Brain (2001), 124, 1720–1733
Changes in brain activity related to eating
From pleasure to aversion
Dana M. Small,1,3Robert J. Zatorre,1Alain Dagher,2Alan C. Evans2and Marilyn Jones-Gotman1
1Neuropsychology/Cognitive Neuroscience Unit,
2McConnell Brain Imaging Center, Montreal Neurological
Institute, McGill University, Montreal, Canada and
3Northwestern Cognitive Brain Mapping Group,
Northwestern University School of Medicine, Chicago, USA
Correspondence to: Dana M. Small, Northwestern
Cognitive Brain Mapping Group, 320 East Superior St
Searle 11-465, Chicago, IL 60611, USA
We performed successive H215O-PET scans on volunteers
as they ate chocolate to beyond satiety. Thus, the sensory
stimulus and act (eating) were held constant while the
reward value of the chocolate and motivation of the
subject to eat were manipulated by feeding. Non-specific
changes) were also present and probably contributed to
the modulation of brain activity. After eating each piece
of chocolate, subjects gave ratings of how pleasant/
unpleasant the chocolate was and of how much they did
or did not want another piece of chocolate. Regional
cerebral blood flow was then regressed against subjects’
ratings. Different groups of structures were recruited
selectively depending on whether subjects were eating
chocolate when they were highly motivated to eat and
rated the chocolate as very pleasant [subcallosal region,
caudomedial orbitofrontal cortex (OFC), insula/oper-
Keywords: feeding; taste; neuroimaging; motivation; orbitofrontal cortex
Abbreviations: ANOVA ? analysis of variance; BA ? Brodmann area; OFC ? orbitofrontal cortex; rCBF ? regional
cerebral blood flow
Early cortical representations of visual, auditory and
somatosensory information (e.g. ‘primary’ and ‘secondary’
areas) are in the unimodal neocortex. In contrast, the cortical
representations of the chemical senses (taste and smell) are
in the limbic and paralimbic cortex. This is true in primates
(e.g. Tanabe et al., 1975a, b; Pritchard et al., 1986; Takagi,
1986; Price, 1990; Baylis et al., 1995; Rolls et al., 1996;
Scott and Plata-Salaman, 1999) and in humans (Zatorre et al.,
1992; Jones-Gotman and Zatorre, 1993; Petrides and Pandya,
1994; Faurion et al., 1999; Pritchard et al., 1999; Small
et al., 1999). Thus, the representations of taste and smell are
in regions of the brain that are thought to be important for
© Oxford University Press 2001
culum, striatum and midbrain] or whether they ate
chocolate despite being satiated (parahippocampal gyrus,
caudolateral OFC and prefrontal regions). As predicted,
modulation was observed in cortical chemosensory areas,
including the insula and caudomedial and caudolateral
OFC, suggesting that the reward value of food is
represented here. Of particular interest, the medial and
lateral caudal OFC showed opposite patterns of activity.
This pattern of activity indicates that there may be a
functional segregation of the neural representation of
reward and punishment within this region. The only brain
region that was active during both positive and negative
compared with neutral conditions was the posterior
cingulate cortex. Therefore, these results support the
hypothesis that there are two separate motivational
approach and another
processing the internal and motivational state as well as the
affective significance of external objects. Stimulation with
taste and smell have been shown in neuroimaging studies to
be potent elicitors of brain activity in limbic regions such as
the amgydala, insula, orbitofrontal cortex, cingulate cortex
and basal forebrain (e.g. Zatorre et al., 1992; Small et al.,
1997b; Zald and Pardo, 1997; Sobel et al., 1998; Zald
et al., 1998; Francis et al., 1999; Royet et al., 2000; Savic
et al., 2000).
evoked by affective stimuli, including chemosensory stimuli.
For example, tastes (Zald et al., 1998; Francis et al., 1999),
Brain activity related to eating chocolate
Fig. 1 Rating scale. Subjects used the rating scale to respond to two questions following ingestion of
each piece of chocolate: (i) How pleasant or unpleasant was the piece of chocolate you just ate? (ii)
How much would you like or not like another piece of chocolate?
flavours (Small et al., 1997b), smells (Zald et al., 1997;
Francis et al., 1999; Royet et al., 2000), music (Blood et al.,
1999), sounds (Morris et al., 1999a), faces (e.g. Morris et al.,
1996; Lane et al., 1997; Phillips et al., 1997), photographs
(Lane et al., 1997a; Paradiso et al., 1999), pain (e.g. Coghill
et al., 1999; Tolle et al., 1999) and touch (Francis et al.,
1999) have been investigated by functional neuroimaging in
humans. However, in each case, different stimuli, or different
stimulus intensities, had to be used to represent different
hedonic valences. Recently O’Doherty and colleagues
modulated the reward value of banana odour by having
subjects eat bananas to satiety (O’Doherty et al., 2000).
Functional MRI was used to measure brain activity evoked
by the same banana odour before and after feeding. Activity
in the medial orbitofrontal cortex (OFC) decreased after
satiety in response to the banana odour but not in response
to a vanilla odour. This suggests that the medial OFC is
preferentially activated to odours when they are rewarding.
However, in this experiment the affective value was
manipulated only from pleasant to neutral, leaving aversive
unexplored. Furthermore, to our knowledge, no study has
investigated the neuronal correlates of changes in the reward
value of food produced by eating. Thus, despite the fact that
much of the non-human animal literature of reward and
stimulus–reward association learning is based upon feeding,
the neural substrates of the affective and motivational
components of feedingin
To investigate brain activity related to affective changes
associated with feeding, we performed successive H215O-
PET scans on volunteers as they ate chocolate to beyond
satiety. Thus the sensory stimulus was held constant, while
its reward value, measured by affective ratings (Fig. 1; see
also Methods), was manipulated by feeding. This paradigm
is unique in that changes in regional cerebral blood flow
(rCBF) can be attributed to changing reward value,
independent of sensory input and behaviour (eating).
Importantly, at the beginning of the experiment, eating the
chocolate is consistent with the subjects’ motivation, but as
the chocolate is eaten to beyond satiety, behaviour comes to
be inconsistent with subjects’ motivation. Thus, the same act
motivational state necessarily occurs over time, the effects
of order almost certainly contribute to neural activity.
Additionally, non-specific effects, such as autonomic and
visceromotor changes, which are intrinsic to both eating and
modulation of the reward value of food, were not assessed
and thus cannot be disentangled from the overall neural
We predicted that rCBF would be modulated by the reward
value of the stimulus in chemosensory regions, including
the insula/operculum and orbitofrontal cortex, reflecting the
involvement of these regions in both sensory and limbic
aspects of the neural representation of food. Additionally, we
expected that structures proposed to be involved in the
initiation of feeding, such as the striatum and dopaminergic
midbrain (Rolls, 1993), would be selectively active when
subjects were motivated to eat chocolate and that the
prefrontal cortex, which has been proposed to be involved
in the decision to terminate eating (Tataranni et al., 1999),
would become increasingly active as subjects became
increasingly motivated not to eat. We also predicted
modulation of rCBF in limbic areas previously implicated in
the positive and negative evaluation of sensory stimuli, and
reward and punishment, including the subcallosal region,
OFC, cingulate cortex, basal ganglia and anterior temporal
lobe structures. Finally, we studied positive or negative
changes in linear rCBF in specific brain regions as an
indication of the extent to which that region is either
preferentially activated by eating chocolate when it is
‘pleasant and rewarding’ versus ‘unpleasant and punishing’
or vice versa.
Pilot testing was conducted to determine what type of
chocolate to use. Fifteen healthy subjects were asked to rank
20 kinds of chocolate from the most to the least pleasant.
Lindt bittersweet (50% cocoa) and Lindt milk chocolate were
consistently ranked as the most pleasant; however, subjects
who preferred the bittersweet did not like the milk chocolate
and subjects who preferred the milk chocolate did not like
the bittersweet chocolate. In the PET experiment we therefore
decided to give subjects the choice between Lindt bittersweet
and milk chocolate. Two subjects chose bittersweet and seven
subjects chose milk chocolate.
D. M. Small et al.
Nine healthy, right-handed volunteers who claimed to be
chocolate-lovers participated in this study. Status as a
chocolate-lover was determined by rating the subject on a
scale from 1 to 10, where 10 referred to ‘chocoholic’ and
zero was neutral; all subjects’ ratings fell between 8 and 10.
Five were women and four were men. All had eaten breakfast
~4.5 h prior to scanning, which took place in the early
afternoon (12.30 hours). Hunger ratings, made on a scale of
1–10, where 10 corresponded to starving, 0 to very full and
5 to neither hungry nor full, indicated that subjects were in
the range of not hungry to mildly hungry (ratings between 5
and 7) at the beginning of the experiment. All subjects gave
informed consent to participate in the study, which was
approved by the Ethics Committee of the Montreal
PET scans were performed with a Siemens HR? scanner in
3D acquisition mode, using the H215O water bolus technique
to measure rCBF (Raichle et al., 1983). Each subject also
received an MRI scan for anatomical registration of PET
data (Collins et al., 1994) and resampling into a standardized
Subjects underwent seven identical ‘chocolate scans’. In
each, ~10 s before scanning, subjects were given one square
of chocolate and instructed to eat it by letting it melt in their
mouth. Immediately after the scan was completed, subjects
indicated how pleasant or unpleasant they found that piece
of chocolate [question (i)] and how much they would like or
not like to have another piece [question (ii)], using the
rating scale shown in Fig. 1. Independent pilot testing with
20 subjects had suggested that these aspects of affective
evaluation of chocolate were different. Specifically, subjects
commonly reported that the chocolate still tasted pleasant
but that they did not want to eat any more. Therefore, in the
final version of the paradigm we included both ratings in
order to capture as much information as possible about the
subjects’ subjective state. There were two main goals of
these ratings. First, we wanted to have a measure of subjective
state to determine how much chocolate to feed each subject.
Secondly, we wanted to be able to regress rCBF against a
value other than scan number in case changes in subjective
affective state did not decrease in a linear fashion. Prior to
the next scan, subjects were fed chocolate, one square at a
time, making both ratings after eating each piece, until the
rating dropped by at least two points. There was a rest period
of at least 5 min between the termination of eating and the
beginning of the next scan, to reduce the possibility of
habituation. In total, subjects ate between 16 and 74 squares
of chocolate, corresponding to between half and two-and-a-
half 85 g bars of chocolate.
In addition to the chocolate scans, we included three
control scans to address potential order effects. Specifically,
one ‘water scan’ (5 ml of water was injected slowly into the
subject’s mouth over the course of the scan) was included
before the first (‘water-pre’) and after the last (‘water-post’)
chocolate scan. In the final scan, subjects were asked to
move their tongue as though they had chocolate in their
mouth, making a total of 10 scans. The entire protocol is
depicted in Fig. 2.
Regression maps (Paus et al., 1996) were calculated to assess
the significance of the relationship between affective ratings
and rCBF. Regression analysis involves correlating rCBF
with incremental changes in a specific experimental variable.
The data set for this analysis consisted of normalized CBF
values obtained in each subject during each of the seven
chocolate scan conditions, yielding a total of 63 image
volumes. The effect of variation in affective rating (ii) was
assessed by means of analysis of covariance, with subjects
as a main effect and the affective rating as a covariate. The
following model was fitted: E(yij) ? ai? bPsij, where yijis
the normalized CBF of subject i on scan j, and sijis the
motivation rating at scan j. The subject effect (ai) is removed
and the parameter of interest is the slope bPof the effect of
the change in affective rating on CBF. Values equal to or
exceeding a criterion of t ? 4.4 for unpredicted peaks were
deemed significant (P ? 0.05, two-tailed). This yielded a
false-positive rate of 0.025 in 200 resolution elements (which
has dimensions of 14 ? 14 ? 14 mm for the main analysis)
if the volume of brain grey matter is 500 cm3(Worsley et al.,
1996). For predicted peaks, values equal to or exceeding a
criterion of t ? 3.2 were considered significant, yielding a
false-positive rate of 0.025 in 1.5 resolution elements in
2 cm3(Worsley et al., 1996).
Since satiety is a phenomenon that unfolds over time, we
introduced several measures to decipher non-specific time
effects from time effects associated with satiety. First, we
employed covariation, a statistical technique designed to
dissociate linearly related variables and then partial out the
effect of the selected variable. Whereas this significantly
reduces the likelihoodof false-positive errors, italso increases
the likelihood of false-negative errors due to the high degree
of multicollinearity between scan order and affective ratings.
Secondly, three control scans (water-pre, water-post and
tongue movement) were also included in our study design to
isolate scan order effects. Specifically, rCBF between the
two water scans, which were identical except for their order
in the experiment, could be compared in areas of interest
(determined by the regression analysis and predictions); if
there was no difference in activation in a region, we reasoned
that linear increases or decreases were unlikely, because of
the effect of scan order.
Finally, subtraction analysis (Worsley et al., 1992) was
performed to identify regions that may have responded non-
linearly to increasing satiety. Specifically, the fourth chocolate
scan, with affective ratings near neutral, was subtracted from
Brain activity related to eating chocolate
Fig. 2 Pictorial representation of protocol. Purple bars represent water PET scans and turquoise bars
represent chocolate PET scans. The tongue movement scan is represented by a blue bar. Interscan
intervals consist of a feeding period and a rest period. The amount of chocolate eaten to produce the
required decreases in affective ratings obtained from questions (i) and (ii) decreased gradually as the
experiment progressed. This is depicted by the shrinking feed periods. Colour-coded bar graphs in
Fig. 3 correspond to the colour scheme used here.
the first and last chocolate scans, in which affective ratings
were high regardless of valence. These three chocolate scans
(Choc 1, Choc 4 and Choc 7) were also each subtracted from
the first scan (water-pre) and the ninth scan (water-post).
Regression of rCBF in each of seven chocolate scans
(Choc 1 – Choc 7) against the ratings to question (ii) (‘How
much would you like or not like another piece of chocolate?’)
revealed significant rCBF decreases (as ratings changed from
positive to negative) in the midline subcallosal region and
midbrain; bilaterally, the inferior and middle temporal gyri,
dorsal insula/frontal operculum, caudomedial OFC and
caudate nucleus; on the right, in the occipitotemporal gyrus,
dorsal insula/frontal operculum and ventral insula; and on
the left, in the thalamus and putamen (Table 1) (Fig. 3A–C).
When this analysis was performed with the ratings to question
(i) (‘How pleasant or unpleasant was the piece of chocolate
you just ate?’), similar results were obtained. Therefore, we
report only the results from the ratings given to question (ii).
When the regression equation was performed with scan
gyri and left insula remained significant. This analysis suffers
from a propensity to false-negative error due to the shared
variance associated with the linear relationship between the
psychophysical ratings and scan order. Therefore, the areas
that remain after this more stringent analysis are robustly
related to the psychophysical ratings but not to scan order.
However, given the likelihood of false-positive errors, we
also considered peaks in the context of the literature (see
Subtraction of the water-pre scan from the water-post scan
revealed similar activity bilaterally in the dorsal insula, right
ventral insula, thalamus, midbrain, left ventral striatum and
hippocampus, suggesting that rCBF changes were due to
eating chocolate as opposed to scan order (Table 2). This
relationship is depicted graphically in Fig. 3. Specifically,
graphs of absolute rCBF changes in each of the 10 scans
were constructed for spherical volumes with an 8 mm radius
surrounding a given peak. Graphing the data in this way
illustrates that rCBF was sensitive to condition and not
simply scan order in many of the predicted peaks that were
not significant after scan order was factored out.
Since the subcallosal peak was very large in both extent
and magnitude, and since it is in a heterogeneous cortical
region, in heterogeneous cortex, the data were reanalysed
with reduced blurring (9 mm full width half maximum) to
ascertain if there were in fact multiple areas of activity. In
addition to the initial subcallosal peak, this analysis resulted
in the emergence of bilateral caudomedial orbitofrontal
activations, probably corresponding to area 13 (Table 1).
Both peaks remained significantly active with scan order
covaried out (t ? 3.6 on the right and t ? 3.8 on the left).
Regions where rCBF increased as ratings moved from
positive to negative included the precentral gyri [Brodmann
area (BA) 4] and the medial frontal gyri (BA 6, 8) [on the
right, two peaks within the caudolateral OFC; on the left,
the inferior (area 45/46) and middle frontal gyri (BA 6)]
(Fig. 3D and Table 2). When the regression was performed
with scan order covaried out of the equation, the peaks within
the motor and premotor areas disappeared. In contrast,
rCBF changes were greater in all other locations (Table 2).
Additionally, two peaks in the anterior cingulate cortex that
almost reached significance in the original regression were
clearly significant with scan order covaried out. This was
also true of blood flow in the right parahippocampal gyrus
(BA 28/36). Areas where there were no rCBF differences
supplementary motor area, caudolateral orbitofrontal cortex,
cingulate, parahippocampal gyrus and left inferior frontal
gyrus. For areas exhibiting rCBF increases during the
experimental scans, this relationship is depicted graphically
in Fig. 3.
To identify regions that may have responded non-linearly
to increasing satiety, we performed subtraction analyses
D. M. Small et al.
Table 1 rCBF decreases with decreasing reward value
Choc 1–7 Water†
Left inferior temporal gyrus
Right inferior temporal gyrus
Right dorsal insula/operculum*
Left dorsal insula/operculum*
Right lateral occipitotemporal gyrus/cerebellum
Left lateral occipitotemporal gyrus/cerebellum
Right middle temporal gyrus
Left middle temporal gyrus
Right caudomedial OFC
Left caudomedial OFC
Right ventral insula
Left caudate nucleus
Right caudate nucleus
*Peaks shown in Fig. 3.†t-Values from the subtraction water-pre minus water-post.‡The value of t
remained significant when scan order was covaried out of the regression equation.
comparing CBF in scans with corresponding ratings that
differed the most from neutral (Choc 1 and Choc 7) with
CBF in scans where ratings were near neutral (water-pre,
water-post and Choc 4). Eight subtractions were performed
and are summarized in Table 3. A peak located in the
posterior cingulate cortex was present in both affective
chocolate scans (Choc 1 and Choc 7) compared with the
neutral chocolate scan (Choc 4) and in both water baseline
scans (water-pre and water-post) compared with the neutral
chocolate scan. In some cases the t value was slightly below
significance (Table 3 and Fig. 3E). However, we did not
covary non-linear time effects out of the equation, and these
cannot be precluded from an interpretation of this result.
Repeated measures analysis of variance (ANOVA) of
the psychophysical data revealed a significant interaction,
indicating that the difference in slope between the ratings
given in response to question (i) and question (ii) was
significant [F(1,8) ? 22, P ? 0.002]. Thus, motivation to
eat declined more rapidly and to a greater extent than
evaluation of pleasantness (Fig. 4). While these scales are
only ordinal, it was nevertheless clear that there were points
during the experiment when subjects did not want to eat
chocolate but still found the chocolate pleasant. Since the
psychophysical results indicated a difference in these two
aspects of evaluation (at a single point in time) but the
original regressions of each type of rating with blood flow
did not reveal any differences, we compared the results of
both analyses [rCBF regressed against ratings from questions
(i) and (ii)] with scan order covaried out of the equation. In
effect, these analyses reduced the total variance, increased
sensitivity and allowed a more direct comparison between
rCBF related to the two different ratings. The comparison
revealed a peak in the retrocalcarine sulcus close to the
isthmus (at 26, –54, 12), which correlated with ratings given
to question (ii) to a greater extent than ratings given to
question (i) (t ? –8.7 compared with t ? –3.7) (Fig. 3F).
Specifically, blood flow increased with increasing motivation
not to eat. This region has been shown recently to be part of
the retrosplenial limbic cortex (Morris et al., 1999).
A repeated measures ANOVA was also carried out to
compare psychophysical data from nine pilot subjects who
performed the identical experiment but who were sitting at
a table as opposed to lying in a scanner with the data from
subjects who participated in the PET study. There was
no difference in the affective ratings between the groups
[F(1,15) ? 0.007, P ? 0.97]. This indicated that the
pleasantness of chocolate and the motivation to eat declined
at the same rate regardless of the experimental context.
Consequently, it is unlikely that there was an interaction
between the increasing unpleasantness of lying in the scanner
and the increasing unpleasantness of the chocolate.
Eating chocolate while its reward value was manipulated by
feeding resulted in differential engagement of the limbic,
neocortical and chemosensory areas (Fig. 3). Thus, different
groups of structures were recruited selectively, depending on
whether subjects were eating chocolate when they were
highly motivated to eat and rated the chocolate as very
pleasant or whether they ate chocolate despite being satiated.
Brain activity related to eating chocolate
Fig. 3 Cortical regions demonstrating significant rCBF correlations with affective rating for question (ii). Regression analyses were used
to correlate rCBF from averaged PET data (Choc 1 minus Choc 7) with affective ratings taken immediately after these scans (see
Methods). Correlations are shown as t statistic images superimposed on corresponding averaged MRI scans. The t statistic ranges for
each set of images are coded by colour bars, one in each box. Bar graphs represent normalized CBF in an 8 mm radius surrounding the
peak. The y-axis corresponds to normalized activity and the bars along the x-axis represent scans. The three colours represent scan type
and correspond to the coloured bars in Fig. 2. Each bar graph corresponds to activations indicated by a turquoise line. (A) Coronal
section taken at y ? 1 showing the decrease in rCBF in the primary gustatory area (bilaterally in the anterior insula/frontal operculum
and in the right ventral insula). (B) Coronal section taken at y ? –26 showing decreases in rCBF in the left thalamus and medial
midbrain (possibly corresponding to the ventral tegmental area). (C) Sagittal section taken at x ? –1 showing decreases in rCBF in the
subcallosal region, thalamus and midbrain. (D) Sagittal section taken at x ? 42 showing the increase in rCBF in the right caudolateral
orbitofrontal cortex. Activation is also evident in the motor and premotor areas. (E) Sagittal section taken at x ? 8 showing an increase
in rCBF in the posterior cingulate gyrus (peak at 8, –30, 45) in subtraction analysis Choc 1 – water-post (see Table 3 and Results
section). This was the only region where CBF was consistently greater in affective scans regardless of valence, compared with the
neutral chocolate scan (Choc 4) and the two water baseline scans (water-pre and water-post). (F) Horizontal section at z ? 12 showing
an increase in rCBF in the retrosplenial cortex (area 30) that correlated with affective rating (ii) but not the affective rating (i) when scan
order was covaried out of the regression analysis (see Results and Methods).
The cortical chemosensory areas
As predicted, activity in regions that probably correspond to
the cortical gustatory areas was modulated by changes in the
reward value of the chocolate (Fig. 3A and D), suggesting
processing of taste in humans. Specifically, as the reward
value of the chocolate decreased, rCBF decreased bilaterally
in the insula in regions shown by previous neuroimaging
studies to represent the primary gustatory area (Kinomura
et al., 1994; Small et al., 1997a, b, 1999; Zald et al., 1998;
Faurion et al., 1999; Francis et al., 1999). In contrast, rCBF
increased with decreasing reward value in a region of the
caudolateral OFC, which has been implicated in gustatory
processing in humans (Small et al., 1997a, b, 1999) and has
been suggested to represent a secondary gustatory area by
Rolls and colleagues (Rolls et al., 1990). When scan order
D. M. Small et al.
Table 2 rCBF increases with decreasing reward value
Choc 1–7 Water†
Left precentral gyrus
Right precentral gyrus
Right supplementary motor area
Left middle frontal gyrus
Medial frontal gyrus
Right caudolateral orbitofrontal cortex*
Right caudolateral orbitofrontal cortex*
Left inferior frontal gyrus
Right cingulate cortex
Right parahippocampal gyrus
*Peaks shown in Fig. 3.†t-Values from the subtraction water-pre minus water-post.‡The value of t
remained significant when scan order was covaried out of the regression equation.
Fig. 4 Average affective rating to questions (i) and (ii) across the
seven chocolate conditions. Dotted line depicts ratings to question
(i) (Pleasantness) and the solid line represents ratings to question
(ii) (Motivation). Error bars represent the standard error of the
mean. Ratings correspond to the rating scale shown in Fig. 1.
Repeated measures ANOVA revealed a significant interaction,
indicating that the slopes of the two lines are different (see
was covaried out of the regression equation, rCBF changes
in the left anterior insula and bilaterally in the caudolateral
OFC remained significant. Thus, even when scan order
was covaried out, modulation was observed in the cortical
gustatory areas. Moreover, there was no difference in rCBF
in these regions in the comparison of the two water scans,
performed at the beginning and end of the session, indicating
that rCBF changes were probably related to the changes in
the affective and motivational value of the chocolate and not
simply to an effect of scan order (see Results and Fig. 3).
Electrical stimulation of the human insula elicits alterations
in gastrointestinal motility, taste hallucinations and a variety
of sensations associated with the digestive tract (Penfield and
Faulk, 1955). Neuroimaging studies have shown this region
to be sensitive to various processes related to feeding,
including odour (Zatorre et al., 1992; Small et al., 1997b;
Fulbright et al., 1998; Francis et al., 1999), taste (Small
et al., 1999), tongue somatosensory stimulation (Pardo et al.,
1997), swallowing (Hamdy et al., 1999), facial expressions
of disgust (Phillips et al., 1997), thirst (Denton et al., 1999)
and hunger (Tataranni et al., 1999). In accordance with these
studies, O’Doherty and colleagues recently reported that
odour-induced insular activation may be attenuated following
satiation with the food related to that odour (in one of six
subjects in their study) (O’Doherty et al., 2000). The anterior
insula is also consistently activated in studies using
emotionally salient tasks or sensory stimulation (e.g. Breiter
et al., 1997; Kosslyn et al., 1996; Lane et al., 1997b; Thut
et al., 1997; Coghill et al., 1999; Morris et al., 1999a).
The overlapping representation of affective, sensory and
autonomic functions in the insular region is consistent with
our result in supporting a role for the insula in feeding
area may be better conceptualized as the ingestive cortex as
opposed to a strictly sensory area. However, the multimodal
nature of this region also raises the possibility that the insular
modulation we observed may be related to numerous aspects
of feeding in addition to the changes in reward value of the
Taste-responsive cells in the monkey are not modulated
by satiety until the OFC (Rolls et al., 1988, 1989);
furthermore, OFC taste cells decrease firing with satiety
(whereas we report increased blood flow in an analogous
region of OFC). There are several explanations for the
discrepancy between the single-cell recordings and our
findings. First, there are many examples of interspecies
differences in the gustatory system. For example, in rats,
physiological state has been shown to modulate the taste
response as early as the brainstem (Jacobs et al., 1988).
Brain activity related to eating chocolate
Table 3 t-Values of activity in the posterior cingulate cortex in affective compared with neutral scans
Area Ch1–Ch4Ch7–Ch4Ch1–wpreCh1 wpost Ch4–wpreCh4–wpost Ch7–wpreCh7–wpost
Posterior cingulate gyrus3.2 220.127.116.11*–– 2.5 3.8
Ch ? Choc; wpre ? water-pre; wpost ? water-post. *Peak shown in Fig. 3.
Secondly, it is possible that our results are not contradictory
but reflect a manifestation of the different scopes of the two
methods (single-cell recording versus PET). For example,
the electrophysiological studies could be biased in that cells
must first display a response to taste in order to be
investigated, and thus cells that increase response in the OFC
with satiety could be missed. Or perhaps both response
profiles exist in the human and are simply not discernible by
PET. Finally, the representation of taste in the insula and
OFC is sparse (~4% of the cells respond to taste) (Yaxley
et al., 1990). Consequently, it is impossible to know if the
CBF changes we observed reflect activity of taste neurones
per se rather than the modulation of cells responding to
reward value or some autonomic aspect associated with being
fed chocolate. In any case, the differential engagement of
the cortical gustatory areas suggests that in humans taste
cells have access to information regarding the internal state
and reward value of the stimulus. Such an organization
represents a departure from classical notions of sensory
organization, which is based mostly upon examination of the
visual and auditory modalities, both of which have primary
cortical representation in the unimodal neocortex.
Differential activity was not observed in the primary
olfactory region, thought to be located in the pyriform region
of humans (Zatorre et al., 1992; Small et al., 1997b; Dade
et al., 1998; Sobel et al., 1998; for review, see Zald and
Pardo, 2000; Zatorre and Jones-Gotman, 2000). This area
does not appear to be sensitive to olfactory sensory-specific
satiety (O’Doherty et al., 2000), although it is sensitive to
subtle cognitive manipulations (Dade et al., 1998) and
different parameters associated with sniffing (Sobel et al.,
1998). The pyriform region has also been characteristically
difficult to image with PET because of rapid habituation of
the odour-induced response (Sobel et al., 2000). Therefore,
our failure to observe modulation may reflect the insensitivity
of PET to temporal events as opposed to insensitivity of the
region to changes in reward value or perceptual experience.
Activity was observed in a region of the medial OFC that
may correspond to the putative secondary olfactory area
(Zatorre et al., 1992). Here activity decreased as motivation
to eat decreased. This result is consistent with single-cell
recording studies of olfactory sensory-specific satiety in this
region (Critchley and Rolls, 1996) and with the functional
MRI study by O’Doherty and colleagues reporting that the
response of the medial OFC to an odour decreases after
subjects eat a related food to satiety (Doherty et al., 2000).
However, bimodal taste and smell-responsive cells and
neurones that respond to the presence of fat in the mouth
have been found throughout the caudal OFC (Rolls and
Baylis, 1994; Rolls et al., 1999), suggesting that neural
processing in this area may give rise to flavour perception
in monkeys. Therefore, the changes observed in OFC activity
as opposed, or in addition, to unimodal taste and smell
We speculate that one reason for this integrated relationship
between sensory and limbic processing of taste is that the
brain regions involved in the processing of sensory stimuli
that are primarily reinforcing, such as tastes and pain,
developed in tandem with the limbic structures for the
common purpose of avoiding danger (i.e. toxins and bodily
harm) and incorporating nutrients for survival. This integrated
relationship may account for phenomena such as single-trial
conditioned taste aversion learning, in which the insula has
been implicated (Gutierrez et al., 1999) and for which there
are clear adaptive advantages. It may also support addictive
ingestive behaviour, including overeating and drug abuse, as
well as the generation of drive and craving states (e.g. hunger
and addiction). For example, Wise suggests that the brain
circuitry underlying addiction originally developed to
subserve feeding behaviour (Wise, 1997). Our results support
this hypothesis, as the structures selectively active when
ratings indicated that the chocolate had a strong positive
valence overlap considerably with areas where increases
in rCBF were evoked by cocaine versus saline injection
(subcallosal region, caudate, putamen, thalamus, hippo-
campus, insula and ventral tegmentum) (Breiter et al., 1997).
Moreover, in addition to hunger (Tataranni et al., 1999) and
thirst (Denton et al., 1999), both the insula and the OFC
have been implicated in drug cravings (Wang et al., 1999).
In the present study, both the insula and the caudomedial
OFC were active only when subjects were highly motivated
to eat the chocolate. Interestingly, chocolate has been
identified as the single most craved food in studies of food
cravings (Rozin et al., 1991), and chocolate addiction has
been described (Hetherington and MacDiarmid, 1993).
The observation that the primary gustatory area and the
chemosensory regions of the OFC are modulated by satiety
suggests that these areas play a role in feeding behaviour in
addition to sensory processing. The striatum, which has been
proposed as a crucial structure for the initiation of feeding
(Rolls, 1993), receives feeding-related projections from both
the insula (Chikama et al., 1997) and the caudomedial OFC
D. M. Small et al.
(Haber et al., 1995), which is itself connected to the laterally
located secondary gustatory area (Carmichael and Price,
1996). In the present study, rCBF in the dorsal striatum and
caudomedial OFC decreased as motivation to eat declined.
This result is also in accordance with the results of Tataranni
and colleagues, who reported activity in these regions in a
comparison of eyes closed resting and hungry with eyes
closed resting and satiated (Tataranni et al., 1999). These
results suggest that the insula, striatum and caudomedial
OFC are part of the neural network underlying the initiation
of feeding. Interestingly, whereas we observed that activity
in the midbrain (in the region of the ventral tegmental area)
and subcallosal region correlated with eating chocolate when
it is judged as pleasant, Tataranni and colleagues observed
no change in these regions in the hungry state compared
with the satiated state. One difference between the present
study and the study by Tataranni and colleagues is that the
subjects in our study received a rewarding stimulus during
scanning, whereas their subjects were scanned after eating.
This discrepancy is consistent with the proposal that the
dopaminergic midbrain mediates the reward value of food
(e.g. Mirenowisz and Shultz, 1996; Richardson and Gratton,
1998; Ahn and Phillips, 1999).
In contrast, rCBF in several motor and premotor areas, the
left lateral prefrontal cortex (left middle and inferior frontal
gyri), the bilateral OFC, the right anterior cingulate and the
right parahippocampal gyrus increased with satiety. The
anterior cingulate and parahippocampal gyrus have been
reported to be involved in the affective evaluation of sensory
stimuli (discussed below), but to our knowledge have not
been implicated directly in feeding. Tataranni and colleagues
reported rCBF increases with satiety in the dorsolateral
prefrontal cortex and speculated that, since the prefrontal
cortex has been shown to participate in the inhibition of
inappropriate behaviours, this region may be important in
decisions to terminate feeding (Tataranni et al., 1999). Our
result supports this hypothesis, and also suggests that, as in
non-human primates (Rolls, 1997), the caudolateral OFC
may also be a part of the neural network underlying feeding
Regional CBF changes were not observed in the amygdala.
The amygdala has been shown previously to be activated by
aversive tastes (Zald et al., 1998), smells (Zald et al., 1997)
and flavours (Small et al., 1997a), and single-cell recording
studies in the monkey suggest that at least some taste cells
are sensitive to satiety (Yan and Scott, 1996). There is also
some evidence that the human amgydala is sensitive to
sensory-specific satiety of odours (O’Doherty et al., 2000).
There are several reasons why we may not have observed
activity here. First is the potential for interspecies differences.
Secondly, it is possible that excitatory and inhibitory activity
cancelled each other out, rendering changes undetectable by
PET (Yan and Scott, 1996). However, it is also possible that
the amygdala is involved in evaluation of the affective
valence of chemosensory stimuli when the association should
be more permanent. Thus, amygdala activation is seen in
response to aversive tastes or to odours such as intestinal
gas (Zald et al., 1997), which will always be aversive, and
in rats it is involved in conditioned taste aversion learning
(e.g. Yamamoto et al., 1994). In contrast, affective evaluation
corresponding to satiety must be flexible, as satiety is
transient, varying with a changing internal state. Our results,
specifically the activity observed in the caudolateral
(secondary gustatory area) and caudomedial OFC, are in
agreement with the suggestion of Rolls and colleagues, based
on the results of electrophysiological experiments in monkeys
of stimulus reversal learning, that the orbitofrontal cortex is
more important for flexible stimulus–reward associations
(e.g. Rolls, 1993).
The largest area of rCBF change observed in our study was
in the subcallosal region. This was also the most robustly
activated region in a similarly designed study using musical
dissonance to modulate the affective valence of a tune (Blood
et al., 1999). In both studies, regression analysis revealed
that rCBF decreased as pleasantness decreased, as a function
of either increasing satiety or increasing dissonance. Clinical
evidence indicates that damage to this region results in
disruption of goal-directed actions, which are guided by
motivational and emotional factors (for review, see Damasio,
1994), and in rats it has been demonstrated that damage to
the medial OFC results in the inability of a cue to access
representational information about the incentive value of
associated reinforcement (Gallagher et al., 1999). Together,
these results suggest that the subcallosal medial prefrontal
region subserves a variety of behaviours guided by
motivational and emotional factors, including feeding. rCBF
in the caudomedial OFC also followed this pattern of activity
(i.e. rCBF decreased with increasing satiety or dissonance),
which is consistent with the postulated involvement of this
area in stimulus–reward association learning (e.g. Rolls,
1996). A final similarity between our study and the musical
study by Blood and colleagues was increasing rCBF in the
right parahippocampal region as the stimuli became more
region, caudomedial OFC and parahippocampal gyrus were
activated even though scan order was counterbalanced, and
in the present study all three regions were still significantly
activated when scan order was covaried out of the regression.
Medial versus lateral OFC activity
The opposite pattern of rCBF was observed in the medial
compared with the lateral OFC. As eating chocolate changed
from rewarding to aversive, rCBF decreased in the medial
OFC and increased in the immediately adjacent lateral OFC.
Above, we have interpreted these results in relation to the
Brain activity related to eating chocolate
feeding. However, the same region of the OFC that is
implicated in taste and smell is thought to be involved
in stimulus–reward association learning (e.g. Iversen and
Mishkin, 1970; Rolls, 1996) in monkeys, and human
neuroimaging studies of emotional state, reward, punishment
and the affective evaluation of non-chemosensory stimuli
consistently report OFC activation (e.g. Thut et al., 1997;
Blair et al., 1999; Blood et al., 1999; Morris et al., 1999;
Rogers et al., 1999; Damasio et al., 2000; O’Doherty et al.,
2001). Moreover, since food is often used as the primary
reinforcer in stimulus–reward association learning paradigms,
Carmichael and Price have suggested that higher-order
processing of the sensory attributes of food in the OFC may
provide the sort of hedonic representation that underlies
much of what is meant by the term ‘reward’ (Carmichael
and Price, 1996).
A similar dissociation between medial and lateral OFC
activity has been noted by O’Doherty and colleagues
(O’Doherty et al., 2001). In their study, subjects performed
an emotion-related visual reversal-learning task while
undergoing functional MRI scanning. Lateral OFC activation
was found in response to a punishing outcome, whereas
medial OFC activation occurred in response to a rewarding
outcome. These results suggest that the neural representations
of reward and aversion are separated within these regions.
Elliott and colleagues have also described a dissociation
between medial and lateral OFC function based on a review of
functional neuroimaging studies conducted in their laboratory
(Elliott et al., 2000). These authors suggest that the medial
OFC is involved in monitoring and holding in mind reward
values, whereas the lateral OFC is recruited when a response
previously associated with a reward has to be suppressed.
Our results partially support this notion. Here, the medial
OFC is active when subjects report that eating chocolate is
rewarding. During this time, their behaviour is in accordance
with their will. As their desire to eat decreases and their
behaviour (eating) comes to be inconsistent with their will
(indicated by their affective ratings), the medial OFC activity
decreases and the lateral OFC activates. Thus, in the present
study, lateral OFC activity occurs when the desire to stop
eating must be suppressed in order to conform to the demands
of the experiment.
Posterior cingulate cortex
Subtraction analysis (see Results) revealed only one
significant non-linear effect in this experiment. Specifically,
rCBF in the posterior cingulate cortex was higher when
subjects rated chocolate as highly pleasant or highly
unpleasant than when they rated it as neutral (Table 3 and
Fig. 3E). As further verification of this effect, we compared
the pleasant and unpleasant chocolate scans individually with
the two neutral water baseline scans (water-pre and water-
the posterior cingulate to a greater extent than did the neutral
water scans. This result is in accordance with Maddock, who,
in a recent review of the neuroimaging literature, concluded
that this is the brain area that is most consistently activated by
emotionally salient stimuli, regardless of valence (Maddock,
1999). Thus, our finding suggests at least some overlap
between the brain regions involved in processing positive
and negative valenced stimuli. However, since this is the
only region we observed with such an rCBF response profile,
our study supports the notion (LeDoux, 1996) that different
neural substrates underlie two motivation systems, one
dealing with positive/appetitive stimuli and a second dealing
with negative/aversive stimuli.
Finally, in the present study, the subjects’ ratings in
response to question (ii) (‘How much would you like, or not
like to have another piece of chocolate?’) decreased faster
and to a greater extent than their ratings to question (i) (‘How
pleasant or unpleasant was the chocolate that you just ate?’)
(Fig. 4). In other words, there was a point in time at which
subjects reported that the chocolate tasted pleasant, yet they
did not want to eat any more. Although question (i) required
the subject to think about the pleasantness of the chocolate
eaten immediately prior to the question, whereas question
(ii) required the subject to report how motivated they were
to eat a piece of chocolate in the immediate future, we feel
the ratings we have collected capture two different subjective
states that cannot be accounted for by time alone. Berridge
and colleagues have described a dissociation between taste
reactivity measures (characteristic responses to pleasant or
aversive tastes) and acceptance or rejection behaviours in
rats (for review, see Berridge, 1996). These two states are
described as ‘liking’ and ‘wanting’, respectively. It is possible
that the ratings we have gathered depict these two dimensions
of affective evaluation, question (i) addressing liking and
question (ii) addressing wanting. We therefore decided to
pursue our psychophysical result. When scan order was
covaried out of the regression equation, a region of the
retrosplenial cortex, probably corresponding to limbic area
30 (Morris et al., 1999b), was identified that correlated to a
greater extent with ratings given to question (ii) compared
with ratings given to question (i). While this finding is
certainly preliminary, we speculate that this region of the
brain may form part of a neural substrate for the subjective
difference between finding the chocolate pleasant but not
wanting to eat any more (Fig. 3F). This interpretation is
consistent with Berridge’s proposal that there are separate
neural systems underlying wanting and liking (Berridge,
Strengths and weakness of the paradigm
The paradigm employed here to evaluate affective changes
associated with feeding is unique because the same stimulus
was used to evoke the entire affective spectrum (positive and
appetitive to negative and aversive). At the beginning of the
experiment, eating the chocolate was consistent with subjects’
motivation, but as the chocolate was eaten to beyond satiety,
behaviour came to be inconsistent with the subjects’
D. M. Small et al.
motivation. Thus, the same act (eating) is both rewarding
and punishing within this paradigm and corresponding neural
activity can be assessed. However, since our subjects were
instructed to eat beyond satiety (in order to make the act of
eating chocolate punishing), the paradigm did not mimic the
natural satiation associated with normal termination of a
meal in this study.
changes associated with feeding occur over time, order effects
almost certainly contributed to our results. However, time—
and thus order—effects are inherent to the process of affective
change associated with eating to satiety (and beyond). We
attempted to address order effects by including ‘control’
water and tongue-movement scans at the beginning and at
the end of the experiment and by employing covariation, a
statistical technique designed to dissociate linearly related
variables and then partial out the effect of the selected
variable. Nevertheless, we acknowledge that neither of these
techniques controls for order completely. Additionally, non-
specific effects, such as autonomic and visceromotor changes,
which are intrinsic to both eating and the modulation of the
reward value of food, were not assessed and thus cannot be
disentangled from the overall neural response.
Finally, we chose to collect affective ratings immediately
after each scan, as opposed to during each scan. This choice
was based on our decision to avoid confounding reward-
related processing in the OFC and decision-making-related
activity in the OFC. The disadvantage of this decision is that
ratings reflected the subjective state immediately after eating
the chocolate as opposed to the subjective state during the
scan. However, given that changes in ratings occurred steadily
and gradually, it is unlikely that these two states differed
We observed differential recruitment of brain regions
depending on whether subjects ate chocolate when they were
highly motivated to eat and rated the chocolate as pleasant,
or whether they were highly motivated not to eat and rated
the chocolate as unpleasant. The only brain region that was
active during both positive and negative compared with
neutral conditions was the posterior cingulate cortex. Thus,
the present study supports the hypothesis that different neural
substrates underlie two motivation systems, one dealing
with positive/appetitive stimuli and a second with negative/
aversive stimuli. This functional dissociation was particularly
apparent in the OFC, where the rCBF decreased in the medial
OFC and increased in the lateral OFC as the reward value
of chocolate changed from pleasant to aversive. This pattern
of activity indicates that there may be a functional segregation
of the neural representation of reward and punishment within
As predicted, modulation was seen in cortical chemo-
sensory areas including the insula and OFC, suggesting that
these chemosensory regions contribute to feeding behaviour
by encoding changes in the value of food reward in addition
to sensory processing. This result is important because it
demands a reconceptualization of these regions as heteromo-
dal ingestive cortices with overlapping representations of
sensory and affective processing of taste and smell, which
departs from classical notions of primary and secondary
sensory areas. Additionally, we observed activity in several
brain regions previously implicated in feeding by studies
with non-human animals including the striatum, midbrain
and OFC. These results provide a reference against which
future studies of eating disorders and obesity in humans may
We wish to thank the technical staff of the McConnell Brain
Imaging Unit and the Medical Cyclotron for their invaluable
assistance and the Neurophotography staff at the MNI.
Funding was provided by grant MT-14991 awarded to M.J.-
G. and R.J.Z. by the Medical Research Council of Canada.
Ahn S, Phillips AG. Dopaminergic correlates of sensory-specific
satiety in the medial prefrontal cortex and the nucleus accumbens
of the rat. J Neurosci 1999; 19: RC29.
Bartoshuk LM. Taste, smell, and pleasure. In: Bolles RC, editor.
The hedonics of taste. Hillsdale (NJ): Lawrence Erlbaum; 1991.
Baylis LL, Rolls ET, Baylis GC. Afferent connections of the
caudolateral orbitofrontal cortex taste area of the primate.
Neuroscience 1995; 64: 801–12.
Berridge KC. Food reward: brain substrates of wanting and liking.
[Review]. Neurosci Biobehav Res 1996; 20: 1–25.
Blair RJ, Morris JS, Frith CD, Perrett DI, Dolan RJ. Dissociable
neural responses to facial expressions of sadness and anger. Brain
1999; 122: 883–93.
Blood AJ, Zatorre RJ, Bermudez P, Evans AC. Emotional responses
to pleasantand unpleasant musiccorrelate with activityin paralimbic
brain regions. Nat Neurosci 1999; 2: 382–7.
Breiter HC, Gollub RL, Weisskoff RM, Kennedy DN, Madris N,
Berke JD, et al. Acute effects of cocaine on human brain activity
and emotion. Neuron 1997; 19: 591–611.
Carmichael ST, Price JL. Connectional networks within the orbital
and medial prefrontal cortex of macaque monkeys. J Comp Neurol
1996; 371: 179–207.
Chikama M, McFarland NR, Amaral DG, Haber SN. Insular cortical
projections to functional regions of the striatum correlate with
cortical cytoarchitectonic organization in the primate. J Neurosci
1997; 17: 9686–705.
Coghill RC, Sang CN, Maisog JM, Iadarola MJ. Pain intensity
processing within the human brain: a bilateral, distributed
mechanism. J Neurophysiol 1999; 82: 1934–43.
Brain activity related to eating chocolate
Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D
intersubject registration of MR volumetric data in standardized
Talairach space. J Comput Assist Tomogr 1994; 18: 192–205.
Critchley HD, Rolls ET. Hunger and satiety modify the responses
of olfactory and visual neurons in the primate orbitofrontal cortex.
J Neurophysiol 1996; 75: 1673–86.
Dade LA, Jones-Gotman M, Zatorre RJ, Evans AC. Human brain
function during odor encoding and recognition: a PET activation
study. Ann NY Acad Sci 1998; 855: 572–4.
Damasio AR. Descartes’ error. New York: Avon Books; 1994.
Damasio AR, Grabowski TH, Bechara A, Damsio H, Ponto LLB,
Parvizi J, et al. Subcortical and cortical brain activity during the
feeling of self-generated emotions. Nat Neurosci 2000; 3: 1049–56.
Denton D, Shade R, Zamarippa F, Egan G, Blair-West J,
McKinley M, et al. Neuroimaging of genesis and satiation of
thirst and an interoceptor-driven theory of origins of primary
consciousness. Proc Natl Acad Sci USA 1999; 96: 5304–9.
Elliott R, Dolan RJ, Frith CD. Dissociable functions in the medial
and lateral orbitofrontal cortex: evidence from human neuroimaging
studies. [Review]. Cereb Cortex 2000; 10: 308–17.
Faurion A, Cerf B, Van De Moortele PF, Lobel E, MacLeod P,
Le Bihan D. Human taste cortical areas studied with functional
magnetic resonance imaging: evidence of functional lateralization
related to handedness. Neurosci Lett 1999; 277: 189–92.
Francis S, Rolls ET, Bowtell R, McGlone F, O’Doherty J,
Browning A, et al. The representation of pleasant touch in the brain
and its relationship with taste and olfactory areas. Neuroreport
1999; 10: 453–9.
Fulbright RK, Skudlarski P, Lacadie CM, Warrenburg S, Bowers
AA, Gore JC, et al. Functional MR imaging of regional brain
1998; 19: 1721–6.
Gallagher M, McMahan RW, Schoenbaum G. Orbitofrontal cortex
and representation of incentive value in associative learning. J
Neurosci 1999; 19: 6610–4.
Bermudez-Rattoni F. Blockade of N-methyl-D-aspartate receptors
in the insular cortex disrupts taste aversion and spatial memory
formation. Neuroscience 1999; 89: 751–8.
H, Hernandez-EcheagarayE, Ramirez-AmayaV,
Haber SN, Kunishio K, Mizobuchi M, Lynd-Balta E. The orbital
and medial prefrontal circuit through the primate basal ganglia.
J Neurosci 1995; 15: 4851–67.
Hamdy S, Rothwell JC, Brooks DJ, Bailey D, Aziz Q, Thompson
DG. Identification of the cerebral loci processing human swallowing
with H2O15PET activation. J Neurophysiol 1999; 81: 1917–26.
Hetherington MM, MacDiarmid JI. ‘Chocolate addiction’: a
preliminary study of its description and its relationship to problem
eating. Appetite 1993; 21: 233–46.
Iversen SD, Mishkin M. Perseverative interference in monkeys
following selective lesions of the inferior prefrontal convexity. Exp
Brain Res 1970; 11: 376–86.
Jacobs KM, Mark GP, Scott TR. Taste responses in the nucleus
tractus solitarius of sodium-deprived rats. J Physiol (Lond) 1988;
Jones-Gotman M, Zatorre RJ. Odor recognition memory in humans:
role of right temporal and orbitofrontal regions. Brain Cogn 1993;
Kinomura S, Kawashima R, Yamada K, Ono S, Itoh M, Yoshioka S,
et al. Functional anatomy of taste perception in the human brain
studied with positron emission tomography. Brain Res 1994; 659:
Kosslyn SM, Shin LM, Thompson WL, McNally RJ, Rauch SL,
Pitman RK, et al. Neural effects of visualizing and perceiving
aversivestimuli: aPET investigation.Neuroreport1996; 7:1569–76.
Lane RD, Reiman EM, Bradley MM, Lang PJ, Ahern GL, Davidson
RJ, et al. Neuroanatomical correlates of pleasant and unpleasant
emotion. Neuropsychologia 1997a; 35: 1437–44.
Lane RD, Reiman EM, Ahern G L, Schwartz GE, Davidson RJ.
Neuroanatomical correlates of happiness, sadness, and disgust. Am
J Psychiatry 1997b; 154: 926–33.
Ledoux JE. The emotional brain. New York: Touchstone; 1996.
Maddock RJ. The retrosplenial cortex and emotion: new insights
from functional neuroimaging of the human brain. TINS 1999; 22:
Mirenowisz J, Schultz W. Preferential activation of midbrain
dopamine neurons by appetitive rather than aversive stimuli [letter].
Nature 1996; 379: 449–51.
Morris JS, Frith CD, Perrett DI, Rowland D, Young AW, Calder
AJ, et al. A differential neural response in the human amygdala to
fearful and happy facial expressions. Nature 1996; 383: 812–5.
Morris JS, Scott SK, Dolan RJ. Saying it with feeling: neural
responses to emotional vocalizations. Neuropsychologia 1999a; 37:
Morris R, Petrides M, Pandya DN. Architecture and connections of
retrosplenial area 30 in the rhesus monkey (Macaca mulatta). Eur
J Neurosci 1999b; 11: 2506–18.
O’Doherty J, Rolls ET, Francis S, Bowtell R, McGlone F, Kobal G,
et al. Sensory-specific satiety-related olfactory activation of the
human orbitofrontal cortex. Neuroreport 2000; 11: 399–403.
O’Doherty J, Kringelbach ML, Rolls ET, Hornak J, Andrews C.
Abstract reward and punishment representations in the human
orbitofrontal cortex. Nat Neurosci, 2001; 4: 95–102.
Paradiso S, Johnson DL, Andreasen NC, O’Leary DS, Watkins GL,
Ponto LL, et al. Cerebral blood flow changes associated with
attribution of emotional valence to pleasant, unpleasant, and neutral
visual stimuli in a PET study of normal subjects. Am J Psychiatry
1999; 156: 1618–29.
Pardo JV, Wood TD, Costello PA, Pardo PJ, Lee JT. PET study of
the localization and laterality of lingual somatosensory processing
in humans. Neurosci Lett 1997; 234: 23–6.
Paus T, Perry DW, Zatorre RJ, Worsley KJ, Evans AC. Modulation
of cerebral blood flow in the human auditory cortex during speech:
role of motor-to-sensory discharges. Eur J Neurosci 1996; 8:
D. M. Small et al.
Penfield W, Faulk ME. The insula: further observations on its
function. Brain 1955; 78: 445–70.
Petrides M, Pandya DN. Comparative architectonic analysis of the
human and the macaque frontal cortex. In: Boller F, Graham J,
editors. Handbookof neuropsychology,Vol. 9.Amsterdam: Elsevier;
1994. p. 17–58.
Phillips ML, Young AW, Senior C, Brammer M, Andrew C, Calder
AJ, et al. A specific neural substrate for perceiving facial expressions
of disgust. Nature 1997; 389: 495–98.
Price JL. Olfactory system. In: Paxinos G, editor. The human
nervous system. San Diego: Academic Press, 1990. p. 979–98.
Pritchard TC, Hamilton RB, Morse JR, Norgren R. Projections
of thalamic gustatory and lingual areas in the monkey, Macaca
fascicularis. J Comp Neurol 1986; 244: 213–28.
PritchardTC, MacalusoDA, EslingerPJ. Tasteperception inpatients
with insular cortex lesions. Behav Neurosci 1999; 113: 663–71.
Raichle ME, Martin WR, Herscovitch P, Mintun MA, Markham J.
Implementation and validation. J Nucl Med 1983; 24: 790–8.
Richardson NR, Gratton A. Changes in medial prefrontal cortical
dopamine levels associated with response-contingent food reward:
an electrochemical study in rat. J Neurosci 1998; 18: 9130–8.
Rogers RD, Owen AM, Middleton HC, Williams EJ, Pickard JD,
Sahakian BJ, et al. Choosing between small, likely rewards and
large, unlikely rewards activates inferior and orbital prefrontal
cortex. J Neurosci 1999; 19: 9029–38.
Rozin P, Levine E, Stoess C. Chocolate craving and liking. Appetite
1991; 17: 199–212.
Rolls ET. The neural control of feeding in primates. In: Booth DA,
editor. Neurophysiology of ingestion. Oxford: Pergamon Press;
1993. p. 137–69.
Rolls ET. The orbitofrontal cortex. [Review]. Phil Trans R Soc
Lond B Biol Sci 1996; 351: 1433–4.
Rolls ET. Taste and olfactory processing in the brain and its relation
to the control of eating. [Review]. Crit Rev in Neurobiol 1997; 11:
Rolls ET, Baylis LL. Gustatory, olfactory, and visual convergence
within the primate orbitofrontal cortex. J Neurosci 1994; 14:
Rolls ET, Scott TR, Sienkiewicz ZJ, Yaxley S. The responsiveness
of neurones in the frontal opercular gustatory cortex of the macaque
monkey is independent of hunger. J Physiol (Lond) 1988; 397: 1–12.
Rolls ET, Sienkiewicz ZJ, Yaxley S. Hunger modulates the responses
cortex of the macaque monkey. Eur J Neurosci 1989; 1: 53–60.
Rolls ET, Yaxley S, Sienkiewicz ZJ. Gustatory responses of single
neurons in the caudolateral orbitofrontal cortex of the macaque
monkey. J Neurophysiol 1990; 64: 1055–66.
Rolls ET, Critchley HD, Treves A. Representation of olfactory
information in the primate orbitofrontal cortex. J Neurophysiol
1996; 75: 1982–96.
Rolls ET, Critchley HD, Browning AS, Hernadi I, Lenard L.
Responses to the sensory properties of fat of neurons in the primate
orbitofrontal cortex. J Neurosci 1999; 19: 1532–40.
Royet JP, Zald D, Versace R, Costes N, Lavenne F, Koenig O.
Emotional responses to pleasant and unpleasant olfactory, visual,
and auditory stimuli: a positron emission tomography study.
J Neurosci 2000; 20: 7752–9.
Savic I, Gulyas B, Larsson M, Roland P. Olfactory functions are
mediated by parallel and hierarchical processing. Neuron 2000; 26:
Scott TR, Plata-Salaman CR. Taste in the monkey cortex. [Review].
Physiol Behav 1999; 67: 489–511.
Small DM, Jones-Gotman M, Zatorre RJ, Petrides M, Evans AC.
J Neurosci 1997a; 17: 5136–42.
Small DM, Jones-Gotman M, Zatorre RJ, Petrides M, Evans AC.
Flavor processing: more than the sum of its parts. Neuroreport
1997b; 8: 3913–17.
Small DM, Zald DH, Jones-Gotman M, Zatorre RJ, Pardo JV,
Frey S. Human cortical gustatory areas: a review of functional
neuroimaging data. Neuroreport 1999; 10: 7–14.
Sobel N, Prabhakaran V, Desmond JE, Glover GH, Goode RL,
Sullivan EV, et al. Sniffing and smelling: separate subsystems in
the human olfactory cortex. Nature 1998; 392: 282–3.
Sobel N, Prabhakaran V, Zhao Z, Desmond JE, Glover GH, Sullivan
EV, et al. Time course of odorant-induced activation in the human
primary olfactory cortex. J Neurophysiol 2000; 83: 537–51.
Takagi SF. Studies on the olfactory nervous system of the Old
World monkey. Prog Neurobiol 1986; 27: 195–250.
Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human
brain. Stuttgart: Thieme; 1988.
Tanabe T, Iino M, Takagi SF. Discrimination of odors in olfactory
bulb, pyriform-amygdaloid areas, and orbitofrontal cortex of the
monkey. J Neurophysiol 1975a; 38: 1284–96.
Tanabe T, Yarita H, Iino M, Ooshima Y, Takagi SF. An olfactory
projection area in orbitofrontal cortex of the monkey. J Neurophysiol
1975b; 38: 1269–83.
Tataranni PA, Gautier JF, Chen K, Uecker A, Bandy D, Salbe AD,
et al. Neuroanatomical correlates of hunger and satiation in humans
using positron emission tomography. Proc Natl Acad Sci USA 1999;
Thut G, Schultz W, Roelcke U, Nienhusmeier M, Missimer J,
Maguire RP, et al. Activation of the human brain by monetary
reward. Neuroreport 1997; 8: 1225–8.
Tolle TR, Kaufmann T, Siessmeier T, Lautenbacher S, Berthele A,
Munz F, et al. Region-specific encoding of sensory and affective
components of pain in the human brain: a positron emission
tomography correlation analysis. Ann Neurol 1999; 45: 40–7.
Wang GJ, Volkow ND, Fowler JS, Cervany B, Hitzemann RJ,
Pappas NR, et al. Regional brain metabolic activation during
cravings elicited by recall of previous drug experiences. Life Sci
1999; 64: 775–84.
Brain activity related to eating chocolate Download full-text
Wise RA. Drug self-administration viewed as ingestive behaviour.
[Review]. Appetite 1997; 28: 1–5.
Worsley KJ, Evans AC, Marrett S, Neelin P. A three-dimensional
statistical analysis for CBF activation studies in human brain. J
Cereb Blood Flow Metab 1992; 12: 900–18.
Worsley KJ, Marrett S, Neelin P, Vandal AC, Friston KJ, Evans
AC. A unified statistical approach for determining significant signals
in images of cerebral activation. Hum Brain Mapp 1996; 4: 58–73.
Yamamoto T, Shimura T, Sako N, Yasoshima Y, Sakai N. Neural
substrates for conditioned taste aversion in the rat. [Review]. Behav
Brain Res 1994; 65: 123–37.
Yan J, Scott TR. The effect of satiety on responses of gustatory
neurons in the amygdala of alert cynomolgus macaques. Brain Res
1996; 740: 193–200.
Yaxley S, Rolls ET, Sienkiewicz ZJ. Gustatory responses of single
neurons in the insula of the macaque monkey. J Neurophysiol 1990;
Zald DH, Pardo JV. Emotion, olfaction, and the human amygdala:
amygdala activation during aversive olfactory stimulation. Proc Natl
Acad Sci USA 1997; 94: 4119–24.
Zald DH, Pardo JV. Functional neuroimaging of the olfactory system
in humans. [Review]. Int J Psychophysiol 2000; 36: 165–81.
Zald DH, Lee JT, Fluegel KW, Pardo JV. Aversive gustatory
stimulation activates limbic circuits in humans. Brain 1998; 121:
Zatorre RJ, Jones-Gotman M. Functional imaging of the chemical
senses. In: Toga AW, Mazziota JC, editors. Brain mapping: the
systems. San Diego: Academic Press; 2000. p. 403–24.
Zatorre RJ, Jones-Gotman M, Evans AC, Meyers E. Functional
localization and lateralization of human olfactory cortex. Nature
1992; 60: 339–40.
Received June 12, 2000. Revised February 8, 2001.
Second revision April 30, 2001. Accepted April 30, 2001