the largest minima between
140 and 220 msec post stimulus onset (Luck, 2014).
Data consisted of the amplitude of the N170 measured
in microvolts (μV); the latency of the N170 was measured
in msec.
RESULTS
N170 amplitude and latency measures were analyzed by
four-way repeated-measures ANOVAs with factors of lat-
eralization (left vs. right), orientation (normal vs. violated),
lighting (normal vs. violated), and gravity (normal vs. vio-
lated). Lateralization did not have major effects on either
measure, and therefore, unless otherwise noted, the aver-
aged amplitude and latency collapsed over left and right
electrodes are reported below.
N170 Amplitude
Overall, these descriptive statistics are consistent with the
hypothesis, with the mean amplitude of the N170 largest
when orientation, lighting, and gravity expectations were
all violated (OV LV GV), and smallest when orientation,
lighting, and gravity expectations were not violated (ON LN
GN). However, visual depiction of means (see Figure 3) sug-
gested that this was not a linear effect as the amplitudes did
not consistently increase with the violation of more factors.
More specifically, results showed that violation of orien-
tation and gravity enhanced N170 amplitude, but these
effects primarily occurred when lighting was normal. The
four-way repeated-measures ANOVA yielded the following
significant main effects and interactions: the main effect of
Orientation, F(1, 24) = 21.67, p < .001, ηp
2 = .47; the main
Table 1. Mean and Standard Deviation of N170 Amplitudes and
Latency for Each Condition
Amplitude (μV)
Latency (msec)
Condition
ON LN GN
ON LN GV
ON LV GN
ON LV GV
OV LN GN
OV LN GV
OV LV GN
OV LV GV
M
−0.00
−0.86
−0.31
−0.43
−1.82
−1.26
−1.55
−1.92
SD
1.62
2.05
1.65
1.70
2.24
2.31
2.35
2.33
M
179.36
178.40
178.00
177.92
184.30
183.08
181.50
184.66
SD
14.70
13.83
14.09
16.37
13.40
12.41
10.41
12.98
The mean and standard deviation of the N170 amplitude
and latency, for each condition, are provided in Table 1.
OV LV GV indicates violation of orientation, lighting, and gravity, respec-
tively, whereas ON LN GN indicates no violation on any of these
parameters.
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Figure 3. (A) Grand averaged waveforms at electrodes P7, P9, P8, and P10, and the pooled grand average across these electrodes. (B) N170
amplitude means for each condition. Error bars represent within-subject 95% confidence intervals (Cousineau-Morey method for repeated measure).
OV LV GV indicates violation of orientation, lighting, and gravity, respectively, whereas ON LN GN indicates no violation on any of these parameters.
effect of Gravity, F(1, 24) = 4.29, p = .049, ηp
2 = .15; the
interaction between Orientation and Gravity, F(1, 24) =
5.91, p = .023, ηp
2 = .20; and the interaction between
Orientation, Lighting, and Gravity, F(1, 24) = 10.76, p =
.003, ηp
2 = .31. Among these, the three-way interaction is
important as it qualifies the other significant main effects
and interaction. That is, the three-way interaction occurred
because orientation and gravity significantly interacted only
when lighting was normal: Tests of simple interaction ef-
fects indicated that the two-way interaction between
Orientation and Gravity was significant when lighting was
normal, F(1, 24) = 7.43, p = .011, ηp
2 = .22, but not when
lighting was violated, F(1, 24) = 0.54, p = .47, ηp
2 = .02.
Focusing on conditions in which lighting was normal,
inspection of marginal means suggested that the two-way
interaction between Orientation and Gravity emerged
because the effect of Orientation was evident when gravity
was normal but not when gravity was violated (ON GN: M =
−0.00 μV; SD = 1.62 μV; OV GN: M = −1.82 μV; SD =
2.24 μV; ON GV: M = −0.83 μV; SD = 2.05 μV; OV GV:
M = −1.26 μV; SD = 2.31 μV). Indeed, tests of simple main
effects of Orientation in the LN conditions were significant
only when gravity was normal, F(1, 24) = 14.47, p < .001,
2 = .38 (ON: M = −0.00 μV; SD = 1.62 μV; OV: M =
ηp
−1.82 μV; SD = 2.24 μV), not when gravity was violated ,
2 = .01 (ON: M = −0.83 μV;
F(1, 24) = 0.84, p = .37, ηp
SD = 2.05 μV; OV: M = −1.26 μV; SD = 2.31 μV).
In summary, these results showed that orientation,
lighting, and gravity all contributed to N170 amplitude.
Orientation and gravity exerted their effects both through
Allen-Davidian et al.
309
interactions and on their own. Lighting modulated the
amplitude by interacting with orientation and gravity.
In addition, effects of lateralization were found in the
omnibus ANOVA as a significant interaction between
Lateralization and Orientation, F(1, 24) = 4.61, p = .042,
ηp
2 = .16, and a marginally significant four-way interaction
between Lateralization, Orientation, Lighting, and Gravity,
F(1, 24) = 4.17, p = .052, ηp
2 = .15. These interactions oc-
curred because effects of Orientation, Lighting, and Gravity
were generally clearer in the right hemisphere. For exam-
ple, the four-way interaction trend was driven by a strong
three-way interaction between Orientation, Lighting, and
Gravity in the right hemisphere. Tests of simple interaction
effects examining the three-way interaction within each
hemisphere were significant in the right hemisphere,
F(1, 24) = 14.47, p < .001, ηp
2 = .33, but not in the left,
F(1, 24) = 0.84, p = .37, ηp
2 = .05. However, because
the four-way interaction was only marginally significant,
detailed assessment of the three-way interaction was car-
ried out by collapsing data over left and right electrode sites,
as described in the foregoing paragraphs. Similarly, inver-
sion of faces caused a greater change in N170 amplitude
in the right hemisphere than in the left: Tests of simple main
effects of Orientation were significant in the right hemi-
sphere, F(1, 24) = 12.07, p = .002, ηp
2 = .33, but not in the
left, F(1, 24) = 3.82, p = .06, ηp
2 = .14(ON: M = −0.39 μV;
SD = 1.76 μV; OV: M = −1.564 μV; SD = 2.31 μV). These
lateralization effects did not alter interpretations of the
main findings about orientation, lighting, and gravity.
All the other main effects and interactions not reported
above were nonsignificant in the omnibus ANOVA.
N170 Latency
The mean and standard deviation of the N170 latency for
each condition, recorded across the left and right hemi-
sphere electrode clusters, are provided in Table 1. These
means provide support for the hypothesis that inverted
faces evoke a more delayed N170 latency than upright faces.
The four-way repeated-measures ANOVA on latency
showed that the main effect of Orientation was significant,
F(1, 24) = 27.31, p < .001, ηp
2 = .53 (ON: M = 178.42 msec;
SD = 14.75 msec; OV: M = 183.39 msec; SD = 12.30 msec).
There were no other significant main effects or interactions.
DISCUSSION
Our aim was to investigate how multiple, orthogonal vio-
lated expectations contribute to the enhancement of the
N170 in the FIE. To this end, the N170 ERP was measured
while participants viewed upright or upside–down faces,
which violated expectations of the direction of lighting
and gravity. We hypothesized that faces with more violating
expectations would evoke a larger N170, than faces that con-
formed to expectations, and that the N170 latency would
be influenced by the effects of orientation alone.
The largest N170 amplitudes were observed when orien-
tation, gravity, and lighting were all violated, and the
smallest when none of these attributes were violated.
However, this was not the consequence of linear addition
of the effects of the three factors. Rather, they modulated
N170 amplitude largely through interactions. Specifically,
although violation of orientation or gravity alone led to
increased N170 amplitudes, these factors also significantly
interacted such that the violation of gravity reliably in-
creased N170 amplitude only when orientation was normal.
Furthermore, this interaction occurred only when lighting
was normal. Thus, the current results showed that all three
factors are important for understanding ERP correlates of
the FIEs: Violating expectations about orientation or gravity
enlarged N170s, but simultaneous violation of both factors
did not necessarily result in further enhancement of N170
amplitude; and for N170 amplitude to be reliably modu-
lated, faces had to be lit from above. Finally, as predicted,
the N170 latencies were influenced by the effects of orien-
tation alone, with the N170 significantly more delayed to
inverted faces than upright faces. Overall, these findings
support the notion that the N170 is modulated by the viola-
tion of prior expectations.
These results challenge the prevalent view within the
literature that the enhanced N170 to an inverted face stems
simply from the disruption of face-specific, structural
encoding processes, which adapt to inversion by recruit-
ing alternate physiognomic feature processes (Sagiv &
Bentin, 2001) or eye-selective neurons (Itier et al., 2007).
Contrastingly, the current findings suggest that, when an
image of an upright face, photographed under normal
circumstances—above illumination with gravitational
pull from below—is inverted, multiple expectations are
violated. As upon rotating the image upside–down, the
face now appears illuminated from below and as though
gravity is pulling from above, which is a simultaneous
violation of orientation, lighting, and gravity expectations
( Jörges & López-Moliner, 2017; Brodski et al., 2015;
Cheron et al., 2014; Itier & Taylor, 2004).
The current findings are consistent with research by
Johnston et al. (2017), with both studies finding the ampli-
tude of the N170 was responsive to violated expectations.
The Johnston et al. (2017) study induced expectations
within each trial by displaying a progressive, implied trajec-
tory, with the final stimuli confirming or violating expecta-
tions of trajectory. Contrastingly, the current study used a
randomized design, with expectations of orientation, light-
ing, and gravity assumed to be established from consistent,
lifelong exposure to the effects of each factor. Evidence
suggests a gradual tuning to upright faces over inverted
faces (Itier & Taylor, 2004), an expectation that light origi-
nates from above (Brodski et al., 2015; Kleffner &
Ramachandran, 1992) and a sophisticated intuitive physics
model of gravitational effects (Russo et al., 2017; Cheron
et al., 2014). Thus, the current study expands upon
Johnston et al. (2017), demonstrating that the N170 appears
to be enhanced to violations of well-established lifelong
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priors, as well as to violations of immediate contextual-
based expectancies.
A predictive coding account of our findings is attractive to
us for a number of reasons. First, our own work revealing
that N/M170 amplitudes are strongly modulated by expec-
tation violations demonstrates the importance of contextu-
ally bound expectations in visual ERPs/ERFs (Robinson
et al., 2018, 2020; Johnston et al., 2017; Simpson et al.,
2015). This led us to ponder the question of whether FIEs
on the N170 amplitude might, in part, reflect expectation
violations, and led us to identify the issue that almost all
FIE studies involving photographic stimuli are confounded
by simultaneously violating expectations about lighting
and gravity in addition to the intended focus of study—
orientation, thus the inspiration and genesis of the current
study.
Second, predictive coding may provide a unifying frame-
work within which the gamut of cognitive phenomena
relating to receiving information, transmitting information,
understanding, planning, and acting may all be understood.
In a recent article, Trapp, Schweinberger, Hayward, and
Kovács (2018) suggest not only that predictive coding
may provide a framework for complementing existing cog-
nitive models of face processing but also that the field of
face processing provides an excellent testbed for honing
our understanding of the mechanisms by which predictive
neurocognition are instantiated. This is precisely because of
the wealth of data and the rich detail of the cognitive
models in the field. We endorse this view and believe that
the current study offers valuable insights in this regard.
A simplistic interpretation of a predictive coding account
would be that the effects of violation across multiple orthog-
onal stimulus attributes would be additive. That is to say
that the more attributes that are violated, the larger the
combined prediction error signal should be. Our results
partly conform to this pattern—the N170 is smallest when
none of the stimulus attributes are violated and largest
when all three are violated. However, it is not simply the
case that the violation of two attributes leads to greater
N170 amplitudes than when only attribute is violated.
Indeed, our data clearly demonstrate that, although the
orientation, lighting, and gravity all interact in modulating
the N170 amplitude, only orientation and gravity have inde-
pendent effects, and the effects of orientation are clearly
the largest.
It is interesting to speculate on the reasons why the
effects of violations of orientation influence the N170 ampli-
tude more so than violations of gravity or lighting. As adult
humans, it is very rare for us to look at an inverted face. It is
also very rare to see faces where normal expectations about
lighting are violated, and only a few hundred humans (i.e.,
astronauts) have been subjected to conditions where the
normal expectations with respect to the effects of gravity
on a face are violated. Let us focus first, however, on the
inverted face. We might occasionally see such a thing; for
instance, when strolling along a beach, or park, we might
pass another person lying with their body in such a position
that their face is “upside–down” relative to our own posi-
tion. However, if we were to engage socially with the
“upside–down” person, social norms dictate that we would,
almost certainly, immediately resolve a mutual positioning
that facilitated face-to-face interaction. Similarly, we might
see a face on a magazine cover that is “upside–down” rela-
tive to our position. However, if we wished to look at the
face, we would, almost certainly, reorient the magazine. The
key insight here is that, in the real world, expectation viola-
tions with respect to face orientation are likely to trigger
actions that aim to resolve the “error” and place the faces
in an “upright” orientation. Such considerations may hold
true for other objects for which there is a canonical orien-
tation. For instance, if we wish to look at a map (that is, un-
derstand), rather than simply seeing it (see Johnston,
Baker, Stone, & Kaufman, 2014), we are likely immediately
to act so as to reorient it to its canonical viewpoint. If we see
an upside–down car, we might be prompted to ensure that
people are safe. In such circumstances, orientation viola-
tions prompt behavioral responses.
What of violations of expectations with respect to the
effects of lighting and gravity upon the face? It is far less clear
that they signal the need for or desirability of action in the
same way that expectation violations with respect to orien-
tation do. Rather, such signals may reflect that a contextual
attribute of the face has fallen outside the “normal” bounds
of expected statistical likelihood and, although a little
surprising by consequence, represent a need to slightly
update the ongoing statistical model of those contextual
attributes, rather than to take immediate action. Unless
such anomalies lead to rapid real-world consequences that
merit them being bestowed a greater weighting and thus be
encoded as a paradigm-changing event. To our knowledge,
there have been no previous studies looking at the effects
of gravity on FIEs, but our results confirm that it may be
an important factor that warrants further attention.
Interestingly, a previous article (Enns & Shore, 1997) has
examined the effects of lighting direction and orientation
in a series of behavioral experiments. These researchers
reported that the effects of these two factors were some-
times additive and sometimes interacting, dependent upon
the specific task demands. This suggests that the effects of
lighting may be modulated by context—an idea that jibes
well with a predictive coding framework.
As mentioned earlier, a naive and simplistic interpreta-
tion of predictive coding might lead to the prediction that
the effects of expectancy violations across multiple orthog-
onal stimulus attributes might be additive. However, even
the briefest reflection reveals that the predictive coding
framework in no way presupposes such linear additivity.
It considers our perceptions as being resolved through
the interaction, cooperation, and competition of many
multidimensional statistical models within dynamic hierar-
chical or nested hierarchical contexts. Perhaps when faces
are inverted, error signals to other attributes may be mod-
ulated, attenuated, or suppressed, so as to prioritize the
error signal that promotes appropriate action, or, perhaps,
Allen-Davidian et al.
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our cognitive systems have multiple overlapping, partially
overlapping, and nonoverlapping statistical models relating
to how lighting and gravity affect nonrigid objects, and all
or any of these might interact with a statistical model of
“upside–down faces.” We do not suggest here that either
of these particular cases are responsible for the pattern of
results that observe—we simply propose them as exam-
ples of the types of complexities that conceivably come
into play.
As such, it is unclear to us that a lack of linear additivity with
respect to the effects of multiple orthogonal expectation
violations offers a strong argument against a predictive cod-
ing account. By the same token, we are also unsure that the
presence of linearly additive effects would represent a defin-
itive demonstration of predictive coding. Notwithstanding,
our results clearly demonstrate that two previously generally
overlooked factors—lighting and gravity—contribute to the
face N170 amplitude and to the N170 FIE. Moreover, we
demonstrate that expectation violations with respect to
two sole attributes (orientation and gravity) significantly
increase N170 amplitude. For lighting, the trend is in the
same direction, and it is possible that the failure to observe
a significant sole effect of lighting may reflect a lack of statis-
tical power. These are novel and potentially important
findings in an area where much is still unknown and opens
a new vista from which to consider the issue. From the per-
spective that “all models are wrong—but they more be more
or less useful,” we propose that the predictive coding model
may be useful in this context because it serves as a useful
“intuition pump” for generating new ideas and testable
hypotheses.
Conclusions
The current study demonstrated that the N170 amplitude is
modulated by a complex interaction of multiple expecta-
tions, which influence how a face is perceived, whereby
when violation of lifelong contextual priors occurred, a
larger N170 was elicited. These findings offer a plausible
explanation for the FIE and provides insight into the role
of contextual priors in visual perception.
Acknowledgments
We would like to acknowledge the gentle encouragement of the
Oily Rag Foundation (EN10006).
Reprint requests should be sent to Patrick Johnston, School of
Psychology and Counselling, Queensland University of
Technology, Brisbane, QLD 4059, Australia, or via e-mail: patrick
.johnston@qut.edu.au.
Author Contributions
Yasmin Allen-Davidian: Investigation, Methodology;
Project administration; Resources; Writing – Original Draft;
Writing – Review & Editing. Manuela Russo: Supervision;
Writing – Review & Editing. Naohide Yamamoto: Formal
analysis; Writing – Review & Editing. Jordy Kaufman:
Conceptualization; Writing – Review & Editing. Alan J. Pegna:
Conceptualization; Supervision; Writing – Review & Editing.
Patrick Johnston: Conceptualization; Project administration;
Supervision; Writing – Original Draft; Writing – Review &
Editing.
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