The area that does holistic processing comes

The fusiform face area (FFA) is an area of the brain in the inferior
temporal lobe that characteristically responds preferentially to face-type
stimuli compared to other stimuli (BAARS
& GAGE, 2013; Kanwisher, McDermott, & Chun, 1997). However, there is controversy
within the field as to whether this increased activity is due to a specific
response to faces as opposed to a general response to things with which one has
expertise. Because humans are extremely social creatures, and a large amount of
social interaction depends on properly interpreting facial expressions,
everyone needs to build a certain amount of expertise with faces in order to
participate normally in society (Haxby,
Hoffman, & Gobbini, 2002). This paper will evaluate the
evidence for and against the specialization of the FFA as a face processing


we look at the studies that provide evidence for and against the fusiform face
area being face specific, we can look at different theories that could be used
to argue for or against the likelihood of a brain area like it existing,
specifically a brain area that processes faces holistically instead of feature
by feature. The most interesting debate in theory about the use of a brain area
that does holistic processing comes from the evolutionary perspective. The main
question evolutionary psychologists ask about the fusiform face area is what
the effect of having a separate brain area for holistic processing would be on
fitness. One side of the debate argues that the evidence for holistic face
processing in non-humans faces is insufficient to conclude that there is clear holistic
processing occurring (Burke
& Sulikowski, 2013). For example, though changing facial
markings on cows makes them less likely to be approached by herd mates (Coulon,
Baudoin, Heyman, & Deputte, 2011), suggesting that they are no longer
recognized, it is not conclusive whether or not this is due to a specially
evolved holistic processing of faces or the simple cooption of preexisting
visual discrimination structures. However, researchers on the other side argue
that because both humans and primates have difficulties learning inverted
(upside down) or split faces (faces which are made by aligning the top half of
one face with the bottom half of another) this suggests that the evolved
process for processing faces is both holistic and configuration based (McKone,
Kanwisher, & Duchaine, 2007), and FFA activation is correlated to
this type behavioral process suggesting that it is an area evolved specifically
for this type of processing (Kanwisher
et al., 1997).

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original study that identified the Fusiform Face Area was conducted by
Kanwisher et al. in 1997. It argued found that there was a specific area in the
inferior temporal lobe that activates preferentially to faces – specifically
intact (not visually scrambled) faces – than it does to any other stimulus. They
used this to argue that the region is selectively involved in facial
processing. Since then there has been debate in the field about whether this
conclusion is accurate. We will start by looking at studies that disagree with
the conclusion that Kanwisher et al. came to, and then look at the response to
these critiques.


are many different critiques of the face specificity argument, most (if not
all) of which argue that though the FFA is more active when viewing faces, this
effect is due to expertise, because faces are something we have a lot of reason
to build expertise in identifying. The first study we will look at that makes
this argument is about general processing of faces of different races. In this
study, they asked participants to recognize both individual features and whole images
of White and Asian faces. What they found was that participants were much
better at holistic recognition of same race faces than of different race faces.
Because the White participant sample was taken in Australia and the Asian
participant sample was taken in Hong Kong, this difficulty mirrored the
relative amounts of experience the participants had with people of other races (Hayward,
Rhodes, & Schwaninger, 2008). This finding suggests that, on the
behavioral level, face processing is at least partially experience based.
However this study looks at general facial processing and not specifically at
activation in the FFA. Perhaps activation in the FFA does not relate to
experience in the way behavioral responses do. A similar study by a different
lab found that differential memory for same race and different race faces was
correlated with FFA activation (Golby,
Gabrieli, Chiao, & Eberhardt, 2001), showing that it is not just general
facial processing, but specifically FFA facial processing that plays a role in
experience based learning.


Other studies look at whether face
and object processing in the FFA can really be distinguished. One study found
that when bird and car experts are shown pictures of birds and cars their FFA
is more active than when they are shown pictures of objects they do not have
expertise with (Gauthier,
Skudlarski, Gore, & Anderson, 2000). This study was originally critiqued
because from certain angles bird faces and cars can resemble human faces, but a
subsequent study that used images of these objects specifically chosen to not
resemble human faces got the same result (Xu,
2005). This activation to objects for
which a character has expertise can also be created: Gauthier et al. conducted
a study in which participants were trained to identify and distinguish novel semi
face-like objects called ‘greebles’. When the researchers compared activation
of face-specific areas of the FFA before and after expertise training, they
found that activation in the FFA increased for greebles, but not for faces (Gauthier,
Tarr, Anderson, Skudlarski, & Gore, 1999). Gaining expertise in an
identification task increases activation in “face” areas of the fusiform gyrus,
which suggests that these areas are more expertise based than face based.


Several studies were used to respond
to Gauthier et al.’s bird and car expertise paper that aimed to distinguish the
way faces and objects of expertise are processed. In a paper that inspired
these studies, researchers had people try to identify components of composite
faces made by combining the top half of one face with the bottom half of
another. They found that people have much more trouble identifying the halves
when they are aligned to form a single composite face than when they are not
aligned. However, this specific difficulty identifying face components in
composites disappears when the faces are inverted (flipped upside down) (Young,
Hellawell, & Hay, 2013). 
These findings suggest that face processing is specific to the
configuration and direction of face elements. McKone et al. repeated this
experiment (composites and inversion), but added non-face images which some
participants had expertise with. Here they found that the identification
difficulty effects of composites and inversion do not affect identification,
which suggests that face processing is done differently than processing of
objects with expertise. This is relevant when it comes to fMRI data, because it
has been found that activation in the FFA depends on having most or all of the
elements of a face visible in the correct configuration (Tong,
Nakayama, Moscovitch, Weinrib, & Kanwisher, 2000).


Another defense of the specificity of
the FFA is that in the case of increased activation to items of expertise, the
increase in signal in the FFA to images of items of expertise is due to the
participant paying more attention to these items, and the increase in signal
for items of expertise is higher in other areas of the cortex than it is in the
FFA (McKone
et al., 2007). A critique of the ‘greeble’ studies
is that the training that teaches participants how to categorize greebles does
not actually confer expertise, and during identification participants are using
ordinary object recognition mechanisms to complete the task (Duchaine,
Dingle, Butterworth, & Nakayama, 2004). This claim is supported by two case
studies of people with acquired prosopagnosia: both were able to learn and
perform well on greeble identification tasks, but unable to do the same for
face recognition tasks, and in one subject this learning occurred even though
they did not have a fully functioning FFA (Rezlescu,
Barton, Pitcher, & Duchaine, 2014), which strongly suggests that the
FFA is not necessary for greeble learning. The other common critique of certain
papers that are arguing for the expertise model is that the region they defined
as the FFA extends past what is typically defined as the FFA, and is
incorporating non FFA signal (McKone
et al., 2007; Rezlescu et al., 2014).        


reading the arguments presented by both sides of this debate I have been
somewhat convinced away from the pure face-processing model of the FFA.
However, I do still believe that the FFA plays an important role in the
holistic processing and identification of faces. There is clearly evidence for
both expertise based processing and face specific configuration based
processing in the FFA. Looking at the two arguments I am entirely willing to
believe that both things can be true simultaneously and occur in the same area.
In individual cell recordings of an analogous region to the FFA in monkeys, researchers
found that though the vast majority of cells were extremely reactive to faces,
there were also some cells that were reactive to other things (Tsao,
2006). There are many different cells in
the FFA, and it is entirely possible that different cells can be accomplishing
different tasks, or that the reaction FFA cells have to faces is a combination
of a reaction to an item of expertise and a reaction to a specific configuration
of features – we have seen cells that are tuned in similar ways in other areas
of the brain in class. I am willing to grant that as far as we know, only faces
are processed in the holistic, configuration based way that has been described
by the studies I explained earlier, but that does not mean that nothing else
can be processed by the same brain area.