Tài liệu Towards a framework for the study of the neural correlates of aesthetic preference pdf

Spatial Vision, Vol. 21, No. 3–5, pp. 379–396 (2008)

Koninklijke Brill NV, Leiden, 2008.
Also available online - www.brill.nl/sv
Towards a framework for the study of the neural correlates
of aesthetic preference
MARCOS NADAL
1,∗
,ENRICMUNAR
1
, MIQUEL ÀNGEL CAPÓ
2
,
JAUME ROSSELLÓ
1
and CAMILO JOSÉ CELA-CONDE
2
1
Department of Psychology, Universitat de les Illes Balears, Crta Valldermossa s/n, km 7,5,
Palma de Mallorca 07122, Spain
2
Department of Philosophy, Universitat de les Illes Balears, Crta Valldermossa s/n, km 7,5,
Palma de Mallorca 07122, Spain
Received 21 March 2006; accepted 10 March 2007
Abstract—Aiming to provide a tentative framework for the study of the neural correlates of aesthetic
preference, we review three recent neuroimaging studies carried out with the purpose of locating
brain activity associated with decisions about the beauty of visual stimuli (Cela-Conde et al., 2004;
Kawabata and Zeki, 2004; Vartanian and Goel, 2004). We find that the results of the three studies
are not in line with previous neuropsychological data. Moreover, there are no coincidences among
their results. However, when they are mapped on to Chatterjee’s (2003) neuropsychological model of
aesthetic preference it becomes clear that neuroimaging data are not contradictory, but complementary,

and their interpretation is enriched. The results of these studies suggest that affective processes
have an important role in aesthetic preference, and that they are integrated with cognitive processes
to reach a decision regarding the beauty of visual stimuli. Future studies must aim to clarify
whether certain methodological procedures are better suited to study any of the particular cognitive
operations involved in aesthetic preference, and ascertain the extent to which the proposed framework
is compatible with the aesthetic appreciation of musical stimuli.
Keywords: Brain; fMRI; MEG; aesthetic preference; beauty.
INTRODUCTION
The question of the neural correlates of artistic production, aesthetic preference, and
similar phenomena, has not been addressed by means of functional neuroimaging
techniques until quite recently, although it has been investigated from a neuropsy-
chological perspective (see Chatterjee, 2004, for a review). Here we offer an in-
tegrative perspective of neuroimaging studies of aesthetic preference. We will not
∗
To whom correspondence should be addressed. E-mail:
380 M. Nadal et al.
try to offer a general overview of the neural correlates of appreciation for artistic
and aesthetic objects. This is a very broad field that includes interesting studies ad-
dressing the brain basis of different phenomena, such as artistic production, artistic
appreciation, the effects of artistic education, visual arts, music, and so on. We have
chosen to be selective in this paper, concentrating on visual art and aesthetics, and
leaving aside several interesting studies carried out in relation to music (reviewed in
Peretz and Zatorre, 2005).
Thus, the present work focuses mainly on the neural correlates of visual aesthetic
preference. Despite the limited scope of the results produced within this line of
research and the current absence of a solid grounding framework, there are already
several new studies being carried out, making an integrative framework much more
urgent. Thus, the main objective of the present work is to begin the construction
of this scaffolding by suggesting a series of testable hypotheses based on existing
results. Our conclusions are not meant as closed, indisputable facts, but as a set of

possible means to work on a solid framework for future studies in this field. The
results of each of the reviewed neuroimaging studies will be discussed in reference
to previous literature, and they will be brought together with the aid of a recent
cognitive model of aesthetic preference.
Cognitive processes involved in aesthetic preference
Several views on aesthetic preference have been developed during the last century,
including Psychoanalysis, Gestalt theory and Empirical Aesthetics. Within the last
of these, aesthetic preference has been related with arousal (Berlyne, 1970, 1971),
prototypicality (Martindale, 1988; Martindale et al., 1988), and appraisals (Silvia,
2005), among other factors. Potentially, any of these perspectives could serve to
ground our interpretation of neuroimaging results. However, given that the present
work aims to provide a tentative relation between neural activity and cognitive
processes, we need a model that specifies the cognitive operations underlying
aesthetic preference, as well as their interactions, and that, at the same time, can
bridge the cognitive-neural levels.
Leder et al. (2004) have recently proposed a comprehensive model of visual aes-
thetic preference and perception, which includes five processing stages: perceptual
analysis of the visual stimulus, implicit memory integration, explicit classification,
cognitive mastering, and the emergence of a cognitive state, resulting from the pre-
vious stages, and an affective state, that results from the continuous interactions
between previous stages and affective systems in the brain. The cognitive state is
the source of aesthetic preference, while aesthetic emotion is grounded on the af-
fective state.
The different stages suggested by Leder and colleagues (2004) include several
operations, involving different variables known to affect aesthetic preference. How-
ever, their model is formulated at a general psychological level, which makes it
difficult to establish straightforward hypotheses about specific brain activity asso-
ciated with those operations. In contrast, Chatterjee’s (2003) framework for the
Neural correlates of aesthetic preference 381
neural correlates of aesthetic preference is directly grounded on visual neuroscience,

which makes it an ideal candidate to bridge this gap. Chatterjee (2003) suggested
that aesthetic preference involves three processing stages, common to the perception
of any visual stimulus. Early visual processes extract and analyze simple compo-
nents in different brain areas. Operations in the intermediate stage segregate some
elements and group others, forming coherent representations. In late visual process-
ing stages certain regions of the object are selected for further scrutiny, memories
are activated, objects are recognized and associated with meanings. In the case
of visual stimuli found to be aesthetically pleasing, these operations elicit emo-
tional processes, which feedback into the system via attentional mechanisms. As
in Leder and colleagues’ (2004) model, there is a second output, here represented
by the decision-making processes required by most experimental designs. Chatter-
jee (2003) suggested that processing aesthetic stimuli involves similar visual brain
regions as processing any other kind of visual stimuli. What sets aesthetic prefer-
ence apart from other cognitive processing of visual stimuli is precisely the engage-
ment and interplay of additional non-perceptual processes, such as emotions and
decision-making.
Regarding the neural correlates of these operations, Chatterjee (2003) suggested
that early visual processing of the basic features of artworks and other aesthetic
stimuli takes place in occipital brain regions, like any other kind of stimuli.
However, features processed in intermediate stages, such as shape or composition,
can engage frontal-parietal attentional circuits, which enhance the processing of
those attributes within the ventral visual stream (Chatterjee, 2003). He anticipated
that the tasks of stating preferences and making decisions about objects would
most likely be associated with activity in the dorsolateral frontal and medial frontal
cortices. Pinpointing the neural correlates of the emotional facet of aesthetic
experience is more difficult, given that its very nature is less clear. In spite of this,
Chatterjee (2003) suggested that given that anterior medial temporal lobe, medial
and orbital cortices in the frontal lobe, as well as subcortical structures, mediate
emotions, they might also be involved in the affective component of the aesthetic
experience.

NEUROIMAGING STUDIES OF AESTHETIC PREFERENCE
There are currently four published neuroimaging studies concerned with the neu-
roanatomical correlates of aesthetic preference for visual stimuli. Three of them
have very similar objectives. Cela-Conde et al. (2004) aimed to locate “brain ar-
eas activated during the visual perception of aesthetic objects” (Cela-Conde et al.,
2004, p. 6321). Kawabata and Zeki (2004) wanted to verify whether “there are brain
areas that are consistently active across subjects when they perceive a painting as
being beautiful and, conversely, whether there are brain areas that are specifically
active when they view paintings that they consider to be ugly” (Kawabata and Zeki,
2004, p. 1699). Vartanian and Goel (2004) carried out their study to “determine
382 M. Nadal et al.
the neuroanatomical correlates of aesthetic preference for paintings” (Vartanian and
Goel, 2004, p. 893). Another similarity is that the three studies were designed to
contrast participants’ brain activity associated with positively and negatively rated
stimuli. Thus, while their brain activity was being recorded, participants created dif-
ferent stimuli conditions varying in beauty or preference as a result of their aesthetic
preference ratings.
A fourth study (Jacobsen et al., 2006) may appear to address the same question
as the aforementioned three. However, it differs in at least two very important
issues. First, whereas the other three studies were concerned with the differences in
brain activation when judging stimuli as beautiful or not beautiful, Jacobsen et al.
(2006) compared the whole process of aesthetic decision making with another kind
of decision, that of symmetry. Thus, the results of the studies by Kawabata and Zeki
(2004), Vartanian and Goel (2004) and Cela-Conde et al. (2004) refer specifically
to the neural correlates of judging stimuli as beautiful compared to those of judging
them as ugly, whereas Jacobsen et al. (2006) designed their experiment to identify
the neural correlates of judging the beauty of images compared to judging their
symmetry. Thus, results obtained by Jacobsen et al. (2006) refer to the neural
correlates of the judgment process itself. This difference is far from trivial; in fact
it has important consequences for the comparison of the results of this study with

the others. Jacobsen et al. (2006) acknowledged this in the first paragraph of their
paper when referring to the other set of studies: “However, these approaches focus
on the particular valences of preferences, e.g., by parametric manipulation of levels
of attractiveness or by direct comparison of beautiful versus ugly or neutral pictures.
In contrast, none of these studies aimed at identifying the network of aesthetic
judgment per se” (Jacobsen et al., 2006, p. 276). In sum, while the question of
the brain correlates of judging the beauty of images in contrast to other judgments,
such as symmetry, is an interesting one, it is not the same as asking about the neural
correlates of judging images as beautiful compared with judging them as ugly.
The second difference between the study by Jacobsen et al. (2006) and the rest
resides in the stimuli presented to the participants. Vartanian and Goel (2004)
and Kawabata and Zeki (2004) asked their participants to express their aesthetic
preferences only for artworks, and Cela-Conde et al. (2004) asked theirs to do so
for artworks, decorative images and photographs. However, Jacobsen et al. (2006)
asked participants to judge the beauty (and symmetry) of black and white abstract
patterns created by the authors. These stimuli consisted of a black circle containing
a centered white square, oriented like a rhombus, in which small black triangles
were arranged to form a variety of graphic patterns. At present it is not clear whether
decisions about the beauty of artistic and decorative stimuli involve the same
cognitive processes as judging the beauty of simple geometric patterns. Berlyne
(1971) considered the tradeoff related with the use of artistic vs simple visual
materials in experimental aesthetics: “In the former case, there is the advantage of
studying reactions to real art and the disadvantage that any two works of art differ
from each other in several different respects, so that the actual factor responsible for
Neural correlates of aesthetic preference 383
any differences in reactions to them is difficult to pin down. The use of artificially
simple material overcomes this drawback but may be open to the criticism that it is a
long way from anything that could be regarded as art and may thus prevent us from
identifying essential components of real-life aesthetic behavior” (Berlyne, 1971,
p. 12). We believe that the introduction of adequate control procedures reduces

many of the disadvantages of using artistic and decorative materials, and that the
use of simple visual patterns might engage different cognitive operations to those
that enable aesthetic appreciation in natural conditions. Furthermore, given that
symmetry is a very salient feature of the materials used by Jacobsen et al. (2006),
their results might be difficult to generalize to other stimuli whose symmetry is less
prominent. For these reasons, the remainder of the present work we will concentrate
on the studies by Kawabata and Zeki (2004), Vartanian and Goel (2004) and Cela-
Conde et al. (2004).
Summary of the neuroimaging results
Regarding the results of the three studies, we shall consider only the contrasts
performed between the conditions of positively and negatively valued stimuli.
Kawabata and Zeki (2004) and Vartanian and Goel (2004) obtained interesting
results when comparing brain activity before different categories of stimuli, such as
abstract vs representational, but such issues will not be commented on here, given
that this review is primarily concerned with the neural basis of general aesthetic
preference. The results of the three studies are illustrated in Fig. 1.
Kawabata and Zeki (2004) registered participants’ brain activity with fMRI
while rating the beauty of stimuli. They found that activity in the orbitofrontal
cortex was greater for stimuli classified as beautiful, while activity in the motor
cortex was greater for stimuli classified as ugly. Cela-Conde et al. (2004)
used magnetoencephalography (MEG) to record brain activity during the aesthetic
preference task. Their results showed that activity in the left dorsolateral prefrontal
cortex increased in late latencies (400–1000 ms) when participants judged stimuli as
beautiful, as compared to the non-beautiful condition. By means of fMRI Vartanian
and Goel (2004) found that the activity in the right caudate nucleus decreased as
preference ratings decreased, while activity in the left anterior cingulate gyrus and
bilateral occipital gyri, increased with preference ratings.
At least two issues merit comment. First, there seems to be a discontinuity
between these three neuroimaging studies and those carried out using lesion and
electroencephalographic methods. For instance, none of the neuroimaging studies

found significant activity in the amygdala, which might have been expected based on
Adolphs and Tranel’s (1999) results. Their study of patients with amygdalar lesions
had suggested that this structure is involved in guiding preference for visual stimuli,
Figure 1. (See color Plate XII) Neural correlates identified by the three neuroimaging studies.
Abbreviations — ACC: Anterior cingulate cortex; CN: Caudate nucleus; DLPFC: Dorsolateral
prefrontal cortex; MC: Motor cortex; OFC: Orbitofrontal cortex; OG: Occipital gyri.
384 M. Nadal et al.
specifically those which are normally judged to be aversive. The neuroimaging
technique used by Cela-Conde et al. (2004) does not allow the recording of
activity in the amygdala, due to its spheroid structure, but Kawabata and Zeki’s
(2004) and Vartanian and Goel’s (2004) studies were well suited to pick up any
significant amygdalar activity, especially in the ugly or non-preferred condition.
The only amygdalar activity was observed when Kawabata and Zeki (2004)
compared the portrait and non-portrait conditions independently of their aesthetic
rating. It is possible that regarding aesthetic preference the conclusions of lesion or
degenerative studies do not easily extend to neuroimaging experiments of healthy
participants. Alternatively, it might be the case that these three neuroimaging studies
did not include unpleasant enough stimuli required to detect amygdalar activity.
This possibility could be experimentally tested by offering participants a broader
affective range of stimuli.
Based on several electroencephalographic studies (Brattico et al., 2003; Jacobsen
and Höfel, 2001, 2003), Jacobsen and Höfel (2003) had suggested a two-stage
model of aesthetic preference. During the first stage, which takes place around
300 milliseconds after the stimulus has been presented, an initial impression is
formed. This process is associated with anterior frontomedian activity, mainly
when participants consider stimuli to lack aesthetic value. The second stage, a
deeper aesthetic evaluation, begins close to 600 milliseconds after stimulus onset
and is related with wide right hemisphere activity. Although the results of three
studies could verify the involvement of frontomedian and right-hemisphere activity,
only the study by Cela-Conde et al. (2004) was well suited, due to the temporal

resolution of MEG, to test the suggested sequence of activity. But as it turned out,
the frontomedian activity Jacobsen and Höfel (2003) found associated with negative
ratings did not appear in any of the neuroimaging studies. In fact, frontal activity
detected by Cela-Conde et al. (2004) (dorsolateral), Kawabata and Zeki (2004)
(orbitofrontal) and Vartanian and Goel (2004) (anterior cingulate) was associated
with positive ratings. Additionally, in the study by Cela-Conde et al. (2004)
all brain activity correlating with aesthetic preference during the first second after
stimuli onset was limited to the left prefrontal dorsolateral cortex. Activity in other
areas, some of which were located in the right hemisphere, was also recorded, but
revealed no significant differences between the beautiful and ugly conditions. These
discrepancies may owe to the use of different kinds of stimuli. Jacobsen and Höfel
(2003) based their model on studies using patterns composed by simple geometric
forms, whereas Cela-Conde et al. (2004) used complex artworks and photographs.
The comparison of the results from neuroimaging studies on the assessment of
facial beauty (Aharon et al., 2001; O’Doherty et al., 2003; Senior, 2003) with
those from the three studies attempting to identify the neural correlates of aesthetic
preference reveals only one coinciding brain region. Kawabata and Zeki’s (2004)
study, the only one out of the three to include portraits, revealed significant activity
in the orbitofrontal cortex before stimuli classified as beautiful, just as was observed
with beautiful faces with high reward value.
Neural correlates of aesthetic preference 385
The second unexpected fact is the complete lack of coincidence among the results
of the three studies when comparing their results regarding the difference in brain
activity between the beautiful and ugly conditions (see Fig. 1). Although each of
the reviewed studies leaves room for improvement, we believe that their limitations
need not lead to an invalidation of their findings, at least until they are replicated or
experimentally disproved. On the other hand, none of these studies asserted that the
areas they had identified were the exclusive neural correlates aesthetic preference.
In fact they all acknowledged that these areas influence and are influenced by the
activity in other brain areas. It might be the case that the three studies captured

only a subset of operations involved in the complex cognitive task of deciding about
the aesthetics of visual stimuli, and that differences in the experimental designs and
procedures lead them to reflect diverse aspects of the aesthetic experience. Thus,
each study might be reporting a partial picture of the neural correlates of aesthetic
preference. But before we attempt to sort out the cognitive operations associated
with the neural correlates identified by each study, we need to address the reasons for
the discrepancy among the results of the three studies. The suggestions commented
below, and summarized in Table 1, are meant here as mere possibilities, given that
at present there are no experimental data to demonstrate that each of these factors
has a direct influence on the neural correlates of aesthetic preference. However, the
revision of the possible reasons behind the divergence of neuroimaging results can
be fruitful in suggesting new testable hypothesis.
Table 1.
Differences among the three neuroimaging studies
Study Kawabata and Zeki Vartanian and Goel Cela-Conde et al.
(2004) (2004) (2004)
Results Greater activity in Activity in right caudate Greater activity in
mOFC for beautiful nucleus decreases with DLPFC for beautiful
stimuli. decreasing preference. stimuli.
Greater activity in Activity in left cingulate
motor cortex for gyrus and occipital gyri
ugly stimuli. increases with increasing
preference.
Technique Event-related fMRI Event-related fMRI MEG
Exposure 2 s 6 s 3 s
Time 500 ms interstimuli int. No interstimuli int. 1–1.2 s interstimuli int.
Task Indicate beautiful, Indicate (0–4) degree of Indicate beautiful or not
neutral or ugly preference beautiful
Participants 5 M 5 F 10 F 2 M 8 F
Stimuli 16 ×(abstract, still (20 ×(representational, 40 × (abstract art,

life, landscapes, abstract)) ×(original, classic, impressionist,
portraits) × filtered, altered) (=120) postimpressionist) +
(beautiful, neutral, 160 photos (=320)
ugly) (=192)
Procedure Pre-classification No No
386 M. Nadal et al.
The most obvious difference among the three studies is the use of a different neu-
roimaging technique (MEG) by Cela-Conde and colleagues (2004) with regards to
the other two studies (event-related fMRI ). The involvement of the detected brain
areas in aesthetic preference is inferred from different parameters. Whereas MEG
detects magnetic fields generated by excitatory and inhibitory postsynaptic poten-
tials in the dendrites of pyramidal neurons (Lounasmaa et al., 1996; Maestú et al.,
2005), fMRI offers an indirect measure of neural activity related with hemodynamic
and metabolic responses underlying neuronal events, probably reflecting input and
intracortical processes (Logothetis et al., 2001). Furthermore, both techniques have
different spatial and temporal resolutions, which require different exposure times
to the stimuli and interstimuli intervals (see Table 1). Verifying that indeed neu-
roimaging technique has an impact on the detected neural correlates of aesthetic
preference could be achieved by using a single protocol for MEG and fMRI, or by
the joint EEG and fMRI recording (Debener et al., 2006).
Another major difference among the three studies is the task that participants
were asked to perform. Kawabata and Zeki (2004) asked their participants to
rate the beauty of the stimuli on a 3-point scale (beautiful, neutral, ugly), whereas
Cela-Conde et al. (2004) used a dichotomous scale (beautiful, not beautiful). In
contrast, Vartanian and Goel’s (2004) participants were asked to rate their degree
of preference for the pictures on a 5-point scale. Leder and colleagues (2005)
suggested that preference ratings are associated with a strong affective or reward
component, and that the task of rating beauty might elicit a stronger cognitive
component. Hence, both tasks might have partially different neural correlates, as
suggested by studies of facial beauty (Aharon et al., 2001).

Another important difference among the three studies that could lead to the
discrepancies in their results is the composition of the groups of participants.
Vartanian and Goel (2004) included 10 women and 2 men, Kawabata and Zeki
(2004) included 5 men and 5 women, while Cela-Conde et al. (2004) included
8 women. This seems to be a relevant issue, in the light of studies that have found
gender differences in aesthetic preference (Bernard, 1972; Burges Cruz, 2000;
Eysenck and Castle, 1971; Furnham and Walker, 2001; Johnson and Knapp, 1963;
Neperud, 1986; Polzella, 2000), and the increasing evidence of sex differences in
the neural correlates of several cognitive (Bell et al., 2006; Boghi et al., 2006;
Georgopoulos et al., 2001; Haier et al., 2006) and affective tasks (Azim et al., 2005;
Kemp et al., 2004; Mackiewicz et al., 2006; Piefke et al., 2005; Tranel et al., 2005).
Thus, it is not known how confounding it is to jointly analyze men and women’s
results, or how limiting it is to only include participants from one of the sexes.
The composition of the material might also turn out to have an important role
in explaining the differences among the three studies being reviewed here. The
only commonality in this respect is that the three studies included both abstract
and representational stimuli, though in different proportions. Cela-Conde et al.
(2004) were the only ones to include non-artistic in addition to artistic stimuli.
Kawabata and Zeki’s (2004) study was the only one to include portraits. Finally,
Neural correlates of aesthetic preference 387
Vartanian and Goel (2004) presented participants with two altered versions of each
picture, in addition to the original form. There is an extensive literature showing
differences in the aesthetic preference for visual stimuli according to their degree
of abstraction, artistic qualities, and modification (Bernard, 1972; Cela-Conde et
al., 2002; Furnham and Walker, 2001; Hekkert and van Wieringen, 1996a, 1996b;
Johnson and Knapp, 1963; Lindauer, 1990; Neperud, 1986; Winston and Cupchik,
1992). It is possible that these behavioural differences may have an expression at the
neural level, as suggested by Kettlewell and Lipscomb’s (1992) neuropsychological
study, though at present we can only assume that neural networks related with
object recognition contribute differently to the aesthetic appreciation of abstract and

representational visual stimuli.
Finally, there are profound differences among the three procedures, which come
to reflect some of the divergences we have already pointed out. For instance, in
contrast to the studies by Vartanian and Goel (2004) and Cela-Conde et al. (2004),
Kawabata and Zeki (2004) included a stimuli pre-selection procedure. This might
have inadvertently elicited recognition processes in the task participants performed
while their brain activity was being recorded, as suggested by results from previous
studies (Cela-Conde et al., 2002; Nadal et al., 2006) that revealed an association
between mnemonic processes and aesthetic preference. The other procedural aspect
that is different among the studies is the preparation of stimuli. There are several
variables that have been shown to affect aesthetic preference of visual stimuli,
such as psychophysical variables (luminance, contrast, predominant wavelength),
complexity, novelty, prototypicality, and so on (e.g. Berlyne, 1970; Martindale
and Moore, 1988). Furthermore, it has been shown that some of these variables
have an impact on the neural correlates of visual processing (Daffner et al., 1998,
2000; Müller et al., 2003; Nicki and Gale, 1977; Sasaki et al., 2005). Whereas
Cela-Conde et al. (2004) homogenized the complexity, novelty, color spectrum and
luminance of the stimuli, in addition to their size and resolution, Vartanian and Goel
(2004) and Kawabata and Zeki (2004) did not report whether they carried out any
detailed procedure, beyond normalizing size and resolution, in order to control these
variables.
POSSIBLE RELATIONS BETWEEN BRAIN ACTIVITY AND COGNITIVE
PROCESSES INVOLVED IN AESTHETIC PREFERENCE
We have discussed the possible reasons for the lack of coincidence among the
results of three neuroimaging studies addressing the neural correlates of aesthetic
preference, concentrating on different procedural aspects. Given that aesthetic
preference is a process that involves multiple cognitive operations, which take
place in different brain areas and in different time frames, it is very possible that
the results of the three neuroimaging studies reviewed here, conditioned by their
respective experimental designs, refer to the neural correlates of only some of

these processing operations. The fact that none of the three studies is grounded
388 M. Nadal et al.
on a specified psychological model of the cognitive operations involved in aesthetic
preference prevents the authors from designing adequate control procedures and
baseline conditions. This would allow them to isolate more specific brain activity,
or a subset of operations involved in aesthetic preference. Thus, for the moment,
we must settle for what seems to be an incomplete and partial knowledge of the
neural correlates of aesthetic or beauty preferences. Therefore, the relation between
specific cognitive operations contributing to aesthetic preference and each of the
brain areas identified by the neuroimaging studies remains to be determined.
Vartanian and Goel (2004) found lower preference ratings associated with de-
creased activity of the caudate nucleus, higher ratings associated with increased
activity in the bilateral occipital giry and left cingulate sulcus. Caudate nucleus
activity has been associated with the processing of primary rewarding stimuli by
animals (Rolls, 1999; Schultz et al., 2000) as well as abstract rewards in humans,
such as imaginary money (Delgado et al., 2000; Knutson et al., 2000). These results
suggest that the caudate nucleus’ activity during aesthetic preference might reflect
the subcortical processing of the emotional response to aesthetic stimuli.
With regard to the increased activity in visual areas, Kaestner and Ungerleider
(2000) have shown that attention modulates the processing of relevant visual stimuli
by enhancing neuronal responses at different levels of visual processing in the brain.
Poghosyan and colleagues (2005) showed that attention can modulate neuronal
responses to certain locations of the visual field, whole visual objects, or specific
visual features, such as color or shape. They noted that these modulatory effects
were stronger in extrastriate visual areas, though different features of selective
attention can also affect activity in striate cortex. However, it has been shown that
the emotional valence of images can also modulate activity in visual areas (Lang et
al., 1998; Shulman et al., 1997). So, it is not easy to determine whether the occipital
activity associated with preferred images observed by Vartanian and Goel (2004) is
associated with attentional or emotional modulation of visual processing. In fact,

Lane and colleagues (1999) found that emotional valence, arousal and attention
independently increased the activity in extrastriate cortex, suggesting that there is
a common influence that converges on early visual processing. They also noted
that the overlap of the activity patterns associated with emotion and attention could
be a reflection of their overlap at a behavioral level, in the sense that attentional
resources would automatically be recruited during emotional states. Maunsell
(2004) suggested that the brain might not even have different neuronal signals
related with attention and reward, broadly defined to include, in addition to primary
reinforcers, other factors that can motivate behavior, such as the preference for
places or stimuli. In this sense, the allocation of attention could be the representation
of the subject’s actual assessment of reward. Thus, occipital activity identified by
Vartanian and Goel (2004) might reflect enhanced processing of preferred stimuli,
related with attentional or affective processes.
Finally, the increase in cingulate activity could be a manifestation at an emotional
level of this attentional engagement of preferred stimuli. Bush and colleagues
Neural correlates of aesthetic preference 389
(2000) suggested that the anterior cingulate cortex is part of an attentional system
that regulates cognitive and emotional processing. They noted that the anterior
cingulate cortex can be functionally divided in two regions: a cognitive division
and an affective division. The latter encompasses the region identified by Vartanian
and Goel (2004), and has been related with the assessment of the relevance of
motivational and emotional information and the regulation of emotional responses
(Bush et al., 2000). The studies carried out by Lane and colleagues (1998) and
Hornak and colleagues (2003) support the notion that the anterior cingulate cortex
is involved in certain aspects related with the conscious awareness of emotions.
Turning to the results obtained by Kawabata and Zeki (2004), let us recall they
found that stimuli rated as beautiful were associated with an increased activity in
the orbitofrontal cortex, as Chatterjee (2003) had suggested, and low activity in
the motor cortex, while the inverse pattern was found for stimuli rated as ugly. It
seems quite clear that this study has essentially captured certain emotional processes

involved in aesthetic preference. The orbitofrontal cortex has often been related with
the representation of the reward value of stimuli and with the integration of affective
information relayed from limbic areas (Krawczyk, 2002). Orbitofrontal activity has
been observed in association with the deliverance of primary tactile and gustatory
reinforcers (Francis et al., 1999; O’Doherty et al., 2002). However, abstract
reinforcers and punishments have also been associated with orbitofrontal activity,
as O’Doherty and colleagues (2001) showed in a study with human participants and
monetary rewards. This last study produced two relevant findings for our purposes.
First, the magnitude of the activity in the orbitofrontal cortex after the application
of a reward or punishment reflected the magnitude of these rewards or punishments,
just as Kawabata and Zeki (2004) observed for aesthetic stimuli. Second, the medial
orbitofrontal cortex, where Kawabata and Zeki (2004) found activity associated
mostly with beautiful images, was most active after a reward and decreased its
activity after punishment, whereas the activity in the lateral orbitofrontal cortex
increased after punishments and decreased after reward. O’Doherty and colleagues
(2001) concluded that these regions represent the magnitude of rewards and
punishments. This perspective has been later ratified by lesion studies (see Hornak
and colleagues, 2004, for instance).
Regarding the relationship between reward and motor cortex identified by Kawa-
bata and Zeki (2004), activity in the motor cortex has previously been observed
during the presentation of unpleasant stimuli, such as short scripts of autobiograph-
ical episodes of anger (Dougherty et al., 1999) or angry faces that had been fear-
conditioned with aversive stimuli (Armony and Dolan, 2002). In relation to reward-
related activity in the motor cortex, and based on single-neuron recordings from
monkeys, Roesch and Olson (2003) pointed out that, although it is usually assumed
that neural activity related with reward reflects the representation of the value of the
reward, the neural signals representing this value are not easily distinguished from
those reflecting the degree of motor readiness or the preparation of specific move-
ments. In fact, their results suggest that whereas the orbitofrontal cortex is involved
390 M. Nadal et al.

in the representation of the reward value of a stimulus, the motor cortex is involved
in keeping a degree of motivation proportional to the value of the reward (Roesch
and Olson, 2004). Thus, it could be that activity in the motor cortex registered
by Kawabata and Zeki (2004) reflects the motor readiness related with withdrawal
behavior elicited by ugly stimuli. However, at present it is not possible to decide
whether activity in this area is associated with the representation of the reward value
or this motor readiness.
The results of Cela-Conde and colleagues’ (2004) study showed that the activity
in the left dorsolateral prefrontal cortex (DLPFC) was greater when stimuli were
judged as beautiful than when they were judged as not beautiful. The involvement
of this area in aesthetic preference was anticipated by Chatterjee (2003). The
literature suggests that this area is involved in the process of decision-making based
on perceptual and/or affective information. Heekeren et al. (2004) showed that
activity in the left DLPFC increased with the easiness of a perceptual decision-
making task, and it decreased when the difficulty increased. Alternatively, it has
been shown that activity in the left DLPFC increases in association with positive
affect. Specifically, Davidson and Irwin (1999) suggested that the DLPFC might be
involved in the representation of goal states towards which elemental positive and
negative affective states are directed, relating specifically the left dorsolateral cortex
with the planning of approach goal-directed actions (Davidson, 2003). Krawczyk
(2002) provided an integrative view of the role of this area: “The left DLPFC
may play a privileged role in decision making that is better constrained, has fewer
options, and which may have preexisting reward characteristics that make for a more
confined set of rules for deciding” (Krawczyk, 2002, p. 661). Thus, the DLPFC
seems to participate in the conscious deliberation about different options, influenced
by emotional information from OFC and certain limbic areas. This is congruent
with Wallis and Miller’s (2003) hypothesis that information about rewards enters
the prefrontal cortex through the orbitofrontal cortex where it is passed on to the
prefrontal dorsolateral cortex, where it is used to control behavior.
A tentative framework for the study of the neural correlates of aesthetic preference

We have suggested that the results of the three neuroimaging studies reviewed here
relate to different cognitive processes, included in Chatterjee’s (2003) model of vi-
sual aesthetic experience. Figure 2 shows the main results of the three neuroimaging
studies mapped onto Chatterjee’s (2003) framework for the neural correlates of vi-
Figure 2. (See color Plate XII) Neural correlates identified by the three neuroimaging studies
mapped onto Chatterjee’s (2003) framework of visual aesthetic preference. We have modified some
details from Chatterjee’s (2003) original representation to include more bidirectional arrows, to show
attentional processes as ubiquitous as opposed to a specific processing stage, and to change the
original label ‘representational domain’ by ‘high vision’, thus avoiding the ambiguity of the term
representation while maintaining the idea of a stage of higher-level visual processing. Abbreviations
— V & G: Vartanian and Goel (2004); K & Z: Kawabata and Zeki (2004); C-C et al: Cela-Conde and
colleagues (2004).
Neural correlates of aesthetic preference 391
sual aesthetics. This framework provides a general scaffolding for the results of
the three studies, and suggests that their results are not contradictory, but comple-
mentary. Mapping the results of the three neuroimaging studies onto Chatterjee’s
(2003) model, briefly described above, clarifies the meaning of each of their results,
allows suggesting what specific processes or aspects of aesthetic experience have
been captured by each of them, and highlights their complementarity. It must be
noted, however, that this is a post-hoc interpretation, and future research is required
to experimentally validate the hypothesis suggested hereafter.
Three of the components of the model were especially highlighted by the results
of the neuroimaging studies: emotional response, enhancement of early visual
processes and decision-making. Two aspects of the emotional response associated
with aesthetic preference have been captured by two of the reviewed studies: the
representation of reward value and the awareness of the emotional state. The cortical
processing of the magnitude of the reward of the stimuli to be aesthetically judged
probably corresponds to activity in the medial orbitofrontal cortex identified by
Kawabata and Zeki (2004): images rated as beautiful were associated with a higher
reward value than those rated as ugly. It remains to be studied whether extending the

degree of ugliness of the images in the sample, including really unpleasant stimuli,
would elicit activity in lateral orbitofrontal cortex in an aesthetic preference task,
as observed by O’Doherty and colleagues (2001). The subcortical component of
reward value processing during aesthetic preference was registered by Vartanian
and Goel’s (2004) study, corresponding to activity in the caudate nucleus. Reward-
related activity in the motor cortex (Kawabata and Zeki, 2004) could either represent
the reward magnitude of ugly stimuli or the motor readiness elicited by them. The
subjective emotional experience associated with preferred stimuli was reflected in
Vartanian and Goel’s (2004) results. Activity in the anterior cingulate cortex seems
to be associated with the attentional regulation of emotional processes associated
with preferred stimuli.
Second, the enhancement of early visual processing (occipital cortex) has been
registered by Vartanian and Goel’s (2004) design. In principle, this effect could be
due to attentional mechanisms, emotional valence or arousal (Lane et al., 1999). It
is difficult to tell which of these factors is actually responsible for increased activity
in occipital areas before preferred stimuli, given that they all have similar influences
on these regions and because these factors have not been controlled in any of the
neuroimaging studies. However, as we have pointed out above, it is even possible
that in fact emotional and attentional influences on early visual processing owe to
the same neuronal and cognitive systems. This question can only be addressed
by further studies which manipulate or control emotional arousal and valence and
attention.
Finally, the decision-making process seems to have been highlighted by Cela-
Conde and colleagues’ (2004) design. However, at present it is not possible to
determine whether the activity they identified in the left dorsolateral prefrontal cor-
tex reflects decisions based on perceptual information, as Heekeren and colleagues’
392 M. Nadal et al.
(2004) results would suggest, or on information regarding reward value, as sug-
gested by Herrington and colleagues’ (2005) study. A third possibility is that the
decision associated with the activity in this brain region requires the integration of

both kinds of information. This will remain an open question until further research
controlling perceptual and emotional factors is conducted.
To sum up, despite the three studies aimed to study brain activity associated with
judging stimuli as beautiful in contrast to judging them as ugly, several subtle dif-
ferences in their procedures seem to have favored the localization of the neural
correlates of different specific subprocesses inherent in aesthetic preference. Chat-
terjee’s (2003) framework has allowed an understanding of how their differences re-
flect complementary processes. The framework of the neural correlates of cognitive
processes involved in aesthetic preference that we have just sketched can be tested
experimentally in future studies. For instance, if we are correct in assuming that the
decision-making processes are related with activity in the left prefrontal dorsolateral
cortex, then we would expect not to find such activity if, instead of having to rate the
images, participants were asked to merely observe them. Second, the involvement
of the orbitofrontal cortex, anterior cingulate cortex, and caudate nucleus in the pos-
itive affective component of the aesthetic experience could be tested by means of an
affective priming experimental paradigm. The same could be said about the relation
of the motor cortex with the negative aesthetic experience. It also remains to be
tested whether the inclusion of stimuli which are more aversive elicits activity in
the lateral orbitofrontal cortex and amygdala. Third, controlling for attentional and
affective processes will allow determining the true role of an increased activity in
the occipital cortex while rating visual stimuli as beautiful. Fourth, the comparison
of the neural correlates of rating beauty and rating preference of visual stimuli, as
well as the use of affective and cognitive priming methods, can determine whether
these two measures of aesthetic experience elicit cognitive and affective processes
to the same measure.
Additionally, future studies must aim to clarify whether any of the methodological
options we considered above, or others, are better suited to study the particular
cognitive and emotional operations involved in aesthetic preference. This would
permit the choice to be adjusted according to specific objectives. In order to
do so, the influence of sex, task, rating scale, emotional content, composition

of materials (artistic vs decorative; simple vs complex; novelty: first and second
exposures), and so on, must be systematically assessed. Additionally, the processes
included in Leder and colleagues’ (2004) model which are not accounted for by
that of Chatterjee (2003), such as the context in which the experience takes place,
pre-classification processes, the role of expertise and the influence of individual
differences must also be investigated and integrated with the results of current
studies. Another interesting issue that needs to be addressed is whether any of these
results can be extrapolated to judging the beauty of stimuli in the auditory modality.
Neural correlates of aesthetic preference 393
Acknowledgements
This work was supported by grant BSO2003-069094-C03 from the Dirección
General de Investigación. The authors would like to thank two anonymous
reviewers, as well as Oshin Vartanian and Martin Skov, for insightful comments
and helpful advice.
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Plate XII
M. Nadal et al.,Figure1.
M. Nadal et al.,Figure2.