brain correlates of aesthetic expertise_a parametric fmri study (2009)

7/28/2019 Brain Correlates of Aesthetic Expertise_A Parametric fMRI Study (2009)

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Brain correlates of aesthetic expertise: A parametric fMRI study

Ulrich Kirk a,b,*, Martin Skov a, Mark Schram Christensen a,c, Niels Nygaard d

a Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Hvidovre, Kettegaard All 30, DK-2650 Hvidovre, Denmarkb Wellcome Laboratory of Neurobiology, Anatomy Department, University College London, Darwin Building, Gower Street, London WC1E 6BT, UKc Department of Exercise and Sport Sciences, University of Copenhagen, The Panum Institute, Blegdamsvej 3, DK-2200 Copenhagen N, Denmarkd Institute for Architecture and Aesthetics, Aarhus School of Architecture, Norreport 20, DK-8000 Aarhus C, Denmark

a r t i c l e i n f o

Article history:Accepted 1 August 2008

Available online 9 September 2008

Keywords:

Neuroaesthetics

Expertise, orbitofrontal cortex

Subcallosal cingulate gyrus

Architecture

Faces

a b s t r a c t

Several studies have demonstrated that acquired expertise influences aesthetic judgments. In this para-digm we used functional magnetic resonance imaging (fMRI) to study aesthetic judgments of visually

presented architectural stimuli and control-stimuli (faces) for a group of architects and a group of

non-architects. This design allowed us to test whether level of expertise modulates neural activity in

brain areas associated with either perceptual processing, memory, or reward processing. We show that

experts and non-experts recruit bilateral medial orbitofrontal cortex (OFC) and subcallosal cingulate

gyrus differentially during aesthetic judgment, even in the absence of behavioural aesthetic rating differ-

ences between experts and non-experts. By contrast, activity in nucleus accumbens (NAcc) exhibits a dif-

ferential response profile compared to OFC and subcallosal cingulate gyrus, suggesting a dissociable role

between these regions in the reward processing of expertise. Finally, categorical responses (irrespective

of aesthetic ratings) resulted in expertise effects in memory-related areas such as hippocampus and pre-

cuneus. These results highlight the fact that expertise not only modulates cognitive processing, but also

modulates the response in reward related brain areas.

2008 Elsevier Inc. All rights reserved.

1. Introduction

In psychological models of aesthetic experience it is generally

assumed that art-related expertise influences subjects preference

for works of art (Leder, Belke, Oeberst, & Augustin, 2004). Indeed,

a substantial number of behavioural studies have confirmed that

level of expertise modulates the aesthetic evaluation of art objects

(Eysenck& Castle, 1970; Gordon, 1951/1952, 1956; Hekkert, Peper,

& van Wieringen, 1994, Hekkert & van Wieringen, 1996a, 1996b;

OHare, 1976; Schmidt, McLaughlin, & Leighten, 1989). It is there-

fore likely that art experts use different neural processes for deter-

mining aesthetic evaluation than non-experts. The question we

wish to raise here is whether this putative difference in aesthetic

evaluation can be detected as a difference in neural activity

through the use of functional magnetic resonance imaging (fMRI).

It has been shown by imaging experiments that acquired exper-

tise is associated with changes in brain structures underlying per-

ceptual and memory processes, even on a macro-anatomical scale.

For example, in a study using voxel-based morphometry analysis,

Maguire and colleagues (2000) found that grey matter volume in

the posterior hippocampus of London taxi drivers is greater than

in age-matched controls, and that the size of this increase corre-

lates positively with time spent taxi driving. Furthermore, several

experiments have demonstrated that musicians, after years of

playing, respond differently to musical inputs as compared to

non-musicians (for a review, see Schlaug, 2003). For example, in

a recent fMRI study, Bangert and colleagues (2006) compared brain

activity in groups of musicians and non-musicians as they pas-

sively listened to a piano sequence and found elevated activity in

the musicians in regions of the temporal lobe associated with audi-

tory processing, and in frontal regions associated with motor

control.

Several neuroimaging studies have investigated cortical areas

that are recruited when subjects make aesthetic evaluations from

a variety of stimulus modalities such as paintings (Cela-Conde

et al., 2004; Kawabata & Zeki, 2004; Vartanian& Goel, 2004), music

(Blood & Zatorre 2001; Blood, Zatorre, Bermudez, & Evans, 1999;

Koelsch, Fritz, von Cramon, Mller, & Friederici, 2006; Brown, Mar-

tinez, & Parsons, 2004; Menon& Levitin, 2005), faces (Aharon et al.,

2001; Nakamura et al., 1998; ODoherty et al. 2003; Winston,

ODoherty, Kilner, Perrett, & Dolan, 2007) and geometrical figures

(Jacobsen, Schubotz, Hfel, & Cramon, 2006). Taken together, these

studies suggest that the computation of aesthetic preferences for

objects predominantly relies on the activity of cortical and subcor-

tical areas implicated in the processing of reward; especially stria-

tum, orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC)

(for a review, see Skov, in press.) It is therefore important to inves-

0278-2626/$ - see front matter 2008 Elsevier Inc. All rights reserved.doi:10.1016/j.bandc.2008.08.004

* Corresponding author. Address: Danish Research Centre for Magnetic Reso-

nance, Copenhagen University Hospital, Hvidovre, Kettegaard All 30, DK-2650

Hvidovre, Denmark.

E-mail address: [email protected] (U. Kirk).

Brain and Cognition 69 (2009) 306315

Contents lists available at ScienceDirect

Brain and Cognition

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / b & c
mailto:[email protected]://www.sciencedirect.com/science/journal/02782626http://www.elsevier.com/locate/b&chttp://www.elsevier.com/locate/b&chttp://www.sciencedirect.com/science/journal/02782626mailto:[email protected]


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tigate whether expertise influences aesthetic evaluation through

the modulation of neural activity in these areas. Since the medial

OFC is not only found to correlate with subjective hedonic value

in most of the studies mentioned above, but have also been dem-

onstrated to be involved in coding stimulus value of a variety of

other sensory modalities, including taste (ODoherty et al., 2001;

Small, Zatorre, Dagher, Evans, & Jones-Gotman, 2001; Small et al.,

2003), olfactory (Anderson et al., 2003; Gottfried, Deichmann, Win-

ston, & Dolan, 2002; Rolls, Kringelbach, & de Araujo, 2003), and

somatosensory (Rolls, ODoherty et al., 2003), we hypothesized that

this region would reflect a modulation of aesthetic assessment

according to level of expertise.

To accomplish this experimental aim, nave subjects (i.e. sub-

jects professing to have no great interest or expertise in art or

architecture) and expert subjects (i.e. graduate students in archi-

tecture and professional architects) were asked to rate the aes-

thetic value of a series of images containing both buildings and

faces during an event-related fMRI paradigm (see Fig. 1). We

hypothesized that the expert-specific conditions (i.e. building

images) would significantly affect both aesthetic ratings and neural

activity differentially in the two groups. Since earlier psychometric

studies have found that people in different cultures, and of both

sexes, tend to agree as to which faces are attractive (Langlois

et al., 2000), we predicted the two groups aesthetic ratings and

neural processing would not differentiate for face images.

2. Experimental methods

2.1. Subjects

A total of 24 healthy volunteers (11 experts/13 non-experts; 6

female experts/7 female non-experts; experts mean age: 30.8

years; age range 2642 years; non-experts mean age: 27.2 years;

age range 2232 years; all subjects were right-handed) were

scanned. We excluded two subjects (both male non-experts) from

the analysis for clinical reasons. The experts were recruited from

architectural offices and schools where they were graduate or

post-graduate students. Non-experts were all undergraduate or

graduate students with no formal education in any art-related

field. Written informed consent was obtained from all subjects

and ethical approval (KF-01-131/03) was obtained before the

experiment. All subjects had normal or corrected-to-normal vision,

and none had a history of neurological or psychiatric disorders.

2.2. Stimulus set

Visual achromatic stimuli belonging to two categories, build-

ings and faces, were used as stimulus material. One hundred and

sixty-eight building stimuli were selected from various online re-

sources. The surrounding of the building image was shaded so that

the building was in focus for each stimulus. This was accomplished

in Photoshop (version 7.0, Adobe, USA). Any image noticeably dis-

torted (e.g., proportion and illumination) by this process was ex-

cluded from the stimulus pool. Building stimuli were presented

with a resolution of 600 pixels in height and varying width with

a maximum of 1024 pixels. Prior to scanning the building stimuli

were exposed to an aesthetic judgment scale in a behavioural pilot

study by a separate cohort of subjects (7 experts/6 non-experts; 3

female experts/3 female non-experts; experts mean age 34.3 years;

age range 2744 years; non-experts mean age 29.2 years; age

range 2730 years). Level of appeal was measured using an aes-

thetic rating scale from 1 to 5, where 1 was defined as very unap-

pealing and 5 as very appealing. The stimuli conformed to a

balanced distribution in the frequency of each rating bin between

experts and non-experts. To investigate whether there were differ-

ences between the two groups for rating-specific stimuli, i.e.

whether there was an image-wise difference between experts

and non-experts for buildings, further analyses were applied. The

building stimuli were selected according to two sub-classes: a for-

mal/stylistic sub-classification (modernist and non-modernist

architecture) and a typological sub-classification (private and

public architecture). This was done in order to further control

for a potential skewed preference distribution between the groups;

for instance, experts might all prefer modernist and non-experts

might all prefer non-modernist buildings. However, this poten-tially confounding effect did not amount to significant differences

between stimuli sub-classes across groups in subsequent statistical

analyses (F(7,40) = 1.78; p > .1).

The face database was provided by the Max-Planck Institute for

Biological Cybernetics in Tuebingen, Germany. 168 face stimuli

were selected; half of the stimuli were female faces. Stimuli were

rated by a separate group of subjects (n = 10/4 females; mean

age 28.4 years; age range 2630 years) for level of appeal in a

behavioural pilot study prior to scanning. Level of appeal was rated

using the same aesthetic rating scale as described above. One hun-

dred and sixty-eight faces were selected from the high, middle and

low ends of the appeal ratings in order to obtain a balanced distri-

bution. The face stimuli were masked in order to remove hair and

were adjusted to be of equal size and luminance by using Photo-shop (version 7.0, Adobe, USA). The faces were centred in a

588 600 pixel black background and presented at a screen reso-

lution of 1024 768 pixels.

2.3. Experimental paradigm

The experimental protocol consisted of an event-related design

in which subjects were scanned while being presented with each of

the 168 face stimuli and the 168 building stimuli in a pseudoran-

dom order, making a total of 336 presentations. On each trial, a fix-

ation cross was presented for 1000 ms on a grey background

followed by a stimuli presentation for 3000 ms. Subjects were in-

structed to press one of five buttons on a response key-pad with

their right hand to indicate their aesthetic judgment (1 = veryunappealing, 5 = very appealing). Randomly interspersed with the

Fig. 1. Experimental paradigm. A fixation cross was shown for1000 ms followed by

stimuluspresentation with a duration of 3000 ms in whichsubjectswere instructed

to indicate the level of aesthetic appeal by means of button-press on a scale from 5

(highest appeal) to 1 (lowest appeal). Examples of stimuli used in the scanningsessions are displayed.

U. Kirk et al./ Brain and Cognition 69 (2009) 306315 307


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stimuli presentations were 56 null event trials (grey screen). Total

scanning-time per subject was 26 min. in one session. The long

paradigm lasting 26 min could have potentially given rise to fati-

gue in the subjects. However, we did not observe any deviations

in behavioural differences when the first part of the scanning

was compared with the last part of the scanning. In particular

the trial to trial judgment variability was assessed as a measure

of fatigue, under the assumption that fatigued subjects would tend

to evaluate similarly from trial to trial when they were fatigued.

Missing trials and the reaction time were also used as indirect

measures, and these did not change either. Prior to scanning, sub-

jects were informed that the study was concerned with investigat-

ing aesthetic judgments, but no reference was made to the

experimental aims. After the scanning task was complete, subjects

were presented with the stimuli again, this time outside the scan-

ner, where they rated each stimulus for familiarity. Familiarity rat-

ings were entered into the design matrix as regressors of no

interest. Stimuli were presented and responses collected using E-

prime (Psychology Software Tools, Inc.). The stimuli were back-

projected via a LCD projector onto a transparent screen positioned

over the subjects head and viewed through a tilted mirror fixed to

the head coil.

2.4. fMRI data acquisition

The functional imaging was conducted by using a 3 Tesla scan-

ner (Siemens, Magnetom Trio, Erlangen, Germany) to acquire gra-

dient T2* weighted gradient echo (GR) echo planar images (EPI) to

maximize the blood oxygen level-dependent (BOLD) contrast

(echo-time, TE = 30 ms; repetition time, TR = 2400 ms; flip angle,

F A=90). The EPI sequence was optimized in order to reduce signal

drop-out in OFC (Deichmann, Gottfried, Hutton, & Turner, 2003).

Each functional image was acquired in an interleaved way, begin-

ning with 2nd slice (slice No. 2,4,. . .,40, 1,3,. . .,39) when counted

from the bottom, comprising 40 axial slices each 3.0 mm thick,

consisting of a 64 64 matrix with an in-plane resolution of

3 3 mm. This gave near whole-brain coverage, excluding inferiorparts of the cerebellum. Each session consistedof 654 volumes. The

subjects pulse and respiration were recorded using an MRI-com-

patible pulse oximeter, and a respiration belt, both sampled at

50 Hz. After the functional scan, a T1 weighted MPRAGE structural

sequence was acquired, using a phased array head coil to provide

high-resolution anatomical detail.

2.5. fMRI data analysis

Image pre-processing and data analysis was performed using

SPM2 (Wellcome Department of Imaging Neuroscience, London,

UK). The EPI images were spatially realigned (Friston et al.,

1995). This was followed by temporal realignment, which cor-

rected for slice-time differences using the middle slice as referenceslice. Images were then normalized to the Montreal Neurological

Institute (MNI) EPI-template provided in SPM2. Finally, a spatial

filtering was performed by applying a Gaussian smoothing kernel

of 8 mm FWHM (full width at half-maximum).

Following pre-processing a general linear model (GLM) was ap-

plied to the time course data, where each event was modelled with

a separate single impulse response function time-locked to middle

stimulus time and then convolved with the canonical haemody-

namic response function (HRF), including its temporal and disper-

sion derivatives in order to capture small variations in the onset

and width of the BOLD responses.

A parametric regression analysis was used (Buchel, Holmes,

Rees, & Friston, 1998) that allowed us to model on/off, linear and

non-linear haemodynamic responses using orthogonalized polyno-mial expansion functions. This was performed for each of the two

stimulus conditions using subject-specific aesthetic ratings in or-

der to model a potential parametric modulation of aesthetic rat-

ings. The on/off or 0th order parametric regression analysis

allows inferences to be made about variations in the response

across the two subject groups independent of the aesthetic ratings.

First-level analysis was performed on each subject to generate a

single mean parameter corresponding to each term of the polyno-

mial expansion. In order to correct for the structured noise inducedby respiration and cardiac pulsation we included RETROICOR (RET-

ROspective Image based CORrection method) nuisance covariates

in the design matrix (Glover, Li, & Ress, 2000). These regressors

are a Fourier expansion of the aliased cardiac and respiratory oscil-

lations. We included six regressors for respiration and ten regres-

sors for cardiac pulsation. We also included 24 regressors that

remove residual movement artefacts with spin history effects,

which have been shown to remain even after image realignment

(Friston, Williams, Howard, Frackowiak, & Turner, 1996). This set

of nuisance regressors have also been shown to reduce inter and

intra subject variation significantly (Lund, Nrgaard, Rostrup,

Rowe, & Paulson, 2005). Having all four types of nuisance regres-

sors in the design improves the assumption of independently and

identically distributed errors (Lund, Madsen, Sidaros, Luo, & Nic-

hols, 2006). For the analysis we also applied a high pass filter with

a cut-off frequency at 1/128 Hz. This high pass filter removes any

temporal drift that oscillates slower than once every 128 s, and it

will therefore remove slowly varying drift caused by hardware

instabilities.

The statistical parametric maps were entered into a second-le-

vel, random effects analysis (RFX) accounting for the between sub-

ject variance. Experts and non-experts were treated as separate

groups in an ANOVA model using the beta-estimates of the two

groups and the two stimuli conditions for the linear and the qua-

dratic expansions. Equal variance was not assumed, thus SPM2s

options for non-sphericity correction was applied (Glaser& Friston,

2004).

Using t-contrasts allowed us to test for correlations of the fMRI

BOLD signal and the parameters of interest performed as on/off,linear and non-linear parametric modulations, respectively. Re-

ported p-values were set at a threshold of p < .001, uncorrected,

unless otherwise stated. In order to correct for multiple compari-

sons in the medial orbitofrontal cortex, a regionin which activation

was predicted on the basis of our a priori hypothesis, we used

small volume corrections (SVC) (Worsley et al., 1996) constraining

our analysis to this region using a sphere with a 10 mm radius. We

used the coordinates reported in Kawabata and Zeki (2004) for

medial OFC. Before using SVC, we transformed coordinates given

by Kawabata and Zeki (2004) from Talairach space to MNI space

(http://www.mrc-cbu.cam.ac.uk). The coordinates of all activations

are reported in MNI space.

3. Results

3.1. Behavioural results

We first inspected the two groups behavioural responses, i.e.

aesthetic ratings, collected during scanning (see Fig. 2). A two-

way ANOVA with two factor levels (buildings, faces) and groups

(experts, non-experts) revealed significant differences between

stimulus conditions (F(1,10) = 54.42; p < 2 107) (see Fig. 2A),

but no significant differences between groups (F(1,10) = 1.89;

p > .1). Furthermore, no significant interactions between stimulus

conditions and groups was observed (F(1,10) = 1.44; p > .2). The

same analysis was applied to the reaction-time data (RT) collected

during scanning. However no significant differences were foundbetween groups (F(1,10) = 0.45;p > .5). Analysing the mean ratings

308 U. Kirk et al. / Brain and Cognition 69 (2009) 306315
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of the two stimulus classes, these results suggest that experts and

non-experts did not display significantly different behaviour in

making an aesthetic judgment of either faces or buildings. We next

inspected whether experts and non-experts differed in the fre-

quency of each rating bin (see Fig. 2C and D), as such a difference

might not be reflected when inspecting the mean aesthetic ratings

(see Fig. 2A). Moreover, such a potential difference in the distribu-

tion of ratings could also have consequences for interpreting thefMRI results, since a different distribution in the frequency of rat-

ing bins between groups could potentially account for differences

in the linear fits between the two groups. No significant differences

were found between groups in the frequency of each rating bin for

face stimuli (see Fig. 2D). For building stimuli (see Fig. 2C) no sig-

nificant differences between groups was observed for rating bin 4

and 5 (reflecting high appeal) and bin 1 and 2 (reflecting low ap-

peal). However, the middle rating bin resulted in a significant dif-

ference between groups (two sample t= 3.02; df = 10; p < .01).

Finally, we looked at the variance of RTs between the two groups.

Although we found no significant differences between the two

groups in mean ratings and RTs, it was possible that a difference

between groups would be reflected in greater variance in RTs be-

tween the groups. However, we found no such difference in vari-ance across groups (F(1,4) = 0.73; p > .4), rating bin (F(1,4) = 0.24;

p > .9), or stimulus type (F(1,4) = 2.25; p > .1). Likewise, we ob-

served no significant interactions (group rating, group stimu-

lus, and group rating stimulus).

3.2. fMRI results

3.2.1. Correlation between the BOLD signal and linear aesthetic ratings

To test whether architectural expertise modulated brain activ-ity associated with making aesthetic judgments a 1st order para-

metric regression model using the subject-specific behavioural

responses was applied. We defined the expertise effect as the inter-

action between the two subject groups and the two stimulus

conditions [Expert_BuildExpert_Faces] [Non-Expert_Build

Non-Expert_Faces]. This analysis allowed us to focus on voxels

for which the difference between the responses for the two stimu-

lus conditions varied across the two subject groups. The interaction

revealed significant activations in bilateral subcallosal cingulate

gyrus (4, 30, 2; z= 4.47; p < .05, corrected for multiple compari-

sons using false discovery rate, FDR; 14, 40, 2; z= 4.32; p < .05,

FDR) (see Fig. 3). When we performed small volume corrections

(SVC) we observed significant activity in bilateral medial OFC

(

8, 30,

20; z= 3.83; p < .05, FDR, SVC; 6, 34,

16; z = 3.40;p < .05, FDR, SVC). These significant interactions were further

Fig. 2. Behavioural responses collected during scanning. (A) Mean aesthetic ratings for the two stimulus conditions and both subject groups. The mean rating for buildingstimuli for experts was 3.29 (SD = 0.21) and for non-experts 3.28 (SD = 0.32). For face stimuli the mean rating for experts was 2.7 (SD = 0.25) and for non-experts 2.79

(SD = 0.33).(B) Mean reactiontimes (RT) forstimulus conditions and subject groups. Examination of RTsrevealedthat average RT forbuildingstimulifor experts was 2003 ms

(SD = 357.4) and for non-experts 2011 ms. (SD = 562.4). The average response time for face stimuli for experts was 1810 ms (SD = 256.6) and for non-experts 1696ms

(SD = 440.4). Response latencies between groups and stimulus conditions did not differ significantly in a one-way ANOVA (F(3,40) = 1.48; p < .23). (C) Distribution of ratings

acrossthe fiverating bins forbuildingstimuli, where each ratingbin is bears a scale from 5 (high appeal) to 1 (low appeal) (x-axis) and the response frequency across subjects

in percent is shown (y-axis). Error bars indicate SD. (D) Distribution of ratings across the five rating bins for face stimuli. Error bars indicate SD.



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the clusters from the building-specific conjunction, and found that

left NAcc (10, 8, 4; z= 3.42; p < .05, FDR, SVC) was significantly

more active in both stimuli conditions in both groups (see Fig. 4).

The activation in left anterior thalamus did not survive SVC. These re-

sults suggest that left NAcc plays a role in encoding high and low aes-

thetic values that is not modulated by expertise or stimulus modality.

3.2.3. Correlation between the BOLD signal and expertise irrespective

of aesthetic ratings

Finally, in order to identify voxels that responded differentially

in the two groups per sei.e., irrespective of aesthetic ratingan

interaction analysis using regressors from a zero-order parametric

regression analysis was conducted. An interaction analysis [Ex-

pert_BuildExpert_Faces] [Non-Expert_BuildNon-Expert_Faces]

showed distinct specificity for buildings compared to faces in

experts relative to non-experts in bilateral hippocampus, left pre-

cuneus and cerebellum (see Fig. 5 and Table 1).

In the converse interaction [Non-Expert_BuildNon-Expert_Fa-

ces] [Expert_BuildExpert_Faces] we observed significant activa-

tions in bilateral calcarine gyrus bilateral and fusiform gyrus

located adjacent to the collateral sulcus and inferior lingual gyrus

posterior to the parahippocampal gyrus (see Fig. 6 and Table 1).

We furthermore conducted a conjunction analysis using the

building-specific main effects for both groups [Expert_BuildEx-

pert_Faces] and [Non-Expert_BuildNon-Expert_Faces]. We ob-

served bilateral activation of the parahippocampal place area

(PPA) [30, 42, 14; 30, 46, 10, FDR] (see Supplementary

material) that has been found to respond selectively to houses,

landscapes and other environmental sceneries (Epstein& Kanwish-

er, 1998).

4. Discussion

The present experiment extends other studies of expertise to

suggest that acquired expertise not only impacts on cognitive

and perceptual systems (Bangert et al., 2006; Maguire et al.,

2000), but also modulates the response of brain areas associated

with the processing of reward. However, the processing of rewardhas been linked to several brain areas, including the ventral teg-

mental area, ventral striatum, amygdala and OFC (for a review,

see McClure, York, & Montague, 2004), and our results show that

only parts of this system are modulated by expertise during aes-

thetic judgment. In contrast to expertise effects observed in OFC

and subcallosal cingulate gyrus, we found that activity in left NAcc

was elevated in both groups and stimuli conditions in response to

appealing and non-appealing stimuli.

The response profile of medial OFC in both groups exhibited a

positive linear correlation with aesthetic ratings. However, when

compared to each other the increase was significantly higher in

the experts than in the non-experts. The fact that the medial part

of OFC shows sensitivity to the magnitude of aesthetic value is in

accordance with studies on reward processing showing that therelative reward value of stimuli is reflected by the amplitude of

Fig. 4. The upper panel shows activation in left NAcc using the2nd order non-linear

term. The lower panel shows the parameter estimates in both groups and for both

stimulus conditions in left NAcc (10, 8, 4) where the x-axis reflects the

experimental conditions consisting of both groups and both stimulus conditions,

and the y-axis shows BOLD signal changes. Activations are overlaid on sagittal,

coronal and axial sections of the canonical SPM structural image. Activation isdisplayed at p < .008, FDR). Error bars indicate 90% confidence interval.

Fig. 5. The upper panel display activation of the left hippocampus from theinteraction [Expert_BuildExpert_Faces] [Non-Expert_BuildNon-Expert_Faces]

using the zero-order parametric analysis that display voxels activated irrespective

of aesthetic rating. The lower panel shows parameter estimates for the left

hippocampus, where the x-axis reflects the experimental conditions, and the y-axis

shows BOLD signal changes. Activation is displayed at p < .001, uncorrected. Error

bars indicate 90% confidence interval.

Table 1

Summary of interaction effects for the parametric regression analysis irrespective of

aesthetic ratings

Brain region MNI coordinates z Score Number of voxels

[Expert_BuildExpert_Faces] [Non-Expert_BuildNon-Expert_Faces]

R hippocampus 38, 28,8 3.60 18

L hippocampus 26,14,14 3.29 17

34,16,20L precuneus 6, 54, 22 3.61 37

R cerebellum 16, 62,16 3.57 26

26, 68,24 3.44 13

[Non-Expert_BuildNon-Expert_Faces] [Expert_BuildExpert_Faces]

R fusiform gyrus 32, 54,4 3.35 9

L fusiform gyrus 30, 56, 0 3.73 42

R calcarine gyrus 18, 58, 16 3.59 21

L calcarine gyrus 18,64, 14 3.79 30

R pons 16, 18, 30 4.41 69

Activations are shown at (p < .001, uncorrected). L, left hemisphere; R, right

hemisphere.

U. Kirk et al. / Brain and Cognition 69 (2009) 306315 311
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neural activity in OFC (Kringelbach, 2005; Tremblay & Schultz,

1999). For instance, in studies comparing subjects ingesting food

in states of hunger and satiety a contrast of these two states reveals

different neural responses in OFC, indicating that OFC neurons

codes reward aspects of a stimulus rather than sensory aspects

(Kringelbach, ODoherty, Rolls, & Andrews, 2003). Furthermore,several studies suggest that the medial aspect of the human OFC

represents the hedonic attributes involved in preference judg-

ments of various stimulus types (Aharon et al., 2001; Anderson

et al., 2003; Blood et al., 1999; Gottfried et al., 2002; Kawabata

et al., 2004; ODoherty et al., 2001; ODoherty et al., 2003; Rolls,

Kringelbach, ODoherty, Rolls, & Andrews, 2003; Rolls, ODoherty,

et al., 2003; Small et al., 2001, 2003). The implication of these pre-

vious findings for the present results is that medial OFC may be en-

gaged under conditions where behavioural decision making based

on stimulus reward value is required (Bechara, Damasio, & Dama-

sio, 2000; Wallis, 2007). Recently, several studies have demon-

strated that medial OFC responses can be modulated by

top-down information such as knowledge of the price of a wine

(Plassmann et al., 2008), brand information (McClure, York et al.,2004), and visual word descriptors influence preference for odours

(de Araujo, Rolls, Velazco, Margot, & Cayeux, 2005). The novelty of

our results is that the representation of stimulus value, or possibly

intrinsic motivation, in medial OFC varies with expertise level to

such an extent that the experts displayed higher activation to the

building stimuli than the non-experts, but not to the control-stim-

uli, i.e. faces.

In contrast to OFC, voxels in the subcallosal part of the anterior

cingulate gyrus responded inversely to high and low ratings in the

experts compared to non-experts. This result supports the growing

recognition that anterior cingulate gyrus and OFC contribute dis-

tinct component processes to decision making (Rushworth, Beh-

rens, Rudebeck, & Walton, 2007). The anterior aspect of the

cingulate gyrus forms an anatomical interface between the OFCand premotor cortex. Since it also receives afferents from subcorti-

cal dopaminergic neurons and inputs from dorsolateral prefrontal

cortex, it has been suggested that the anterior cingulate integrates

the affective drive and action strategies for the purpose of selecting

appropriate motor responses, i.e. making decisions how to act

(Paus, 2001). Another possibility might be that subcallosal cingu-

late gyrus activity reflects the subjects monitoring of their own

emotional state (Ochsner et al., 2004), whereby appealing buildings

are more arousing to the experts than to the non-experts. Indeed,the subcallosal aspect of the cingulate gyrus has previously been

implicated in such forms of emotional processing, including the re-

call of happy autobiographical memories (Lane, Reinman, Ahern,

Schwartz, & Davidson, 1997) and attending to emotionally stimu-

lating words (Maddock, Garrett, & Buonocore, 2003). Interestingly,

decreasing musical dissonance, associated with an elevated experi-

ence of pleasure (Blood et al., 1999) and passive listening to unfa-

miliar, pleasant musical compared to a rest condition (Brown et al.,

2004) has also been shown to produce enhanced activity in subcal-

losal cingulate gyrus. Finally, as pupillometry data was not re-

corded in the present study we are unable to assess whether or

not such effects would have detected differences between the

two groups. Indeed there is evidence for involvement of the subcal-

losal cingulate in generating and monitoring autonomic interocep-

tive states (Critchley, 2004).

It is notable that while activity in OFC and the subcallosal cin-

gulate gyrus were sensitive to the level of expertise, the behav-

ioural responses did not parallel this difference in neural

activation between the two groups. As a number of previous

behavioural studies have found an effect of expertise on aesthetic

evaluation to be robust, our result was somewhat surprising

(Eysenck & Castle, 1970; Gordon, 1951/1952; Gordon, 1956;

OHare, 1976; Schmidt et al., 1989). One possible reason for this

discrepancy betweenour study and earlier ones couldbe the meth-

od of comparison used in our study. It is conceivable that compar-

ing means of rating is not sufficiently sensitive to detect

differences in experts and non-experts ratings. Experts and non-

experts are known to respond differentially to dimensions of stim-

ulus qualities such as craftsmanship and quality (Hekkert & vanWieringen, 1996b), or chromatic versus achromatic versions of

paintings (Hekkert & van Wieringen, 1996a). It is conceivable that

our set of buildings stimuli lack perceptual properties that system-

atically influence the differential aesthetic assessment of experts

and non-experts. On the other hand, the fact that we did not ob-

serve a behavioural difference in the two groups responses to

the building stimuli strengthens the neural result. If both a differ-

ence in behaviour and neural activity between the two groups had

been observed, the difference in neural activity might have been

confounded by the differences in behavioural responses. In the

present situation where the two groups differ in neural activity

but not in behaviour we can be sure that what we observe is a true

group difference.

Our finding of a positive bivalent response in the ventral stria-tum, specifically the left NAcc, in both subject groups and to both

stimuli types replicates and extends previous findings that NAcc

and OFC play different functional roles in reward processing (Knut-

son, Fong, Adams, Varner, & Hommer, 2001; ODoherty et al., 2002;

ODoherty et al., 2003; Tremblay& Schultz, 1999; Watanabe, 1999).

Whereas the OFC is thought to process reward outcomes, the NAcc

is generally believed to subserve the prediction of reward and to

compute the variance between reward expectation and the actual

reward (for reviews, see Knutson & Cooper, 2005; Montague, Hy-

man, & Cohen, 2004). Although earlier results have found non-lin-

ear response profiles in the NAcc as discussed below, to our

knowledge there has been no previous descriptions of NAcc activ-

ity with negative aesthetic ratings. Electrophysiological recordings

in animals have demonstrated that NAcc neurons increase theirresponse to positive reward prediction errors (situations that are

Fig. 6. The figure displays the interaction [Non-Expert_BuildNon-Expert_Fa-

ces]

[Expert_BuildExpert_Faces] from the zero-order parametric analysis thatshows brain areas activated, irrespective of the actual aesthetic ratings. The upper

panel displays a bilateral activation of the fusiform gyrus on slices where z-

coordinates for the three slices are ascending from 6, 4 and 2, respectively.

Evident on the slices are the collateral sulcus just lateral to the activation in the

fusiform gyrus. The lower panel displays the corresponding parameter estimates in

the right fusiform gyrus. The x-axis reflects the experimental conditions. The y-axis

shows BOLD signal changes. Activations are displayed atp < .001, uncorrected. Error

bars indicate 90% confidence interval.



8/10

better than expected) and decrease their response to negative pre-

diction errors (Apicella, Ljungberg, Scarnati, & Schultz, 1991;

Schultz, Apicella, Ljungberg, Romo, & Scarnati, 1993). Neuroimag-

ing work has subsequently replicated these findings (e.g., ODoher-

ty et al., 2006; Seymour, Daw, Dayan, Singer, & Dolan, 2007; Spicer

et al., 2007). However, recently another hypothesis has been put

forth, suggesting that activations of the ventral striatum are not

sensitive to errors in prediction, but rather encode salience dimen-

sions of the stimulus. This idea heralds from imaging studies where

the ventral striatum has been shown to correlate with prediction

errors regardless of valence (Jensen et al., 2007; Zink, Martin-Skur-

ski, Chappelow, & Berns, 2004). A recent fMRI study by Cooper and

Knutson (2008), though, suggests that the ventral striatum may

compute the interaction of valence and salience, depending upon

the context wherein motivational behaviour takes place. Directly

comparing degrees of valence and salience, Cooper and Knutson

found that both the valence and the salience of anticipated incen-

tives correlated with NAcc activation. More specifically, in this

study when outcomes were uncertain and salience high, NAcc acti-

vation increased for anticipated loss and gain, whereas NAcc acti-

vation increased for anticipated gain and decreased for

anticipated loss when outcomes were certain and salience low. In

our study the experimental set-up might be seen as similar to the

first situation (uncertain outcome and high salience). However, we

neither manipulated the salience of the pictures nor the relation

between anticipation and reward, so this remains conjecture. Since

it is possible that the subjects covertly anticipated the reward out-

come of the upcoming stimuli based on the recently transpired

judgment act, we cannot rule out the possibility that the NAcc acti-

vation reflects prediction error signalling.

The zero-order parametric regression analysis identified brain

regions showing a typological response to the two stimulus con-

ditions irrespective of aesthetic ratings. Hence, this analysis de-

tects differences in the two groups response to the stimulus

material beyond those differences specifically related to making

an aesthetic judgment. Inspection of the parameter estimates in

significant voxels from the interaction showed that experts hadsignificantly more activity in hippocampus, precuneus and cere-

bellum relative to non-experts for expert-stimuli (buildings) com-

pared to control-stimuli (faces). Precuneus is often reported to

play a role in integrating the current input with prior established

knowledge (Fletcher et al., 1995; Maguire, Frith, & Morris, 1999)

and in episodic memory retrieval (Krause et al., 1999). Our data

suggests that the demand on the precuneus is higher in experts

when perceiving expert-stimuli, as building conditions presum-

ably depend more on connections between retrieved information

and prior knowledge for this group relative to non-experts. The

hippocampus has also been consistently implicated in episodic

memories (Brown & Aggleton, 2001; Eichenbaum, Schoenbaum,

Young, & Bunsey, 1996; Eichenbaum, Yonelinas, & Ranganath,

2007). Hippocampus activation has been associated with condi-tions where subjects correctly recollect contextual information

compared to conditions where they do not (Cansino, Maquet, Do-

lan, & Rugg, 2002). Our findings support these data and suggest

that the hippocampus and precuneus may be selectively engaged

during memory retrieval in experts. As we have ruled out famil-

iarity effects in the data, experts may have attempted to organize

new information into a framework of prior knowledge and use

this information to guide and bias aesthetic judgments. The pos-

sibility that the hippocampus and the precuneus are specifically

involved in biasing preference judgments based on recruitment

of episodic memory has also been suggested by other studies

(Jacobsen et al., 2006; McClure et al., 2004). Specifically, a charac-

teristic of episodic memories in the present study might be in-

creased encoding of associations in experts (Eichenbaum et al.,2007) responding to expert-stimuli, which is dissociable from

stimuli recognized based on familiarity (Eldridge, Knowlton, Fur-

manski, Bookheimer, & Engel, 2000).

For the converse interaction analysis we found no activation in

areas involved in episodic memory formation. However, we found

activity in regions of the visual cortex and in the ventral temporal

cortex, such as the calcarine gyrus and in the fusiform gyrus. The

bilateral activation of the fusiform gyrus is interesting as this re-

gion, although distinctly demarcated by the collateral sulcus, isanatomically closely located to an area straddling the anterior

end of lingual gyrus which has been deemed the location of a

building-sensitive region (Aguirre, Zarahn, & DEsposito, 1998).

Further evidence for building selectivity shows that the medial

portion of the fusiform gyrus, including the collateral sulcus, dem-

onstrates greater fMRI signal change in response to buildings as

compared to faces and chairs (Ishai, Ungerleider, Martin, Schouten,

& Haxby, 1999). There is disagreement about the exact anatomical

location of a building-sensitive region, but it seems to include both

inferior lingual gyrus and the fusiform gyrus surrounding the col-

lateral sulcus. Our activation, clearly located in the fusiform gyrus,

is, however, distinct from the face-sensitive region within the fusi-

form gyrus (Kanwisher, McDermott, & Chun, 1997), which is lo-

cated inferior and lateral to our building-sensitive voxels. This is

furthermore evidenced by the parameter estimates in the build-

ing-sensitive region of the fusiform gyrus, where it is shown that

this area is unresponsive to face stimuli in both groups (see

Fig. 6). The region we observed in the fusiform gyrus is located just

adjacent to the parahippocampal gyrus. Several neuroimaging

studies have demonstrated that the posterior portion of the para-

hippocampal gyrus is involved in the representation of large-scale

places and scenes (Epstein& Kanwisher, 1998; Maguire, Frith, Bur-

gess, Donnett, & OKeefe, 1998). It is noteworthy that we observed

activity in the PPA in the conjunction analysis between [build-

ings > faces] for experts and non-experts. Evident in this conjunc-

tion is also activation, beyond the PPA, of the entire ventral

temporal cortex and visual cortex (see Supplementary material),

suggesting that the response to buildings is not restricted to the re-

gion that responds maximally to that object category located in thefusiform gyrus. However, this effect may also be driven by differ-

ences in visual stimulation across the two stimulus conditions, be-

cause building trials were presented with varying pixel width. The

fact that building stimuli activate the entire ventral temporal

cortex, albeit to varying degrees, suggests, in agreement with other

reports (Ishai et al., 1999), that the representation of buildings in

this portion of the cortex may be feature-based rather than build-

ing-sensitiveper se. Such an interpretation may account for the dif-

ferential activation of the fusiform gyrus between experts and non-

experts evident in the interaction analysis. The demand on this

portion of the fusiform gyrus is higher for non-experts compared

to experts presumably due to experts recruitment of episodic

memory, whereas non-experts are more sensitive to specific per-

ceptual features of building stimuli, which finds further supportby the relative stronger activation in the calcarine gyrus in non-ex-

perts relative to experts.

In conclusion, we have demonstrated that expertise modulates

brain areas to both aesthetic processing and to cognitive or typo-

logical processing irrespective of aesthetic ratings. Specifically,

our new discovery is that the representation of stimulus value in

medial OFC and bilateral subcallosal cingulate gyrus is modulated

by expertise. We found that only some regions associated with the

processing of reward are modulated by expertise (OFC, subcallosal

cingulate gyrus), while activity in NAcc was typical of both experts

and non-experts, suggesting that these regions play different roles

in reward processing. Furthermore, we have demonstrated that ex-

perts and non-experts differ in their neural response to expertise

stimuli per se, irrespective of aesthetic ratings. This typological re-sponse was observed bilaterally in the hippocampus and precu-

http://-/?-http://-/?-


9/10

neus, and suggests that experts may integrate current input into a

framework of prior knowledge and use this information to orga-

nize aesthetic judgments.

Acknowledgments

We thank Prof. S. Zeki, Dr. O.J. Hulme and Dr. T. Lund for helpful

discussions. Prof. C. Frith, Dr. M.Self,Dr. V. Cardin and Dr. T. Ramsy

provided useful comments on the manuscript. P. Neckelmann pre-

paredthe stimulusmaterial. U. Kirk was supportedby a Ph.D. schol-

arship from the Danish Medical Research Council; M. Skov was

supported by Hvidovre Hospitals research foundation; M.S. Chris-

tensen wassupported by a Ph.D. scholarship from theFacultyof Sci-

ence, University of Copenhagen; N. Nygaard was supported by a

Ph.D. scholarship by the Danish Research Council for the Humani-

ties. The MR-scanner was donated by the Simon Spies Foundation.

Appendix A. Supplementary data

The figure displays the building conjunction from the zero-or-

der parametric analysis derived from the building-specific main

effects for both groups [Expert_BuildExpert_Faces] and [Non-Ex-

pert_BuildNon-Expert_Faces]. Glass-brain activation is displayed

at FDR-corrected threshold. Supplementary data associated with

this article can be found, in the online version, at doi:10.1016/

j.bandc.2008.08.004.

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