Introduction:
Psychology has demonstrated a long-standing interest in the remarkable ease with
which humans recognise faces. It is no mean feat to exhibit perceptual discrimination in
an object-class that is largely homogenous; as well as to associate and retrieve large
amounts of - sometimes arbitrary e.g. names – information to each recognisable face. The
published literature in face-research until now, can be crudely dichotomised into these
two areas: i) the nature of perceptual expertise in face-discrimination; and ii) decoding of
this perceptual input for information such as person-identity, race, social communication,
etc. Models have been conceived for these two broad stages of face-processing (e.g.
{Valentine, 1991 #201;Bruce, 1986 #202} and more recently, efforts have been made to
reconcile the two in a unified computational model of face processing – from ‘pixels to
person’ {Burton, 1999 #200}.
What is often neglected in models of face-processing, however, is a stage that can
be reasonably assumed to take place even before face-perception. Before a face can be
processed, it must be attended to. The processed face is not always presented at the centre
of fixation, as an isolated percept, as most models of face-processing seem to implicitly
assume. A naturalistic visual scene is often “cluttered” with a variety of non-face images.
Thus, it is paramount for a face to be detected and oriented towards first, before it can be
processed. It is this stage of face-processing that this dissertation concerns itself with.
More specifically, it is the aim of the experiments reported here to investigate the
relationship between spatial-attention and face-detection. To do so, face-detection shall
be studied within experimental designs more traditionally associated with spatialattention.
In this chapter, the nature of face-detection will be first be illustrated in a
pioneering study on the topic; that is, the face-detection effect. Converging findings on
the same theme will be presented and their implications discussed. Following this, two
current face-detection models will be considered. Having discussed face-detection as a
demonstrable process as well as its role in face-processing models, an attempt will be
made to understand the mechanics of this process. It has been suggested that facedetection occurs easily because spatial attention automatically orients to face-stimuli (de
Gelder & Rouw, 2001). This claim will be investigated through a selective review of
experiments that cover the broad themes of spatial-attention and face-processing: visualsearch, ERP studies, change-detection, neuropsychological patient testing.
What is face-detection?
The term face-detection implies several things. Firstly, it refers to the cognitive
stage when a person is only just conscious of the presence of a face. At this point, there is
no recognition of the person or arguably, even the object-type. Also, implicit to the term
“face-detection” is the assumption that this is a process that is special to faces as a visual
object; or at least, that a face-like visual pattern fulfils a set of criterion that grants it
privileged access to conscious awareness. Succinctly, it is the ability to be aware of the
presence of a face prior to actually registering that the detected image is a face; or any
particular person’s face for that matter.
Last but not least, it suggests that the visual system can register the presence of
complex configurations - as opposed to line orientations and blobs {Hubel, 1963
#150;Hubel, 1968 #151} – even early on in the visual processing stream, depending the
perceived configuration’s identity. This runs counter to the popular notion that perception
is entirely bottom-up; that is, humans reconstruct their visual environment from binding
simple features into complex configurations. The following paragraphs will present
experimental support for the claim that the structural configuration of a face can facilitate
its detection even prior to classification.
Are Faces Special?
The human face is a visual pattern with obvious biological significance. Whether
or not the perceptual processes pertaining to a face-pattern is special continues to be a
topic that is much debated over. There are certainly reasons to believe that faces might be
perceived differently from other objects and a brief selection will be presented here. The
following is only meant to introduce the reader to a selective background of the issues;
primarily, to explain why face-processing is considered by some to be special from
general object processing. Not everyone is in agreement with this view and
comprehensive reviews of this topic are readily available elsewhere in the literature (e.g.
{Kanwisher, 2000 #170;Tovee, 1998 #172}. To justify this claim, it is necessary to prove
that there exists processes supporting face-perception that is not utilised in the perception
of other objects.
Evidence supporting the position that faces are special, stems mainly from three
lines of enquiry. From behavioural findings, a common finding is that recognition
accuracy for faces suffers a disproportionate decrement with a vertical image-inversion,
in comparison to other objects that are similarly mono-oriented e.g. houses {Yin, 1969
#157}. This has led to the claim that the processes driving face-recognition are more
sensitive to the configural layout of the image’s component features, compared to general
object-recognition. This is not to say that face-recognition does not rely on featural
information at all. Rather, face-processing relies so heavily on the configurational
information present in a face-image, such as the spatial relations between features, that an
entirely unfamiliar face-percept can be derived merely by fusing the top and bottom
halves of highly familiar faces (cf. {Young, 1987 #175}). This effect can be negated
simply by inverting this ‘chimeric’ face, validating both the assumption that inversion
specifically distorts the configural information present in a face-image as well as the
reliance of face-processing on this information. Even when learning face-features e.g.
nose, it was reported that it was better learnt when presented within the context of an
upright face compared to an inverted face {Tanaka, 1993 #177;Tanaka, 1997 #178}.
Given the vital relevance of such studies with dissertation, the effects of face-inversion
and how it affects configural processing will be covered in greater detail later. Suffice to
say for now, that face-processing is special from object-processing in its particular
reliance on configural information.
Alternatively, claims that face-processing is special can also be obtained at the
neuronal level, from the use of a host of neurophysiological techniques. Functional
neuroimaging investigations have reported regions in the right fusiform gyrus that
respond selectively to face-images, at least twice as strongly for faces as compared to a
variety of non-face object stimuli {Kanwisher, 1997 #179;Sergent, 1992 #180}. Scalp
ERP readings and MEG studies that benefit from a finer temporal resolution of eventrelated response also corroborate these results by similarly showing selective responses to
the presentation of upright faces {Liu, 2000 #182;Bentin, 1996 #181}. Single-cell
recordings of the primate brain also reveals cells at the neuronal level, in the temporal
cortex, that fires exclusively to faces and not other objects, rendering further support of
the specificity of face mechanisms {Perrett, 1982 #164;Perrett, 1984 #165}. The
existence of specific neural mechanisms that respond preferentially to the presence of
faces accords with the notion that face-processing is special and different from object
recognition (however, see {Tarr, 2000 #183} for an alternative view). In fact, Haxby and
colleagues {Haxby, 2000 #184} conducted a detailed review of neurophysiological
studies pertaining to face-processing and concluded that there was sufficient information
to propose a plausible model of a face-specific neural system, fully illustrating the
relationships of specific neural regions to corresponding aspects of face-perception.
Finally, the double dissociation between neuropsychological patients with specific
impairments of prosopagnoia and general object agnosia distinguishes face-processing as
an independent process. Prosopagnosia was first reported by Bodamer {Bodamer, 1947
#171} and refers to a neurological condition whereby sufferers experience a specific
deficit in identifying familiar faces (for recent review; see {De Renzi, 1997 #152}. By
comparing different patient groups that suffer from selective cognitive impairments, a
case can be made for separable processes. For example, lesion patient (C.K.) suffers from
severe object agnosia and cannot recognise simple line drawings of everyday objects but
retains the ability to recognise familiar faces. This, is in stark contrast to a prosopagnosic
such as patient L.H. demonstrates a reverse pattern of cognitive performance
{Moscovitch, 1997 #153}. The existence of such double dissociations can be treated as
evidence for the uniqueness of face-processes, from general object recognition. Later on
in the chapter, we shall examine how further testing of prosopagnosic patients on a
variety of face-processing tasks has allowed theoretical models incorporating the process
of face-detection to be formed.
The findings presented here is merely a sample of the reasons that has motivated
the research of face-perception as a distinct system of processes from general object
recognition. To surmise, face-perception is believed to be more reliant on the abstract
configural information contained within the visual image, compared to general object
recognition. In addition, there exists specific neural substrates that respond selectively to
faces and not other objects. Lesioning of these specific regions can result in a specific
neurological disorder i.e. prosopagnosia, that exhibits face-specific processing deficits.
Hence, the visual image of a face is commonly believed to be processed differently from
any other object. Still, the question remains as to where specifically and how early on in
the visual processing stream are faces accorded their special status. Next, we will discuss
how the face-pattern can be treated preferentially, even at an early perceptual stage.
Face Detection Effect
While there are those who believe that face-recognition is special and different
from the recognition of other object stimuli (e.g. {Ellis, 1989 #141}, the distinction is
commonly thought to involve higher cognitive processes of recognition rather than lowlevel visual processes such as reflexive orienting. The traditional viewpoint, such as
implied by Bruce & Young’s (1986) popular model, is that face-processing is a special
topic of discussion only after it has been structurally encoded and that the processing of
structurally encoding a face is no different from that of any other object.
In the late 1980s, several studies mooted the possibility that faces could enjoy
privileged status at an early visual processing stage, prior to being structurally encoded
and identified. In the general experimental paradigm, participants were presented with a
target stimuli that appeared on either side of a fixation cross and were expected to make a
two-alternative forced choice (2AFC) response corresponding to the target’s position
whenever they detected the presence of a visual stimuli. By introducing a backward
visual mask shortly after target presentation, presentation times of the target stimuli could
be varied for each participant until a consistent accuracy performance of 75% was
achieved. This measure was termed the detection threshold. Comparing the detection
thresholds for different visual patterns, the main findings were that participants had lower
detection thresholds for a normal face stimuli (38ms) in comparison to an equally
complex visual target; that is, a scrambled face comprising the same parts (56ms)
{Purcell, 1986 #27}. A later study replicated the same findings using an inverted face as
a comparison stimuli, showing that it is specifically the upright and normal configuration
of a face features that enhanced its detection {Purcell, 1988 #24}. In a later section of this
chapter, it will be seen that the face-detection effect can be demonstrated, even in
prosopagnosic patients who suffer from specific deficits in face-recognition and were
previously believed to have lost all face-processing related processes {de Gelder, 2001
#33;de Gelder, 2000 #34}.
The crucial point to note in these experiments is that successful task completion
did not depend on identifying the target. In fact, when participants were presented with
the same experimental trials and asked to classify the targets according to identity, the
classification threshold for upright faces were significantly longer than its corresponding
detection threshold (Experiment 5: Purcell & Stewart, 1988). The significance of these
findings is that the configural structure of a face facilitates its detection even before the
structure is fully perceived to allow for identification.
In a more recent experiment, the same findings were replicated with the use of
smiley faces (see Fig. 1.2 for examples) demonstrating that this effect is not dependent on
a detailed or veridical face-pattern (Experiment 1:{Shelley-Tremblay, 1999 #121}.
Target stimuli were presented for a fixed duration (16ms) before the application of a
backward visual mask. This experiment differed from those conducted by Purcell &
Stewart (1986; 1988) in several ways. Firstly, trials varied for target presence and
participants were only required to indicate whether or not a stimuli was presented
between the start of trial and the backward visual mask. Hence, no localisation decision
was necessary. Also, participants were requested to provide a subjective rating for each
target stimuli’s clarity on a scale of 1-5, when deemed present. Finally, fixed
measurements of detection accuracy were taken across 5 different stimulus onset
asychrony (SOA) between target stimuli and mask instead of the detection threshold
measure. In support of previous findings, measures of detection accuracy were higher for
normal upright smiley faces than scrambled and inverted faces. In addition, subjective
ratings for clarity were similarly higher for normal upright smiley faces over scrambled
and inverted faces.
To understand the face-detection effect, it is important to understand the timecourse of this effect. One way of doing so is by directly measuring single-cell responses
of face-sensitive neurons when faced with this task. Preceding the study conducted by
Shelley-Tremblay & Mack (1999), the above behavioural findings were extended by a
series of experiments that utilised the same experimental procedure, but with both
macaques and humans {Rolls, 1994 #7}. Using macaques allowed for single-cell
recordings to be retrieved from a neuronal population in the macques’ superior temporal
sulcus that were already known to show preferential firing to faces. The primary aims of
this experiment were to compare differences of neural firing rates in relation to variations
of the experimental parameters, such as to better understand how neural events
corresponded with the behavioural findings of Purcell & Stewart’s (1996;1998)
experiments. Thus, the firing rates of face-selective neurons were compared across a
range of SOAs between a photograph of an upright/scrambled face (16ms) and a visual
mask. The main findings were as such: i) the introduction of a backward visual mask
served to attenuate neural-firing such that the neuron would stop firing shortly after the
introduction of the mask; ii) at short SOAs (i.e. 20ms), neural firing rates were
indiscriminate for normal and upright faces; iii) gradually, the neurons fired more
responsively to the upright face over the scrambled face, as the SOA is increased through
60ms. When the same experiment was conducted with human participants, their findings
coincide with Shelley-Tremblay and Mack’s (1999) for measures of judged clarity; but
more importantly, upright faces were judged to be significantly clearer than scrambled
faces only within the same critical SOA range of 40-60ms. This also corresponds with the
psychophysical findings of Purcell & Stewart (1986; 1988) that demonstrated the
emergence of the FDE in the temporal window of 40-60ms. Considering the
neurophysiological and behavioural data in concert, we could surmise that the rapid
timing of face-detection (that is, the point in time when the image is deemed sufficiently
clear to register in the consciousness) bears relation to when firing rates of face-specific
neurons begin to discriminate in favour of normal upright faces.
The face-detection effect claims that the early stages of the perceptual system is
sensitive to the structure of a face. No doubt, this sounds like a contradiction in itself.
After all, why should and indeed, how could the identity or object-class of a visual
pattern i.e. faces facilitate its detection prior to its identification? In other terms, how can
a face speed along its own detection by virtue of its structure before it is registered as a
face, at least on the conscious level. In neurophysiological studies describing the
architecture of the visual cortex claim, the early stages of the primate visual pathway (i.e.
V1) is only known to be responsive to edges and blobs, not complex patterns such as
faces {Dow, 2002 #142; Hubel, 1968 #8}. Traditional accounts of visual object
recognition will argue that a complex figure i.e. face can be perceived only when
mentally reconstructed from these basic sensory inputs (e.g. Marr, 1985). The facedetection effect, however, imputes that the face-pattern has an influence, much earlier in
the visual pathway than previously assumed. To surmise, the mere configuration of a
face-pattern enjoys certain privileges in the early stages of visual processing. Specifically,
prior to its identification. This implies an early face-specific process in the visual stream
that precludes face identification. Moreover, this effect operates even with basic faceschemas i.e. smiley faces that are not strictly speaking, faces. This effect also has a
specified time-course of between 40-60ms, during which a face-pattern is considered to
be significantly clearer than other images comprising the same visual components.
1.2 Corroborating Evidence
In the previous section, the face-detection effect was examined in detail.
Essentially, it raises the possibility that human perceivers can utilise the structural
configuration of a face to facilitate its detection even before the same image is fully
identified as a face. This effect is believed to reflect face-selective processes that emerge
early on in the visual processing stream. Bearing this in mind, we will now consider other
findings in the face-research literature spanning across a wider breadth of methodologies,
that could render support for the same claim.
Developmental studies
Another worthwhile question to ask is whether this privileged status is conferred
to faces as a result of object familiarity or if it is, unlike the process of face-recognition
that requires learning, an innate function. Studies that investigate neonatal visual
preferences is one way for testing the independency of face-processes that motivate
detection and identification.
Neonates are not expected to possess the extensive experience with faces that
adults do. Despite this, Goren, Sarty & Wu {Goren, 1975 #155} have reported that
newborns (3 – 27 mins) tend to monitor simple face-like patterns over scrambled images
comprising the same elements and controlled for symmetry. More speculatively, this
sensitivity enables infants (as young as 12.5 – 201 hrs) to recognize their mother’s face
{Bushnell, 1989 #203} and by the age of 17-22 weeks, discriminate between different
faces {Fagan, 1972 #204}. Thus, it can be assumed that prior to the acquisition of any
extensive experience with face-patterns, infants do in fact orient towards face-patterns.
Some authors might argue that perceptual precocity of this nature reflects an
innate selectivity for socially significant stimuli i.e. face-like patterns (Bowlby, 1969;
Fantz, 1961; Gibson, 1969). After all, there is an ecological benefit in doing so and it is
not unreasonable to argue for an evolved predisposition towards faces that is hard-wired
into the neural system. Termed the structural hypothesis, proponents of this view argue
that face-like patterns have privileged access to the visual system; perhaps due to their
social significance. There is, however, a more parsimonious explanation known as the
energy hypothesis that focuses on the limitations of an early visual system and how an
infant’s visual preference is more tightly governed by what it is, effectively, capable of
sensing {Kleiner, 1987 #156}.
Kleiner (1987) argues that early affinity to a face-like pattern can be explained,
without recourse to the stimuli’s social significance, simply by the fact the visual
properties of a face-like stimulus (measured in terms of spatial frequencies) is in sync
with what early infants are able to see. The early visual system can be surmised as being
particularly responsive to patterns of low spatial frequencies and high contrasts {Banks,
1985 #145;Banks, 1978 #143;Banks, 1983 #144}. Kleiner (1987) does not dispute that an
infant is likelier to orient towards a face-like pattern over a simple lattice pattern.
However, she argues that this is by virtue of the amount of visual information that
‘survives’ the filtration imposed by the infant’s visual limitations in acuity and contrast.
A face-like pattern is claimed to survive this process far better than any other patterns.
However, Kleiner (1987) does not venture to suggest if there might be comparable
image-patterns with the same level of ‘energy’ as face-patterns that could result in
comparable preferential viewing in infants. In Kleiner’s (1987) study, preferential
viewing levels of
infants (mean age =
1.7 days) were
compared on a set of
images that were
carefully controlled
for levels of
Fig 1.2: Experimental stimuli used in Kleiner
amplitude and phase
(1987): A – schematic face figure; B – complex lattic figure;
(see Fig 1.2 for examples). Phase levels determine the configural layout of an image
C – hybrid image of image A’s phase and B’s amplitude
while amplitude levels determine the level of image contrast or stimulus ‘energy’ levels.
levels; D – hybrid image of A’s amplitude and B’s phase
In her study, infants preferred the images in the order of A>D>(B=C).
levels
Firstly, it should be noted that her findings replicate early findings of how infant
observers will tend to prefer a schematic face image above all the other images. What is
interesting though is that the hybrid image D should be viewed preferentially over images
B and C, when most adult observers would rate hybrid image C as being more face-like.
These findings are not easily interpretable. Kleiner (1987) accounts for these findings by
claiming that sensitivity to a face-configuration is a secondary criterion in the
prioritisation of viewing preference. She claims that infants are first sensitive to the levels
of perceptual ‘energy’ contained within an image but thereafter, they will attend
preferentially to the face-configuration.
The debate concerning precedence of a face-configuration in infant visual
preference was more recently resolved. A series of experiments were designed with the
specific aim of directly comparing the influence of a normal face configuration versus
optimal spatial frequencies on infant viewing preferences {Valenza, 1996 #207}. In the
first few experiments, the above findings were replicated and infants were found to prefer
a schematic face configuration over an equivalent image with misplaced features, as well
as patterns that contained spatial frequencies tailored to fit an infant’s early visual system
over those that did not. By subsequently juxtaposing these same images that elicited these
visual preferences, it was found that it was the face-like pattern that captured the infants’
attention, rather than the pattern of optimal spatial frequency. Thus, there is strong claim
to the existence of an early face-monitoring system that primes infants to the presence of
a face-image, independent of the limited range of spatial frequencies that characterise the
early visual system.
Overall, all the evidence presented so far supports the existence of an early
sensitivity to an upright face-configuration in infants, that cannot be attributed to
perceptual face-learning. The simple explanation for this phenomenon is to postulate that
humans possess an innate visual affinity to faces and that this corresponds with a built-in
neural correlate. Certain neurological studies support this view and has found
hemispheric specialisation to face-processing within the first few months of infancy {de
Schonen, 1986 #206;de Schonen, 1987 #205}. Despite this proof of a precocious
sensitivity to the face configuration, studies that compare different age-groups for
identification skills have demonstrated that perceptual expertise commonly associated
with face-recognition does not fully develop until around 10-11 years of age {Feinman,
1976 #209;Ellis, 1990 #208}. In fact, young children are not believed to capitalise on the
more subtle but more disciminative configural differences between highly similar faces
as a means for identification until puberty, relying instead on inconsistent featural
differences such as hairstyles {Flin, 1980 #211;Carey, 1980 #210}; although, see {Flin,
1985 #212} for a slightly improvised account). Hence, even in developmental studies do
we notice this distinction between the early visual preference for the face-configuration
i.e. face-detection, and the ability to identify and discriminate a face from highly similar
counterparts i.e. face-recognition.
Change detection
It is sometimes believed that conscious perception cannot occur without attention.
A group of phenomenon that support this notion includes: inattentional blindness {Mack,
1998 #194}, the attentional blink (Raymond, Shapiro, & Arnell, 1992; Shapiro, 1994),
repetition blindness (Kanwisher, 1987; Kanwisher & Potter, 1990), change blindness
{Simons, 1997 #195;Rensink, 1997 #193} and visual-neglect that occur with
neuropsychological patients (Rafal, 1998; Rafal & Robertson, 1995; Bisiach, Luzzatti, &
Perani, 1979). Generally, these studies operate on the assumption that visual attention can
be circumscribed by a zone of finite spatial parameters. Thus, participants can be
empirically tested for awareness or change-detection of stimuli that fall outside this “zone
of attention”.
Experiments – such as in inattentional blindness {Mack, 1998 #194} - usually
involve participants attending to a specified spatial region, where a task-relevant stimuli
is located. During the experiment, an unexpected (or the critical) stimuli appears and
participants are post-experimentally quizzed for their conscious awareness of this
unexpected event. The consistent finding was that participants did not notice the
appearance of the critical stimuli when it appeared in a different region from the studied
stimuli, but did so when it was close to the attended region. In order for a visual object to
reach consciousness, it is necessary to first attend to the given object. This ties in with our
current interest with the face-detection effect. By virtue of their configuration, perceivers
are highly conscious of a face’s presence in a visual scene, a well-replicated finding in
tests for the face-detection effect {Purcell, 1986 #27;Purcell, 1988 #24;Shelley-Tremblay,
1999 #121}. Concurring with the face-detection effect, was Mack and Rock’s 1998) lack
of success in replicating findings of inattentional blindness with upright faces. Despite
their best efforts to draw attention away from the critical stimuli i.e. faces, their
participants’ attention were always inevitably drawn to the faces’ presence. The only
manipulation that rendered faces susceptible to inattentional blindness was an imageinversion of their natural configuration. Such findings indicate that there might be a
spatial component to the face-detection effect.
The upright face-configuration is particularly resilient to a good variety of
experimental paradigms designed to induce change blindness. Another good example is
the use of a flicker paradigm introduced by Rensink and colleagues {Rensink, 1995
#197;Rensink, 1997 #193}. In the flicker paradigm, the presentation of an original image
repeatedly alternates with the same image, modified. Interspersed between the two
presentations is a blank field interval that prevents change-detection from the use of lowlevel motion signals. During each trial, the observer is allowed to view this repeated
sequence for as long as is required to identify the modified differences between the
original image and its modified counterpart. Traditionally, such experiments are used
with real-world scenes and the main finding is that the flicker across the two disparate
images can obscure even large visual changes, such that it takes a surprisingly long time
for obvious changes to be registered. Predominantly, changes involving objects of
marginal interest are more susceptible to the flicker effect than objects of central interest
{Rensink, 1997 #193}. Unfortunately, there has not been a systematic study to qualify
what counts as an object of marginal or central interest. Objects that are classified to be
of central interest are simply those that have been mentioned in the verbal description of
each scene, by at least 3 or more participants and objects of marginal interest are those
that have not met this critertion. This definition is circular and does not indicate why
certain objects should be of central or marginal interest. Predictions in accordance with
the face-detection effect would predict that an upright face configuration should be of
central interest and more resilient to the flicker paradigm than an equally complex image
e.g. inverted/scrambled face.
Using face-stimuli as the sole critical image in the flicker paradigm could yield
interesting results concerning the aspect of faces that are most resilient to changeblindness. In one such experiment, the main modification between the original faceimage and the transformed comparison stimuli was in the spatial relationships between
features {Davies, 2002 #196}. Either the eyes or the mouth position was shifted a fixed
and minute distance, either upwards or downwards. Thus, the change that had to be
detected was of a configural nature as the particular features were no different across both
sequentially-presented images. In addition, the paired images were presented in either
their normal upright orientation or inverted. The results in this experiment were in strict
correspondence with what we would expect from previous studies. Visual salience of a
face was a privilege associated with an upright face configuration, such that changedetection performance for configural changes was consistently better for upright
compared to inverted faces, on both measures of detection accuracy and latency. Hence,
an upright face-configuration is automatically paid better attention then an inverted faceconfiguration, particularly for configural changes. This finding is reiterated in another
study wherein it was found that an inversion-transformation of the upright configuration
severely impaired change detection for changes in eye and mouth positions {Barton, 2003
#198}.
The performance findings for the change-detection of featural modifications
across inversion transformations are less clear. Davies and Hoffman (2002) found that the
upright configuration sensitized observers to featural changes such as the localised
inversion of features i.e. eyes and mouth, compared to inverted faces. However, it could
be argued that localized inversion of the eye and mouth region are, in fact, configural
rather than featural modifications. As Davies and Hoffman admits in the same paper,
localized inversions of eyes and mouth can also disrupt configural information as
demonstrated in Thompson’s {Thompson, 1980 #199} classic illusion. In his illustration,
he introduces the use of these local inversions to confer disproportionate grotesqueness
upon Magaret Thatcher’s face, that is immediately negated upon inverting the face.
Hence, Davies and Hoffman (2002) recommended the use of featural changes such as the
lightening of mouth colour or change in eye-colour instead, a suggestion that was
promptly picked up in Barton et al’s (2003) paper. In their experiment, face-inversion had
no significant effect in reducing change-detection performance for featural changes that
modified only for eye-colour and the lightness-contrast of the mouth. To surmise, the
high visual salience of an upright face is particular to its configuration and not its features.
Inversion of the face-configuration removes this privileged status and renders changes at
the configural level just as susceptible to inattentional blindness as those on the featural
level.
So far, the findings under discussion in this section have dealt the detection of
changes within a single face-image, upright or inverted. The main finding has been that
there is a strong sensitivity to changes in the configural information that defines a facepattern and that this is mitigated by the upright face-orientation. Using the same flicker
paradigm, other investigators have also questioned whether an upright face-pattern is
more salient than other non-face objects contained within the same visual scene. In a
recent study, the flicker paradigm was conducted with a circular array of 6 different
objects positioned equidistant from and evenly spaced around a fixation point. Each item
was a member of a different class-category of namely: faces, food, clothes, musical
instruments, appliances and plants. Half the trials involved a change in one object item
between the two repeated serial visual presentations whilst the other half did not depict a
change at all. Overall, a change in the face item resulted in more accurate changedetection as well as shorter detection latencies, compared to all other object items (Expt 1:
{Ro, 2001 #73}). Yet again, any benefit for the change-detection of face-items was
completely eradicated when the objects were presented as inverted images (Expt 2b: {Ro,
2001 #73}). Thus, the key to a face’s visual salience clearly lies in its upright
configuration. Interestingly, when participants were asked to rate each object-category for
change-detection difficulty, participants were not conscious of their performance and did
rate faces an easier object-category to detect changes for. It can be derived from this that
the participants in this study were not relying upon their perceptual expertise in facerecognition to detect the changes in visual array. Rather, their privileged sensitivity to the
face-configuration precedes explicit awareness and is more related to the mechanism of
face-detection.
Visual neglect
The difficulties posed to participants in solving change-detection experiments are
often to inattention
Prosopagnosia & Face-detection
Given the disproportionate importance of configural processing to successful face
recognition as compared to object recognition, it has also been suggested that
prosopagnosia reflects a general loss of configural processes and a regression to the use
of part-based processing in face recognition {Levine, 1989 #161}. In fact, the loss of a
face-inversion effect – described in the preceding section – has been offered as a
diagnostic marker for normal face-processing {Yin, 1970 #158}. This argument, however,
is circular and as we shall soon discover, fails to fully appreciate the complicity of
prosopagnosic deficits. Furthermore, there is proof that under certain conditions, certain
prosopagnosic patients do possess a sensitivity to configural information and in fact,
cannot adopt a feature-based processing strategy even if there is a task-benefit in doing so.
Levine and Calvanio (1989) based their claim that prosopagnosia was a general
impairment of configural processing when their patient L.H., a prosopagnosic patient,
performed badly on a test battery of standardised configural processing tasks.
Nonetheless, these findings were rendered inconclusive when subsequent testing of the
same patient (LH), but only on basic perceptual tasks that also required configural
processing e.g. Kanisza-type visual illusions, resulted in performance equivalent to
normal controls {Etcoff, 1991 #185}. Unfortunately, both studies were concerned with
LH’s general configural processing abilities and only tested him with line drawings,
abstract figures and Kanizsa-type visual illusions, instead of with faces. All that can be
concluded from these studies is that LH does not suffer from general perceptual deficits
such as those experienced with apperceptive and integrative agnosia (e.g.{Riddoch, 1987
#186}. It would have been more relevant to have tested LH’s configural processing in a
way that was relevant to face-images.
The truth is, testing prosopagnosia patients on face-configuration tasks reveal a
far more complex picture than one would imagine. If it was true that the emergence of
prosopagnosia simply signalled the complete loss of configuration-based processing, at
least with regards to faces, then we ought to expect prosopagnosic sufferers to process
inverted faces no differently from upright faces. Specifically, prosopagnosia should result
in the loss of the inversion-inferiority effect that is well-documented in normal faceprocessing {Valentine, 1988 #154}. Instead, certain prosopagnosic patients have been
reported to reflect a reverse set of cognitive performance; that is, an inversion-superiority
effect (for example: patient LH, {de Gelder, 2000 #35;Farah, 1995 #176;de Gelder, 2000
#36}; patient RP, {de Gelder, 2000 #34}). In these reports, prosopagnosic patients
performed better with inverted faces than upright faces on sequential matching tasks of
unfamiliar faces. Furthermore, prosopagnosic participants are also impaired on face
feature-matching tasks when the feature is found within the context of a face. Again, this
is a reverse of another well-known advantage i.e. face-context effect, related to the use of
configuration-based processing with upright faces {Homa, 1976 #167}. Even when
presented with the explicit instruction to only attend to face-features, prosopagnosic
patients are detrimentally affected by the presence of the upright face-configuration.
Clearly, prosopagnosic victims do not suffer from a complete loss of sensitivity to a faceconfiguration. In addition, rather than demonstrating a general regression to the exclusive
use of feature-based processing, certain prosopagnosic patients are, in fact, unable to
avoid using configuration-based processes even when it is task-inefficient to do so.
Still, there is a class of prosopagnosics who do not demonstrate the inversionsuperiority effect. Known as developmental prosopagnosia (DP), this syndrome differs
from the more common form of acquired prosopagnosia (AP) in that its sufferers have
no medical history of sudden neural injury despite sharing a face-specific deficit. Thus,
DPs’ face-specific impairment are believed to be of a purely developmental origin.
Unlike APs, DPs do not possess a pre-trauma face-learning experience as they have never
been able to recognise faces. Thus, a comparison study of a DP (patient A.V.) and a AP
(patient R.P.) was carried out to find out whether the reverse pattern of inversion
superiority in APs had anything to do with pre-trauma face-learning {de Gelder, 2000
#34}.
First of all, it must be noted that the face-detection effect was noted with both
patients, A.V. and R.P. as well as the 15 normal participants recruited as controls. Thus,
both classes of patients are not completely insensitive to configurations; at least, not to
that of a face-like pattern. This bolsters the supposition that face-detection is a process
that is independent of learning and served by early perceptual processes. On simultaneous
and delayed matching tasks of unfamiliar faces, it was found that R.P. replicated the
previous performance of other APs (e.g. L.H. {de Gelder, 2000 #35;de Gelder, 2000
#36;Farah, 1995 #176}) by showing better performance when faces were inverted
compared to when they were in their normal upright position. Normal controls on the
other hand, replicated the classical findings of inversion-inferiority and did poorer with
inverted faces instead (cf. {Yin, 1969 #157}. Patient A.V., however, displayed
performance superiority for neither upright nor inverted faces-images, displaying a pure
insensitivity to face-orientation on matching tasks.
On a different task, participants were required to match facial features contained
either within an upright or inverted face-context. Again, only patient R.P. and the normal
controls showed an orientation-effect, but with opposite trends of performance. Whilst
normal controls benefited from seeing the feature in an upright face-configuration, patient
R.P showed the reverse pattern and performed better with seeing the feature contained
within an inverted face-configuration. In accordance with the earlier results, patient A.V.
did no better or worse with matching face-features that were enclosed by either upright or
inverted face. When considered in concert, the opposing trends in performance displayed
by patient R.P. and the normal controls can only be attributed to the face-learning
experience that patient A.V. lacks. There are developmental theories that could explain
this (e.g. see {Diamond, 1986 #188}. Briefly surmised, it claims that extensive
experience with faces results in perceptual expertise that is primarily characterised by an
over-reliance on configural information contained within a face; that the imagetransformation inversion specifically distorts. It is the ability to retrieve such abstract
information that facilitates fine within-class object discrimination to take place. There is
data to support this perspective. Configural processing as measured by the inversion
effect is known to increase with age {Carey, 1994 #190;Carey, 1977 #189}. Therefore,
patient A.V. who does not possess the extensive experience with face-processing in the
manner that normal controls do, has to rely entirely on a feature-based strategy in the
matching tasks and remains completely unaffected by face-orientation. While this
explains the difference in performance between the normal controls and developmental
prosopagnosic A.V., it does not offer a ready explanation for patient R.P.’s paradoxical
inversion superiority effect.
Interesting, both developmental and acquired prosopagnosia exhibits the facedetection effect which is central to this dissertation. This has allowed de Gelder and
Rouw {de Gelder, 2001 #33;de Gelder, 2000 #34} to conceive a model to explain the
effects of inversion-superiority noted in acquired prosopagnosia, but not in
developmental prosopagnosia (see Fig 3). In this model, the perceiver is able to utilise a
part-based or whole-based approach to analyse any visual image presented depending on
whichever is the more effective in accurate object identification. This mirrors the holistic
hypothesis presented by Farah and colleagues that argues for a whole-based processing
bias for faces because faces are represented in memory as a whole Gestalt unit {Farah,
1998 #192;Farah, 1992 #191;Farah, 1995 #176}. However, they did not fully explain
why faces and not other objects should be represented in memory as a holistic
representation to begin with.
The involvement of an innate face-detection process in the early stages of
development of object representation offers a reasonable explanation. The precocious
face-detection ability allows infants to perceive and encode faces as a Gestalt unit. In
time, this lends to a shift in whole-based processing for faces that develops with facelearning experience (cf. {Flin, 1980 #211;Carey, 1980 #210}). Associative learning
allows the innate face-detection module to act like a switch that automatically alerts the
face-identification system to the presence of a face, involuntarily triggering the use of
whole-based object processing. This provides an explanation of the inverse-inferiority
effect in normal controls as well as why the inverse-inferiority effect increases with age
{Flin, 1985 #212}. Acquired prosopagnosic patients do not suffer from a general loss in
configural processing, though their injury prevents them from recognising or match faces
on the basis of configural information. Despite this, their pre-trauma experience now
prevents them from utilising anything other than whole-based encoding processes when
presented with an upright face pattern. Developmental prosopagnosics, however, do not
suffer from such a learnt disadvantage. Having never possessed the ability to encode
faces as Gestalt units, their intact face-detection abilities remain to be a completely
independent process from general object processing and do not bias object processing
towards the use of configural or featural processes. Hence, developmental prosopagnosics
remain completely unaffected by manipulations of face-orientation. Figure 1.4 is a brief
illustration adapted
from de Gelder and
Upright
Rouw’s (2001) first
Face image
publication of this
theoretical model.
Fa
ce
General Object
Recognition
Essentially, de
Detection
Face
Gelder and Rouw
(2001) claimed that
Identificati
Part-based
Fig. 1.3. Dual-route account of face recognition
the face-detection
on
Whole-based
systemought
comprising
independent
face detection
system
to be considered
autonomous
fromand
face-identification processes. In addition,
(&
related each system (see Table 1).
identification
systems.
(Adapted
from
Gelder
& Rouw
they
came up with
a list of
attributes
thatdeought
to characterise
(2001)
Given
this dissertation’s particular interest effects)
with the spatial components of face-detection,
we shall limit our discussion to the claim that the face-detection system is based on
1
2
3
Face detection
Fast
Based on exogenous attention
4
Based on coarse-grained
representations/processes
Requires limited stimulus exposure
5
Category specific/unique
6
Neuronal basis is distributed across a
variety of brain areas that contain facesensitive cells
Ontogenetically primitive
7
Face identification
Slower
Under the influence of endogenous
attention and perceptual strategies
Requires fine-grained representations
Depends on extensive learning between
ages 0 and 12 year
Shares resources with object
recognition system
In FFA and overlapping with object
recognition areas
Ontogenetically complex as assembled
from more primitive components
Table 1. List of theoretical attributes associated with the autonomous systems of facedetection and face-identification
exogenous attention. In the next section, we shall look at some relevant findings in the
attentional literature and discuss how that might relate to face-detection, if it is true that
the face-detection influences exogenous attention.
Features and Conjunctions: Searching for a face
The visual search paradigm was designed to understand how the human visual
system selects an item in a cluttered scene for further processing. In a standard visual
search task, participants have to locate a pre-specified target item amongst distractor
items {Treisman, 1985 #162;Treisman, 1988 #122}. Efficiency of visual search is gauged
by plotting measures of reaction times (RT) and accuracy as a function of the number of
items in the display (set-size). Much replicated findings are that targets that can be
differentiated from distractors by a single basic feature e.g. red from green, produce RT x
set-size functions with slopes nearing zero. Such searches are termed efficient or parallel;
that is, analyses of both the target and distractors for criterion-suitability can proceed in
parallel such that the number of display items is not a limiting factor. In contrast, targets
discriminable from their distractors only through a conjunction of features – e.g. red
oblique amongst green obliques and red vertical lines – return steep linear search slopes,
exceeding the 6 msec per item criterion {Treisman, 1985 #162}. Such searches are
described as serial and self-terminating, whereby each item in the display has to be
individually assessed for target-suitability. With parallel searches, the target item is said
to ‘pop-out’ such that the time taken to detect it remains the same regardless of the
number of items in the visual array {Treisman, 1980 #70;Treisman, 1985 #162}. In this
light, the parallel search process resembles the face-detection effect. This naturally begs
the question as to whether upright faces do pop out in a visual search task.
Treisman and colleagues explain that parallel search occurs pre-attentively at the
level of topological feature maps {Treisman, 1998 #65;Treisman, 1980 #70;Quinlan,
2003 #72}. If a target can be identified on the basis of a single feature, it’s presence can
be detected almost automatically. The need for serial search arises only when there is a
need to check each item for whether its spatial location ‘lights’ up across 2 or more
featural maps. For this interpretation to be upheld, it is vitally important to define what
constitutes a feature. One way of doing so is by inferring from neurophysiological
evidence, special purpose neural systems that are primarily dedicated to processing a
single visual attribute (see, e.g., {Zeki, 1976 #163}). By this criterion, the list of features
could include orientation, colour, spatial frequency, and movement. By the same token,
the configuration of a face-pattern might qualify as a feature, despite being a complex
image that could also be described in terms of the preceding list of features.
Primate studies indicate the presence of neurons in the temporal lobe that respond
selectively to faces, with response rates greater by a factor of 2 to 10 than those obtained
for other stimuli {Rolls, 1984 #166;Perrett, 1982 #164;Perrett, 1984 #165}; These cells
are also selective for the spatial configuration of features making up a face, giving
weaker responses to scrambled photographs of faces. Also, their firing responses are
unaffected by unnatural featural transformations such as colour, thus suggesting that
responses from these face-selective neurons could be separable from established features
and that face-configuration could qualify as a feature in itself. Refering back to the facedetection effect, the face-detection effect shares the same temporal parameters as when
face-specific neurons start to respond preferentially to images containing a normal faceconfiguration as opposed to those with a scrambled configuration {Rolls, 1994 #7}.
There is also some support from the visual search literature for this proposition.
When requested to detect non-oblique lines
in an array comprising oblique distractors, nonoblique lines that formed a face-configuration were
more readily detected than if they made up other
complex configurations (see Fig. 1.4 for examples)
{Gorea, 1990 #21}. Yet, participants were hardly
a
)
b
)
aware of the presence of these configurations and if
asked to classify the configurations, performed no
d displays
cFig. 1.4: Examples of search
better for a face-like configuration compared to
either symmetrical or asymetrical configurations.
utilised by Gorea & Julesz (1991) that require
)
)
detection of non-oblique lines that make up a :
Therefore, we can infer from these findings that the
a) face configuration, b) symmetrical non-face
c) asymetrical non-face
configuration of a face can work towards increasing the configuration,
salience of
its component
configuration, d) face configuration amongst
features, without the conscious knowledge of the perceiver.
results could explain
highlyThese
similar distractors.
other face-superiority effects wherein sequential matching of a face feature is better if the
feature is first presented within the context of a normal upright face {van Santen, 1978
#168;Homa, 1976 #167}. Like this experiment here, the only critical stimuli that need
matter is not the configuration but the configuration’s components. Nonetheless, having
an upright face for a configuration, even a schematic one, greatly facilitates the
processing of the critical components. Presumably, this is because the face-configuration
is particularly salient and draws attention to itself and its components.
Besides this study, there have been several studies that have applied the visualsearch paradigm directly to the search for faces. A logical application would be to
investigate whether upright faces ‘pop-out’ in a crowded scene of non-face distractors,
producing a flat RT x set-size function. In one of such experiments, the target stimuli was
a simple line-drawn face amongst the distractors like itself except with the internal
features jumbled {Nothdurft, 1993 #136}. The task in each trial was to determine
whether the target was present or absent in a crowded array varying for set-size, up to 48
items. Contrary to expectations, RTs for face-detection varied as a linear function to setsize. The relationship between the RTs for target-present trials and array size was found
to be on average, 113ms per item. This same finding was replicated with the use of
inverted faces as distractor items. Similar experiments were conducted by Kuehn and
Jolicoeur {Kuehn, 1994 #135}, using schematic faces derived from Photofit kits that
included basic skin and hair tones. Their experiments also differed from Nothdurft’s by
using much smaller arrays to a maximum set-size of twelve items only. Their predictions
followed the same premise that search for an upright face amongst inverted distractor
faces would be efficient and result in a shallow search slope of no more than 6msec per
item. Conversely, search for an inverted target amongst upright face-distractors was
expected to occur in a serial fashion, with steeper search slopes. Unfortunately, this
prediction was not borne out. The search slope for an upright face was by no means flat
and in fact, search times for target-present trials were not even consistently faster for
upright faces than inverted faces. Furthermore, search slopes for target-absent trials were
double that of target-present trials for upright faces, indicating that searches proceeded in
a serial and self-terminating fashion.
Arguably, Nothdurft’s (1993) and Kuehn and Jolicouer’s (1994) failure to find a
‘pop-out’ effect could have resulted from their use of abstract schematic faces as target
stimuli. However, this is highly unlikely when we consider how the face-detection effect
was proven even with the use of a smiley-face {Shelley-Tremblay, 1999 #121}; and also,
the parsimonious configural make-up of a face-pattern in Gorea and Julesz’s (1990)
featural search experiment. Nonetheless, the search for upright face ‘pop-out’ in the
peripheral vision has since been attempted with the use of actual face-photographs
instead of schematic faces {Brown, 1997 #132}. Instead of RT measures, face ‘pop-out’
was measured in terms of the probability that the first eye-saccade would be towards the
upright face instead of non-face distractors i.e. inverted/scrambled faces, equidistant to
the point of fixation. Measurements were obtained using an eye-tracker. Thus,
participants were presented with a circular array of upright face target and distractor
inverted faces on each trial, each equidistant from a fixation point and requested to make
an eye-movement towards the upright face-target. Unfortunately, saccades towards the
upright face were neither more probable than saccades towards a distractor item, nor even
above probability of chance. Measures of saccade latency were no different in the event a
saccade towards an upright face was made compared to when it was not. Even changing
the nature of distractors to scrambled faces failed to make a difference.
This inability to find a ‘pop-out’ effect for an upright face-configuration is
disappointing and contradicts the proposition that the face-configuration can be processed
pre-attentively and orients attention. Still, it is particularly puzzling why a feature
contained within a face-configuration should be any easier to detect than if it was not
{Gorea, 1990 #21}. Even more surprising is that their target features were contained
within a visual depiction of a face configuration that was far more parsimonious and
abstract than those utilised in subsequent studies of visual searches that employed the
actual face as a target stimuli (cf. {Nothdurft, 1993 #136;Brown, 1997 #132;Kuehn, 1994
#135}). Careful examination of these studies raises the possibility that task demands
might be key in explaining the failure to find a “pop-out” effect with upright faces. The
main difference between Gorea and Julesz’s (1990) study and subsequent studies
{Nothdurft, 1993 #136;Brown, 1997 #132;Kuehn, 1994 #135} lie in the nature of the
pre-specified target. The search task that did find a facilitative effect for the presence of a
face-configuration required participants to search for a feature that unbeknown to them,
made up an upright face-configuration. Participants in this task were not consciously in
search of an upright face unlikely those in the studies that actually failed to find a benefit
for the upright face-configuration. In fact, asking participants of the same experimental
paradigm to consciously identify the configurations yielded percentage accuracies as one
might expect from the ‘failed’ findings of visual search studies; that is, participants were
no better in identifying an upright face from an equally complex non-face stimuli.
Whilst it might seem counter-intuitive to presume that searching for an upright
face could actually block its detection privileges, it is not theoretically implausible.
Firstly, the face-detection effect is repeatedly reported to occur without the subjects full
knowledge of the detected item’s identity {Purcell, 1988 #23;Purcell, 1986 #27}.
Furthermore, de Gelder and Rouw’s (2001) dual-route account of face-processing is one
whereby the automatic stream of face-detection is subordinate to and can be override by
the conscious processing stream of face-identification. The experiments in Chapter 2
have been designed to test if faces can attract spatial attention and result in pop-out when
participants are not consciously in search of an upright face.
Final Conclusions
In this chapter, we have presented the experimental phenomenon of the facedetection effect {Purcell, 1986 #27;Purcell, 1988 #24;Shelley-Tremblay, 1999 #121}.
The face-detection effect refers to how human observers are likelier to detect the
presence of an upright face-configuration in a visual array than a non-face pattern of
equivalent complexity, such as inverted/scrambled faces. This effect reveals itself when
the image suffers from limited presentation i.e. backward visual masking, such that faceidentification is not reliably accurate. For this reason, face-detection is raised as an
autonomous process from face-identification and one that has logical precedence to it.
Taking into account the face-detection effect, we are better equipped to
understand why it should be so that upright face-configurations are conferred visual
privileges within the context of other experimental paradigms. By assuming that facedetection is an innate and perhaps sub-cortical mechanism {Valenza, 1996 #207}, we can
understand why neonates prefer looking at face-like patterns despite their apparent lack
of perceptual and social learning experience {Goren, 1975 #155;Kleiner, 1987 #156}.
Also, by assuming that this early detection for faces connotates a sensitivity to changes in
the face-image, we can better explain why the face-configuration repeatedly defies
various experimental attempts to induce change-blindness to it (e.g. {Ro, 2001 #73;Mack,
1998 #194}.
Furthermore, neuropsychologists have been able to explain anomalies in their
prosopagnosic data by coming up with a more comprehensive model of the faceprocessing system that considers the role of face-detection in the learnt acquisition of
face-identification expertise {de Gelder, 2001 #33}. This model is an improvement from
traditional accounts (e.g. Bruce and Young (1986)) for two main reasons.
Firstly, the model is a developmental account that not only attempts to explain
adult face-identification expertise, but takes into account the qualitative differences
between children and adult face-processing performance. That is, how adult faceprocessing relies more on the configural information present in a face than that of a child
{Flin, 1980 #211;Carey, 1980 #210}. In addition, this recent model presents a unified and
more detailed account of how a face-image is treated by early perceptual processes.
Bruce and Young’s (1986) model did not consider the visual processing of faces any
different or special to that of general objects prior to cognition or its identification.
Nevertheless, the face-detection effect contests this assumption. In this more recent
model by de Gelder and Rouw (2001), we are presented with a detailed exposition of
what the process of “Structural encoding” might entail and how the reported facedetection effect might be involved. The biggest research contribution such a model offers
is in its theoretical predictions. One of its predictions is that face-detection is based on
exogenous visual attention. In other words, the upright face-image can act as a salient cue
that automatically captures visual-attention.
This prediction has had minimal support in the visual search literature. While it is
true that a face-configuration can facilitate searches for target stimuli within itself {Gorea,
1990 #21}, it has also been repeatedly proven that an upright-face does not pop-out from
a cluttered visual array, as one would expect {Nothdurft, 1993 #136;Kuehn, 1994
#135;Brown, 1997 #132}. Still, it must be noted that these visual search tasks for upright
faces placed an implicit demand for face-identification on their participants. Hence, their
participants were actively searching for upright faces and were likely to have utilised an
endogenous strategy in the task. All the experiments presented in this dissertation have
been specifically designed to avoid this confound.
Chapter 2 will present a series of visual search experiments whereby the presence
of an upright face is entirely inconsequential to the task. The premise is that if upright
faces do capture visual spatial attention, it will severely impair performance on the
primary visual search task. In addition, the elements comprising the visual search array
has been chosen such as to remove any possibility that any strategies pertaining to the
face-image might be endogenously applied.
Chapter 3 describes a dot-probe experiment that assesses how an upright face
image directly compares to a non-face image i.e. inverted face, in terms of cue validity.
Again, the presence of the face-image is completely irrelevant to successful completion
of the task . Nonetheless, the upright face-configuration is expected to be a better spatial
cue than an inverted-face if automatic face-detection is capable of priming observers to
the spatial location of the upright face.
To surmise, this dissertation sets out to investigate the primary claim that facedetection results in the early spatial monitoring of an upright face-configuration. This
consequence is supposed to be involuntary and automatic. Furthermore, it is subsumed
into the broader processes of face-identification. We propose that this claim has
implications on how visual searches might be conducted, in the absence of faceidentification search strategies. Hence, the presence of an upright face can have an impact
on visual searches that have to rely entirely on exogenous information.