Psychiatry Research: Neuroimaging 147 (2006) 57 – 67
www.elsevier.com/locate/psychresns
Neural correlates of habituation to taste stimuli in healthy women
Angela Wagner a,b , Howard Aizenstein a , Guido K. Frank a,c , Jennifer Figurski a ,
J. Christopher May d,e , Karen Putnam f , Lorie Fischer a , Ursula F. Bailer a,g ,
Shannan E. Henry a , Claire McConaha a , Victoria Vogel a , Walter H. Kaye a,⁎
a
University of Pittsburgh, School of Medicine, Department of Psychiatry, Western Psychiatric Institute and Clinic, Pittsburgh,
Pennsylvania, United States
b
University of Mannheim, Central Institute of Mental Health, Department of Child and Adolescent Psychiatry, Mannheim, Germany
c
University of California, San Diego, Department of Psychiatry, La Jolla, California, United States
d
Department of Psychology, University of Pittsburgh, PA, United States
e
Center for the Neural Basis of Cognition, University of Pittsburgh, PA, United States
f
University of Cincinnati, School of Medicine, Department of Environmental Health, Division of Epidemiology and Biostatistics,
Cincinnati, Ohio, United States
g
Medical University of Vienna, Department of General Psychiatry, University Hospital of Psychiatry, Vienna, Austria
Received 14 January 2005; received in revised form 30 August 2005; accepted 8 November 2005
Abstract
Recent studies show that specific regions of the cortex contribute to modulation of appetitive behaviors. The purpose of this
study was to determine whether neural response in these regions changes over time when a taste stimulus is administered
repeatedly. Such a paradigm may be useful for determining whether altered habituation contributes to disturbed eating behavior.
This study used a programmable syringe pump to compare administration of a 10% sucrose solution to distilled water in 11 healthy
female subjects using functional magnetic resonance imaging. The stimuli were presented in either a sequential or pseudorandom
order. An a priori ‘Region of Interest’ (ROI) based analysis method was used, with ROIs defined in the prefrontal cortex, insula,
amygdala, and hippocampus. To test habituation, activation during the first half of each block was compared with activation during
the second half. For the pseudorandom blocks, subjects showed habituation in almost all ROIs to water, but in none to sucrose. By
contrast, for sequential blocks, both stimuli produced habituation in taste-related brain regions. These data suggest that habituation
patterns in healthy subjects may depend on frequency and regularity of stimulus administration.
© 2006 Elsevier Ireland Ltd. All rights reserved.
Keywords: Taste; Habituation; fMRI; Amygdala; Insula; Eating disorder
1. Introduction
⁎ Corresponding author. University of Pittsburgh, Western Psychiatric Institute and Clinic, Iroquois Building, Suite 600, 3811 O'Hara
Street, Pittsburgh, PA 15213, United States. Tel.: +1 412 647 9845;
fax: +1 412 647 9740.
E-mail address: kayewh@upmc.edu (W.H. Kaye).
Individuals with anorexia nervosa (AN) and bulimia
nervosa (BN) show behavioral disturbances which are
categorized as “eating disorders”. However, it is not
known whether there is a primary disturbance of
appetite regulation, taste perception or habituation, or
disturbed feeding behavior secondary to anxiety. The
0925-4927/$ - see front matter © 2006 Elsevier Ireland Ltd. All rights reserved.
doi:10.1016/j.pscychresns.2005.11.005
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A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
current study was designed to identify habituation
aspects of taste in healthy women, as part of a long
term goal of identifying primary disturbances of eating
disorders.
Recent studies have shown that specific regions of
the cortex contribute to the modulation of appetitive
behaviors. Studies in non-human primates suggest that
the anterior insula and adjacent frontal operculum are
the primary taste cortex while the caudolateral
orbitofrontal cortex (OFC) is part of secondary taste
cortical areas (Scott et al., 1986; Ogawa et al., 1989;
Rolls et al., 1990; Yaxley et al., 1990). Studies in
healthy humans using either positron emission tomography (PET) (Kinomura et al., 1994; Small et al.,
1997; Zald et al., 1998; Frey and Petrides, 1999) or
functional magnetic resonance imaging (fMRI) (Faurion et al., 1999; Francis et al., 1999; O'Doherty et al.,
2001; De Araujo et al., 2003a; Kringelbach et al.,
2003) support these findings. In addition, other brain
regions involved in gustatory processing have been
described. The amygdala might play a role in the
discrimination of a novel and aversive stimulus (Small
et al., 1997; Zald et al., 1998, 2002; O'Doherty et al.,
2002; Small et al., 2003). Other studies have found an
activation in the cingulate cortex (Kinomura et al.,
1994; Zald et al., 1998; De Araujo et al., 2003a; De
Araujo and Rolls, 2004). Neural activity was also
described in the dorsolateral prefrontal cortex (PFC)
(Gautier et al., 1999; Tataranni et al., 1999; Kringelbach et al., 2004).
The imaging studies described above used a variety
of food administration techniques to assess taste
perception and reward. For example, sweet, salty or
bitter unimodal taste stimuli or multimodal taste stimuli
such as tomato juice or chocolate milk were contrasted
with a neutral stimulus (25 mM KCl and 2.5 mM
NaHCO3) (De Araujo et al., 2003b; Kringelbach et al.,
2003; De Araujo and Rolls, 2004) or water (Faurion et
al., 1999). In comparison, imaging studies in AN and
BN have only used pictures of food (Ellison et al., 1998;
Gordon et al., 2001; Uher et al., 2004). Whether pictures
of food are a relevant challenge for understanding the
pathophysiology of eating disorders is unknown. Thus,
our laboratory developed a standardized paradigm
(Frank et al., 2003) to assess brain activation using
fMRI and blind administration of pure macronutrient
solutions. In the present study two taste stimuli, sucrose
and water, were chosen to investigate induced neuronal
activation in healthy women with an a priori region-ofinterest (ROI) approach, with ROIs defined in the
prefrontal cortex, medial OFC, insula, amygdala, and
hippocampus.
Pathologic eating behaviors vary from severe food
restriction in AN to overeating in BN. Theoretically,
such alterations could be related to altered modulation of
satiety or habituation. In other words, we speculate that
feeding may elicit exaggerated satiety in AN and
reduced satiety in BN. The decrease in the hedonic
response to a food that is repeatedly consumed, known
as sensory-specific satiety (Rolls et al., 1981), has been
shown to have neural correlates. Kringelbach et al.
(2003) reported a cluster of voxels in the OFC that
showed a decrease in activation specific to the particular
food consumed. It is also important to note that
individuals with AN and BN tend to have stereotypic
and monolithic eating patterns in which the same foods
are consumed every day, particularly when restricting or
binge eating. It is possible that sensory-specific satiety
reflects habituation to specific taste stimuli. Thus the
purpose of the study was to devise a paradigm that
assessed habituation to the same taste stimulus. To test
this, healthy subjects were administered the same
stimulus 20 times in a row to determine whether they
habituated to the same stimulus. This is compared to a
more common design in which the stimuli alternate in a
pseudorandom order.
2. Methods
2.1. Sample
Eleven healthy female volunteers were recruited
through local advertisements. They were 28.6 ±
6.75 years old and had a current Body Mass Index of
22.06 ± 2.67 kg/m 2 . They had no history of any
psychiatric, medical or neurological illness. Participants
had no first-degree relative with an eating disorder. They
had normal menstrual cycles, had been within normal
weight range since menarche, and were not on medication, including herbal supplements.
This study was conducted according to the institutional
review board regulations of the University of Pittsburgh,
and all subjects gave written informed consent. The MR
imaging was performed during the first 10 days of the
follicular phase for all subjects. The follicular phase was
determined by history. The MR study was done at 9:00
am. All subjects had the same standardized breakfast on
the morning of the study. This design was chosen to
standardize the subjects' state of satiety.
2.2. Experimental paradigm
The paradigm was based on a task developed in our
group and described previously (Frank et al., 2003). In
A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
59
the present task two different stimuli were used: 10%
sucrose (Fisher) and distilled water. These solutions
are described in the literature as pleasant and neutral,
respectively (Drewnowski et al., 1987). The paradigm
consisted of six blocks of 20 trials each. Within
blocks, stimuli were presented either sequentially or
pseudorandomly. In four sequential blocks (2 of each
solution), either sucrose or water was given repeatedly
for the 20 trials. Therefore the total scan number for
either sucrose or water was 40. In the two pseudorandom blocks, sucrose and water were presented
randomly, but in the same “random” order for all
subjects (hence pseudorandom). Within these pseudorandom blocks, the number of sampling scans of
sucrose and water was the same, resulting in a total of
20 for both. The six blocks were presented randomly
to all subjects such that sequential blocks of the same
solution were never presented consecutively. Each
taste stimulus consisted of 1-ml volume of liquid and
was delivered every 20 s through one of two tubes in
the buccal region. Subjects were trained to perform
one tongue motion (swishing the solutions across the
tongue) after each application of taste stimulant, in
order to wash the taste stimulus around the mouth and
stimulate taste buds.
line from the anterior to posterior commissures (the
AC–PC line), with an in-plane resolution of 0.78 mm2
and with a field of view of 200 mm2. Functional images
were acquired using a one-shot reverse spiral pulse
sequence (Noll et al., 1995; Bornert et al., 2000) with
TE = 26 ms and TR = 2000 ms; 30 oblique axial slices
were acquired with an in-plane resolution of 64 × 64
with 3.125 mm2 pixels and a slice thickness of 3.2 mm,
with a field of view of 200 mm2. Functional images
were acquired in six blocks of 20 trials each over the
course of learning. The presentation of stimuli was
synchronized with the scanning such that ten 2-second
images were acquired per trial.
2.3. Apparatus
2.5.2. Automated labeling pathway
We used an a priori ROI approach, with the regions
defined anatomically in each individual's anatomic
space. An automated approach for defining the ROIs
was used, as described in Rosano (Rosano et al., 2005)
and Aizenstein (Aizenstein et al., 2004). The anatomical ROIs were chosen based on a literature review of
previous studies. Bilateral amygdala, BA10, BA11,
BA46, hippocampus, and insula were defined in the
Automatic Anatomical Labeling (aal) map obtained
from the MRIcro software package (Tzourio-Mazoyer
et al., 2002). The caudal anterior cingulate cortex
(ACC) was chosen from a previous functional imaging
study (Carter et al., 2000). To define each ROI for each
single subject in her own space, the following steps
were performed. First, each subject's low-resolution
anatomical image was cross-registered to her highresolution anatomical image, using a six-parameter
linear algorithm (Woods et al., 1998a). Then the
Montreal Neurological Institute (MNI) single-subject
high-resolution anatomical image (the Colin brain) was
aligned with each subject's high-resolution anatomical
image using a second order warping algorithm with 30
parameters (Woods et al., 1998b). Each ROI from the
aal map was then put onto each subject's SPGR. Then
a gray matter mask was applied to each label, using the
The macronutrient solutions were contained in two
25-ml syringes, which were attached to a semiautomatic
and programmable customized syringe pump (J-Kem
Scientific, St. Louis, MO), positioned in the scanner
control room. Tastes were delivered to the subjects via
two separate approximately 10-m long FDA approved
food grade teflon tubes (Cole-Parmer Vernon Hills, IL).
The syringes were also attached to a computercontrolled valve system, which enabled the two
solutions to be delivered independently along the
tubing. Taste delivery was controlled by E-Prime
(Psychology Software Tools, Inc., Pittsburgh, PA)
software operating on a personal computer positioned
in the control room. The stimuli were also synchronized
with MR scanning.
2.4. Scanning procedures
Imaging data were collected with a 3T Signa scanner
(GE Medical Systems). High-resolution anatomical
images (1.5 mm3) were acquired for each subject.
Additionally, T1 structural images were acquired with a
3.2-mm thickness (in-plane with the functional images).
These had 36 oblique axial slices oriented parallel to a
2.5. Image analysis
2.5.1. Data preprocessing
Motion correction was performed using a sixparameter linear algorithm (Woods et al., 1998a). A
linear detrending algorithm was also done, using only
data within 3 standard deviations of the mean to estimate
the linear trend. Global normalization was performed
multiplicatively to give each subject a mean intensity of
3000. All analyses were conducted on a single subject
basis on non-cross-registered data.
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A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
FAST algorithm from the FSL package (Zhang et al.,
2001). The labeling of each subject's ROIs was then
visually inspected to assure accurate mappings.
3. Results
2.5.3. Time series analysis
For each subject and for each ROI, a mean time series
was extracted. The time series for each voxel in each
region was first calculated as the percent signal change
across the 10 different scans of a trial, that is, the percent
change of signal intensity in that voxel from the first
scan of the trial. The mean signal for each trial type and
for each region was then calculated. The mean time
series across all blocks was used to test the effect of
condition type, and the difference in peak signal across
the blocks (i.e., first half of trials of one condition versus
second half of trials for the same condition) was used to
test for habituation.
A significance level was computed for each test
result presented in Table 1 using t-tests of percentage
signal change at expected HRF peak versus 0 (df = 10) as
well as in Table 2 using paired t-tests (df = 10).These
levels were then adjusted to an overall family-wise error
rate of 0.05 for each condition using the Hochberg
procedure, a “step-up” modified Bonferroni method for
multiple comparisons (Hochberg, 1988). Using this
approach, significance levels are ordered from largest to
smallest and compared to the Hochberg adjusted alpha.
The Hochberg adjusted alpha is calculated by multiplying the P value by the rank number it has in the list of
comparisons.
For the distilled water stimuli, there was significant
neuronal activation for all of the ROIs, except for the
medial OFC and dorsolateral prefrontal cortex after
correcting for multiple statistical testing (Table 1a). In
contrast, the neuronal activation following sucrose
stimuli did not stay significant in all ROIs after
correction for multiple comparison (Table 1b).
A contrast analysis of sucrose versus distilled water
revealed significant differences, at a level of P < 0.05,
for bilateral amygdala, hippocampus, insula, caudal
ACC, dorsolateral prefrontal cortex and medial OFC
(Brodmann area, BA 11). However, only the contrast for
the bilateral amygdala, hippocampus, medial OFC and
right insula remained significant after correction for
multiple statistical testing (Table 2a).
To test for effects of habituation, the activation that
occurred during the first half of the blocks was
compared to activation that occurred during the second
half of the blocks. For the water trials, there were
significant reductions in activation during the second
half of the trials for all ROIs (Table 2b) except medial
OFC. However, there were no differences in activation
for sucrose, when activation during the first half of the
sucrose trials was compared with the activation during
the second half of the trials (Table 2c). An interaction
analysis comparing response to sucrose and water
3.1. Pseudorandom blocks
Table 1
Activation in several brain regions for each stimulus in each block
Brain regions
Amygdala left
Amygdala right
Hippocampus left
Hippocampus right
Caudal anterior cingulate cortex
Insula left
Insula right
Dorsolateral prefrontal cortex left (BA 46)
Dorsolateral prefrontal cortex right (BA 46)
Medial orbitalfrontal cortex left (BA 11)
Medial orbitalfrontal cortex right (BA 11)
Medial orbitalfrontal cortex left (BA 10)
Medial orbitalfrontal cortex right (BA 10)
a
b
c
d
Pseudo blocks
Pseudo blocks
Sequential blocks
Sequential blocks
Water
Sucrose
Water
Sucrose
0.0001, 6.09
0.0002, 5.70
0.0009, 4.60
0.0001, 5.77
0.0019, 4.15
0.0004, 5.19
0.0004, 5.10
0.0183, 2.81
0.0175, 2.84
0.0024, 4.02
0.0123, 3.048
0.0502, 2.23
0.0683, 2.04
0.0249, 2.63
0.0117, 3.08
0.0472, 2.26
0.0236, 2.67
0.0191, 2.79
0.0069, 3.39
0.0700, 2.03
0.3097, 1.07
0.1787, 1.45
0.1188, 1.71
0.2051, 1.36
0.5001, 0.70
0.4097, 0.86
0.0002, 5.61
0.0006, 4.83
0.0014, 4.37
0.0011, 4.51
0.0012, 4.44
0.0004, 5.16
0.0011, 4.48
0.0460, 2.28
0.0156, 2.91
0.0967, 1.83
0.1477, 1.57
0.0949, 1.84
0.1050, 1.78
0.0002, 5.60
0.0012, 4.46
0.0049, 3.58
0.0021, 4.09
0.0072, 3.36
0.0006, 4.91
0.0055, 3.52
0.2655, 1.18
0.1049, 1.78
0.0716, 2.01
0.1266, 1.67
0.8207, 0.23
0.5658, 0.59
Significance values (P and t, df = 10) using a t-test of %signal change at HRF peak versus 0 for sucrose (S) and water (W) for both block types. Levels
were adjusted for multiple statistical tests within each condition using the Hochberg method, with the overall level of significance set at α = 0.05 and
10 degrees of freedom. Bold values presented are significant after the Hochberg multiple comparison adjustment.
A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
61
Table 2
Activation in several brain regions for different conditions
Brain regions
Amygdala left
Amygdala right
Hippocampus left
Hippocampus right
Caudal anterior cingulate cortex
Insula left
Insula right
Dorsolateral prefrontal cortex left
(BA 46)
Dorsolateral prefrontal cortex right
(BA 46)
Medial orbitalfrontal cortex left
(BA 11)
Medial orbitalfrontal cortex right
(BA 11)
Medial orbitalfrontal cortex left
(BA 10)
Medial orbitalfrontal cortex right
(BA 10)
a
b
c
d
e
f
Pseudo blocks
Pseudo blocks
Pseudo blocks Sequential blocks Sequential blocks Sequential blocks
S vs. W
Habituation W⁎ Habituation S⁎ S vs. W
Habituation W⁎
Habituation S⁎
<0.0001, −6.43
<0.0001, −7.93
<0.0001, −6.28
<0.0001, −8.17
0.0308, − 2.51
0.0316, − 2.50
0.0002, −5.87
0.0087, − 3.25
0.0003, −5.41
<0.0001, −6.42
0.0007, −4.84
<0.0001, −5.92
0.0047, −3.62
0.0010, −4.61
0.0004, −5.20
0.0061, −3.44
0.1939, − 1.39
0.2969, − 1.10
0.0321, − 2.49
0.2082, − 1.35
0.3858, − 0.91
0.1935, − 1.40
0.7508, − 0.33
0.9059, − 0.12
0.2947, − 1.11
0.1886, − 1.41
0.0925, − 1.86
0.1211, − 1.69
0.0267, − 2.60
0.1193, − 1.70
0.0477, − 2.26
0.2044, − 1.36
0.0007, −4.82
0.0011, −4.52
0.0003, −5.50
<0.0001, −7.22
0.0085, −3.27
0.0027, −3.95
0.0016, −4.26
0.0322, −2.49
0.0001, −6.22
<0.0001, −7.48
<0.0001, −6.88
<0.0001, −9.24
0.0005, −5.06
0.0002, −5.82
0.0007, −4.89
0.0078, −3.33
0.0374, − 2.39
0.0060, −3.48
0.7067, 0.39
0.1839, − 1.43
0.0237, −2.66
<0.0001, −6.41
0.0010, −4.56
0.0247, −2.65
0.2796, 1.14
0.9174, − 0.11
0.0167, −2.87
0.0140, −2.98
0.0015, −4.34
0.0212,− 2.74
0.5504, 0.62
0.8981,− 0.13
0.0167, −2.87
0.0158, −2.91
0.0978, −1.83
0.0914, −1.87
0.3631, 0.95
0.2550, − 1.21
0.1029, −1.80
0.1073, − 1.76
0.1458, − 1.58
0.0327, −2.47
0.4074, 0.86
0.3083, − 1.08
0.0675, −2.05
0.0239, − 2.66
Significance values (P and t, df = 10, paired t test) for comparisons of sucrose (S) versus water (W) for pseudorandom or sequential block contrasts (a
and d). Columns b, c, e and f show activation of the first half of each block compared with the activation of the second half of each block. Levels were
adjusted for multiple statistical tests within each condition using the Hochberg method, with the overall level of significance set at α = 0.05 and
10 degrees of freedom. Bold values presented are significant after the Hochberg multiple comparison adjustment.
confirmed that there were differences in response to
water and sucrose over time for all ROIs (P < 0.05)
except the medial OFC (BA 10). Figs. 1 and 2 show
representational findings for the left amygdala and left
insula. In summary, for pseudorandom blocks, sucrose
and water showed different neuronal responses over
time for almost all ROIs, with subjects showing
habituation to water but not sucrose.
3.2. Sequential blocks
For the distilled water stimuli, there was significant
neuronal activation for all of the ROIs, except for the
medial OFC and dorsolateral prefrontal cortex after
correcting for multiple statistical testing (Table 1c). For
the sucrose stimuli, there was significant neuronal
activation for the amygdala, hippocampus, and both
sides of the insula after correcting for multiple statistical
testing (Table 1d). A contrast analysis between sucrose
and distilled water stimuli showed no significant
differences for all ROIs (Table 2d).
To test for effects of habituation, the activation that
occurred during the first half of the blocks was compared
with activation that occurred during the second half of
the blocks. There were reductions, significant at a 0.05
level, in activation in the second half of the blocks for
water in all ROIs except the medial OFC (BA 10). After
adjustment for multiple comparisons, only neural response in amygdala, hippocampus and insula remained
significant (Table 2e). Similarly, when activation during
the first half of the study block was compared to
activation during the second half of the study block for
sucrose, significant reductions in neuronal activation
were found in all ROIs except the medial OFC (BA 10)
(Table 2f). These data showed that sucrose and water had
similar responses over time for a block design (Figs. 1–4).
4. Discussion
The purpose of this study was to test methods that
might characterize changes in neuronal activation to
food stimuli over time, and thus reflect habituation. In
this way we intended to test methods that might
replicate, in a laboratory setting, the patterns of eating
behaviors commonly seen in AN and BN.
4.1. Pseudorandom design versus sequential design
This study found that healthy control women respond
differently when sucrose and water are administered
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A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
Fig. 1. Time course of BOLD signal (mean of all 11 subjects) for taste-related response in the left amygdala during sequential blocks and
pseudorandom blocks comparing the activation during the first 10 trials versus the second 10 trials.
in different patterns. Reported studies tend to use
designs with a stimulus delivery in an unpredictable
pseudorandom order (Berns et al., 2001; De Araujo
and Rolls, 2004; Kringelbach et al., 2004) to compare
sweet and neutral stimuli. Those studies, and the
pseudorandom design described in this article, tend to
show activation of the insula, medial OFC (BA 11),
amygdala, hippocampus, caudal ACC and dorsolateral
PFC. Consistent with the literature, the region of
the medial OFC described as BA 11 was activated
(O'Doherty et al., 2000; Berns et al., 2001; Kringelbach et al., 2003; De Araujo and Rolls, 2004). By
contrast BA 10 was as expected not significantly
activated indicating the specific neural response of the
taste paradigm.
However, we questioned whether a design with
unpredictable food stimulus delivery was the best
method for studying subjects with eating disorders,
because individuals with AN and BN do not have
normal feeding patterns (Kaye et al., 1993). Instead,
they tend to restrict or binge by consuming a narrow
range of foods. Because food choice is not varied
during aberrant extremes of feeding in AN and BN, we
wanted to test the use of a predictable, sequential
design.
Anticipation of a taste experience may result in
different activation patterns for unpredictable pseudorandom blocks in contrast to more predictable sequential
blocks. There was no significant difference in neural
activation for all ROIs when sucrose was compared with
water in the sequential blocks. Our findings are
consistent with Berns who described that the medial
OFC displayed a significant activity for fruit juice
versus water when the stimuli were unpredictable
(Berns et al., 2001). Predictability (both stimuli were
alternated) was only correlated with activity in the right
superior temporal gyrus. In contrast, O'Doherty found
that expectation of a pleasant taste produced activation
in the posterior dorsal amygdala, striatum and OFC,
while apart from the OFC, these regions were not
activated by reward receipt (O'Doherty et al., 2002).
Our paradigm, in which the stimulus becomes predictable because it is sequentially administered, may not be
comparable to one using a visual cue, which indicates,
before the taste stimulus is delivered, whether a sweet
taste or water is to be administered.
A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
63
Fig. 2. Time course of BOLD signal (mean of all 11 subjects) for taste-related response in the left insula during sequential blocks and pseudorandom
blocks comparing the activation during the first 10 trials versus the second 10 trials.
4.2. Habituation effects
Rolls (Rolls, 2001) suggested that the brain regions
investigated in our study contribute to the modulation
of the reward value of a sensory stimulus such as the
taste of food. Normally, food tastes pleasant when
someone is hungry. However, after a food is eaten to
satiety, there is a reduction in the pleasantness of its
taste. In fact, neurons in the OFC decrease their
response to a food eaten to satiety, but remain
responsive to other foods, contributing to a mechanism
for sensory-specific satiety. In addition, O'Doherty et
al. found sensory-specific satiety effects for some
subjects also in the insula, amygdala and anterior
cingulate cortex (O'Doherty et al., 2000). A similar
effect in the OFC, middle part of the insula and rostral
ACC is described for water and a subject's thirst level
(De Araujo et al., 2003b). It is possible that sensoryspecific satiety and habituation are related phenomena.
However, the paradigms used to address them are
different. The Rolls group first gave a complex food
stimulus to satiety and then tested fMRI response to
further administration of this stimulus. In comparison,
we tested the administration of a pure macronutrient or
water given repeatedly. These differences in method
may explain different findings, especially for the
pseudorandom blocks. Interestingly, we did not find
habituation effects for sucrose when the stimuli were
given in an unpredictable alternated order. In contrast,
this paradigm did reveal a habituation effect to distilled
water. It is not clear why subjects did not habituate to
sucrose. Perhaps the block length of around 6 min is
too short for habituation effects of strong stimuli like
sucrose. It should be noted that the overall percentage
signal change for the pseudorandom blocks (trials 1–
10) for sucrose was significantly lower (t(10) = 4.50;
P = 0.001) than for the sequential blocks (trials 1–10) in
the amygdala (Fig. 1). It is possible that in the
sequential blocks there is a more robust early amygdala
activation due to the anticipation of sucrose.
Another way to look at a different kind of
habituation effect could be to compare the entire first
block versus the entire last block. O'Doherty et al.
revealed this type of habituation effect over the time
course of their experiment only in the orbital frontal
region when glucose was compared with a neutral
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A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
Fig. 3. Time course of BOLD signal (mean of all 11 subjects) for taste-related response in the right amygdala during sequential blocks and
pseudorandom blocks comparing the activation during the first 10 trials versus the second 10 trials.
(25 mMKCl and 2.5 mM NaHCO3) stimulus, but not
when a salty stimulus was compared with a neutral
stimulus (O'Doherty et al., 2002). We did not detect this
kind of habituation in our data set comparing the first
versus the last of the same block type for all ROIs (data
not shown). It appears, therefore, that there is more
habituation within blocks of repeating stimuli than across
blocks when blocks of repeating stimuli intervene.
4.3. Limitations
In terms of limitations, the delivery interval of 20 s
was not long enough to return the activation back to
baseline and therefore could drive the analysis. But we
expect a continuing central activation over several
minutes following a taste stimulus (Liu et al., 2000),
which does not fit into any event-related study design.
It has to be mentioned that twice as many sucrose/water
stimuli appear in sequential blocks than in pseudorandom blocks. It could be argued that stimulus numbers
influence overall magnitudes of habituation between
sequential and pseudorandom blocks. It is known that
neurons in taste-modulating brain regions do not
respond exclusively to taste but also to mechanical
stimulation related to a fluid or plastic tube (Katz et al.,
2002). The purpose of this study is to report a method
to assess possible habituation effects in eating disorders. Whether mechanical stimulation effects might
be washed out in a contrast analysis of eatingdisordered subjects versus control subjects remains to
be determined. Additionally, we studied female subjects only. However, since gender may have an impact
on the result of the neuronal activation (Cailhol and
Mormede, 2002), we made this choice as this study
was designed as a comparison for women with eating
disorders.
4.4. Summary
This study confirms and extends our understanding
of neuronal activation patterns in taste processing. In
summary, we replicated the activation of the primary
and secondary taste cortex as well as other taste-specific
brain regions such as caudal ACC and dorsolateral PFC.
To our knowledge, this is the first study assessing a
neuronal correlation of habituation effects in taste using
A. Wagner et al. / Psychiatry Research: Neuroimaging 147 (2006) 57–67
65
Fig. 4. Time course of BOLD signal (mean of all 11 subjects) for taste-related response in the right insula during sequential blocks and pseudorandom
blocks comparing the activation during the first 10 trials versus the second 10 trials.
fMRI. This study suggests that habituation patterns in
healthy subjects may be related to methods of stimulus
administration, predictability of stimuli or duration of
blocks. Habituation effects can play a role in reinforcement of eating. Thus, the predictable, sequential
experimental design may be useful for assessing taste
processing in eating-disordered patients and may shed
light on their eating behavior.
As noted above, future studies will seek to determine
whether individuals with AN and BN have an abnormal
physiologic response to foods, such as carbohydrates.
Furthermore, we might test the hypothesis that individuals with AN and BN have disturbances of these higher
order taste centers that regulate the satiating aspects of
feeding or related emotional behavior.
Acknowledgments
The authors thank Eva Gerardi for manuscript
preparation and C. Carter for comments on an earlier
draft. The authors are indebted to the participating
subjects for their contribution of time and effort in
support of this study.
Financial support was provided by the following
grants: NIMH MH046001, MH04298 and K05-MH01894.
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