Attenuated neural response to gamble outcomes in drug-naive patients with Parkinson's disease
Parkinson's disease results from the degeneration of dopaminergic neurons in the substantia nigra, manifesting as a spectrum of motor, cognitive and affective deficits. Parkinson's disease also affects reward processing, but disease-related deficits in reinforcement learning are thought to emerge at a slower pace than motor symptoms as the degeneration progresses from dorsal to ventral striatum. Dysfunctions in reward processing are difficult to study in Parkinson's disease as most patients have been treated with dopaminergic drugs, which sensitize reward responses in the ventral striatum, commonly resulting in impulse control disorders. To circumvent this treatment confound, we assayed the neural basis of reward processing in a group of newly diagnosed patients with Parkinson's disease that had never been treated with dopaminergic drugs. Thirteen drug-naive patients with Parkinson's disease and 12 healthy age-matched control subjects underwent whole-brain functional magnetic resonance imaging while they performed a simple two-choice gambling task resulting in stochastic and parametrically variable monetary gains and losses. In patients with Parkinson's disease, the neural response to reward outcome (as reflected by the blood oxygen level-dependent signal) was attenuated in a large group of mesolimbic and mesocortical regions, comprising the ventral putamen, ventral tegmental area, thalamus and hippocampus. Although these regions showed a linear response to reward outcome in healthy individuals, this response was either markedly reduced or undetectable in drug-naive patients with Parkinson's disease. The results show that the core regions of the meso-cortico-limbic dopaminergic system, including the ventral tegmental area, ventral striatum, and medial orbitofrontal cortex, are already significantly compromised in the early stages of the disease and that these deficits cannot be attributed to the contaminating effect of dopaminergic treatment.
A JOURNAL OF NEUROLOGY
Attenuated neural response to gamble outcomes in
drug-naive patients with Parkinson’s disease
Joyce P. M. van der Vegt,
Oliver J. Hulme,
Kristoffer H. Madsen,
Michael M. Weiss,
Bastiaan R. Bloem,
Hartwig R. Siebner
1 Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
2 Department of Neurology, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behaviour, 6500 HB
Nijmegen, The Netherlands
3 Department of Paediatric and Adult Movement Disorders and Neuropsychiatry, Institute of Neurogenetics, University of Lu¨ beck, 23562 Lu¨ beck,
4 Department of Neurology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
5 Department of Neurology, Christian-Albrechts-University, 24105 Kiel, Germany
Correspondence to: Prof. Hartwig R. Siebner (MD),
Danish Research Centre for Magnetic Resonance,
Copenhagen University Hospital Hvidovre,
Parkinson’s disease results from the degeneration of dopaminergic neurons in the substantia nigra, manifesting as a spectrum of
motor, cognitive and affective deﬁcits. Parkinson’s disease also affects reward processing, but disease-related deﬁcits in re-
inforcement learning are thought to emerge at a slower pace than motor symptoms as the degeneration progresses from dorsal
to ventral striatum. Dysfunctions in reward processing are difﬁcult to study in Parkinson’s disease as most patients have been
treated with dopaminergic drugs, which sensitize reward responses in the ventral striatum, commonly resulting in impulse
control disorders. To circumvent this treatment confound, we assayed the neural basis of reward processing in a group of newly
diagnosed patients with Parkinson’s disease that had never been treated with dopaminergic drugs. Thirteen drug-naive patients
with Parkinson’s disease and 12 healthy age-matched control subjects underwent whole-brain functional magnetic resonance
imaging while they performed a simple two-choice gambling task resulting in stochastic and parametrically variable monetary
gains and losses. In patients with Parkinson’s disease, the neural response to reward outcome (as reﬂected by the blood oxygen
level-dependent signal) was attenuated in a large group of mesolimbic and mesocortical regions, comprising the ventral puta-
men, ventral tegmental area, thalamus and hippocampus. Although these regions showed a linear response to reward outcome
in healthy individuals, this response was either markedly reduced or undetectable in drug-naive patients with Parkinson’s
disease. The results show that the core regions of the meso-cortico-limbic dopaminergic system, including the ventral tegmental
area, ventral striatum, and medial orbitofrontal cortex, are already signiﬁcantly compromised in the early stages of the disease
and that these deﬁcits cannot be attributed to the contaminating effect of dopaminergic treatment.
Keywords: fMRI; reward; mesolimbic system; Parkinson’s disease; drug-naive
doi:10.1093/brain/awt027 Brain 2013: 136; 1192–1203 | 1192
Received October 8, 2012. Revised December 7, 2012. Accepted December 27, 2012. Advance Access publication February 26, 2013
ß The Author (2013). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
For Permissions, please email: email@example.com
at Staats - und Universitaetsbibliothek Hamburg on June 23, 2013http://brain.oxfordjournals.org/Downloaded from
Although Parkinson’s disease is primarily characterized as a move-
ment disorder, there has been growing attention towards the
non-motor disturbances in sensory, affective and cognitive do-
mains (Lyons and Pahwa, 2011; Chen et al., 2012). The clinical
spectrum of Parkinson’s disease comprises a wide range of
non-motor symptoms such as autonomic dysfunction, hyposmia
and psychiatric and sleep disorders (Langston, 2006; Gallagher
et al., 2010). These non-motor symptoms are increasingly recog-
nized as important factors affecting the patient’s quality of life
(Langston, 2006; Soh et al., 2011). Several recent studies have
shown that many non-motor symptoms, in particular depression,
anxiety, rapid eye movement sleep disorder and hyposmia may
precede the onset of motor symptoms in Parkinson’s disease
(Alonso et al., 2009; Jacob et al., 2010; Kano et al., 2011;
Lyons and Pahwa, 2011; Wu et al., 2012; Yu et al., 2012).
Along similar lines, personality changes such as increasing intro-
version and decreased novelty seeking have been identiﬁed as
possible preclinical signs (Kano et al., 2011), and have been
hypothesized to result from a relatively early degeneration of the
mesolimbic dopaminergic pathways that extend beyond classical
nigrostriatal motor circuits (Ross et al., 2000; Braak et al., 2003,
2004; Kano et al., 2011). Such deﬁcits in novelty seeking and
approach behaviour are congruent with the emerging consensus
that dopamine is a transmitter involved in the computation of
short-term reward prediction errors (phasic dopamine) and the
long-term reward expectations (tonic dopamine) (Dayan and
Balleine, 2002; Montague et al., 2004; Berridge, 2007; Glimcher,
Some non-motor symptoms that are associated with Parkinson’s
disease reﬂect deﬁcits in motivational drive and reward processing.
Many patients suffer from depression and apathy, deﬁned as a
loss of motivation and interest and a reduction in effortful
behaviour (Aarsland et al., 2012; Gallagher and Schrag, 2012).
For instance, in a prospective study on 80 patients with
Parkinson’s disease, 50% showed signs of apathy, and 30% of
these did not express co-morbidity with depression (Kirsch-Darrow
et al., 2006).
Another major motivational dysfunction, encountered in up to
13.6% of patients receiving dopamine replacement therapy, is the
inability to appropriately control impulses to engage in rewarding
behaviours. The clinical spectrum is broad and includes hypersexu-
ality, compulsive shopping, pathological gambling, punding, com-
pulsive eating, as well as compulsive use of dopaminergic
medication (Weintraub et al., 2010; Ambermoon et al., 2011;
Voon et al., 2011; Vilas et al., 2012). These impulse control dis-
orders often have major adverse consequences on the quality of
life of the patient and their caregivers (Wolters et al., 2008).
Multiple intrinsic and extrinsic factors are thought to contribute
to impulse control disorders in Parkinson’s disease. Male gender,
early disease onset, depression, pre-existing recreational drug or
alcohol use, and novelty seeking personality traits are associated
with a higher prevalence of impulse control disorders. However,
dopamine replacement therapy, in particular the treatment with
dopamine agonists, constitutes the main risk factor for developing
impulsive behaviours (Weintraub et al., 2010; Ambermoon et al.,
2011; Cilia and van Eimeren, 2011). The relevance of dopamine
treatment for the manifestation of impulse control disorders is
further supported by the fact that untreated patients with
Parkinson’s disease do not differ in impulse control disorder
frequency from healthy control subjects (Antonini et al., 2011;
Cilia et al., 2011). Because the mesolimbic dopaminergic system
is relatively less affected by the neurodegenerative process than
the mesostriatal dopaminergic system, the occurrence of impulse
control disorders has been attributed to a relative overstimulation
of the mesolimbic system by dopamine treatment (Morrish et al.,
1996; Booij et al., 1999; Cools et al., 2003; Braak et al., 2004).
Complementary to the ‘overdose hypothesis’, it has been
hypothesized that a pre-existing dysfunction of the mesocortico-
limbic pathway may predispose to impulse control disorders in
patients with Parkinson’s disease (Balarajah and Cavanna, 2012).
The high prevalence of motivational deﬁcits such as depression
or apathy, which often precede the onset of motor symptoms, as
well as the risk of inducing impulse control deﬁcits when starting
dopamine treatment suggest that the meso-cortico-limbic circuits
are already dysfunctional early in the disease before the adminis-
tration of dopamine medication. However, this hypothesis remains
to be explicitly addressed, since reward function in Parkinson’s
disease has almost exclusively been probed in patients who had
ongoing or prior dopamine therapies. Such studies reveal that pa-
tients with Parkinson’s disease tend to make suboptimal choices
(relative to healthy control subjects) in gambling tasks, and appear
to be hypersensitive to rewards and hyposensitive to punishment
(Robinson and Berridge, 1993; Czernecki et al., 2002; Thiel et al.,
2003; Perretta et al., 2005; Abou-Sleiman et al., 2006; Mimura
2006; Berridge, 2007; Schott et al., 2007; Kobayakawa
et al., 2008, 2010; van Eimeren et al., 2009; Frosini et al. ,
2010; Housden et al., 2010; Schonberg et al., 2010; Voon
et al., 2010). A hypersensitivity to rewarding cues appears to be
particularly associated with impulse control disorders. In two
C-raclopride PET studies, patients with impulse control disorders
showed a greater endogenous dopamine release during gambling
(Steeves et al., 2009) and in the context of reward-related cues
(O’Sullivan et al., 2011) relative to patients without an impulse
control disorder. While most of this evidence is congruent with a
hyper-dopaminergic dysfunction, it remains to be shown whether
this reﬂects a primary dysfunction or is driven by the confounding
effects of dopamine treatment.
Using functional MRI, this study was designed to characterize
the function of meso-cortico-limbic circuits in de novo patients
who have been newly diagnosed with Parkinson’s disease. Given
that the disease process is most likely related to a hypo-
dopaminergic state (Schott et al., 2007; Bodi et al., 2009), our
central hypothesis was that in the absence of ongoing or prior
dopamine treatment, the reward responsivity of the meso-
cortical-limbic system would already be attenuated in the early
motor stage of Parkinson’s disease. Additionally, we hypothesized
that this impaired reward responsivity would correlate with clinical
measures of disease severity as reﬂected by the Movement
Disorder Society Uniﬁed Parkinson’s Disease Rating Scale score
(Goetz et al., 2007). We tested these hypotheses by probing func-
tional responses of the mesolimbic and mesocortical systems while
Reduced reward sensitivity in PD Brain 2013: 136; 1192–1203 | 1193
at Staats - und Universitaetsbibliothek Hamburg on June 23, 2013http://brain.oxfordjournals.org/Downloaded from
recently diagnosed drug-naı¨ve patients with Parkinson’s disease
engaged in a simple probabilistic gambling task.
Materials and methods
Thirteen de novo patients with Parkinson’s disease (eight males, mean
age: 58 10 years) who were naive to dopamine medication and 12
healthy control subjects (ﬁve males, mean age: 60 7 years) without
a history of impulse control disorders or other psychiatric or neuro-
logical symptoms participated in the study (Table 1). Written consent
was obtained from all participants according to the Declaration of
Helsinki, and the study was approved by the local research ethics
committee. Newly diagnosed patients with Parkinson’s disease were
prospectively recruited from the outpatient clinic for movement dis-
orders at the Department of Neurology, University Medical Centre
Hamburg-Eppendorf, Hamburg, Germany. Diagnosis of Parkinson’s
disease had been made within a 2-week period before testing by a
movement disorder specialist (C.B.) in accordance with the UK
Parkinson’s Disease Society Brain Bank clinical diagnostic criteria. The
inclusion criterion was that patients had not previously been treated
with dopamine drugs. Additionally, patients should not have under-
gone a diagnostic levodopa test in the 12 months before the study.
Three patients had a low dose acute levodopa test in the past (42
years ago), but had not used any dopamine medication since then.
The reported onset of motor symptoms ranged from 0.5 to 5 years
(median symptom duration: 3 years).
Prior to scanning, all subjects were examined using the Movement
Disorder Society Uniﬁed Parkinson’s Disease Rating Scale (Goetz et al.,
2007) motor rating scale (part III) and classiﬁed according to the
Hoehn and Yahr (Hoehn and Yahr, 1967; Goetz et al., 2004) and
Schwab and England scales (Schwab, 1968). Global cognitive function
was assessed using the Mini-Mental State Examination (Folstein et al.,
1975). Presence of depression was measured using Beck Depression
Inventory II (Psychological Corporation). To rule out increased
risk-taking behaviour or the presence of problematic gambling, we
used the Barratt Impulsiveness Scale (Patton et al., 1995) and the
Gambling Addiction Questionnaire of the Berlin Gamblers Advisory
Committee. Through a clinical interview with the patients and if
available through their spouses, we ascertained that none of the
patients had explicit recall of any impulse control disorder-like behav-
iours or reported typical symptoms associated with impulse control
disorders such as pathological gambling, compulsive sexual behaviour,
compulsive shopping, compulsive/binge eating or punding.
During each functional MRI acquisition session (60 trials), participants
engaged in a simple gambling task (Fig. 1) that has been shown to
reliably elicit reward-related responses in the basal ganglia (Yacubian
et al., 2006). A similar version of the gambling task has been used in
a previous study that revealed abnormalities in reward responsivity
in ventral striatum in pathological gamblers (Reuter et al., 2005).
At the onset of each trial, two playing cards were presented
alongside iconic representations of the money (low-stake = 2 E,or
high-stake = 5 E) which could be lost or won. Subjects were required
to decide within 3 s which card to gamble on. Subjects indicated their
decision by a button press (right index for left, or middle for right) and
after a jittered period (1–7 s, ﬂat probability distribution) the outcome
was revealed. Between trials there was also a jittered resting period (1–
7 s, ﬂat probability distribution). Outcome contingencies were set and
explicitly instructed to the participants, so that red cards resulted in
winning the stake, black cards in losing. A running total amount of
cumulative gains and losses was displayed above the card at all times
during the trial.
Each subject was randomly assigned to one of ﬁve preset
pseudo-randomized sequences of gambling trials. In macaque mon-
keys, phasic dopaminergic responses have been shown to be max-
imally responsive to unpredictable outcomes, and at the single cell
level within the ventral tegmental area and substantia nigra, ﬁring
rates are commonly maximal for reward probabilities of 0.5 (Schultz
et al., 2008). Therefore, gamble probabilities were set to 0.5 for win-
ning versus losing. Stimuli were presented by back-projection, viewed
using a head-coil mirror. Task presentation and recording of behav-
ioural responses were performed using the software Presentation
(Neurobehavioral Systems, Inc.). Before scanning, subjects received a
standardized verbal description of the task, in which they were in-
structed not to press the same button constantly, and truthfully in-
formed of the outcome probabilities and that the cumulative total
would be realized in physical currency at the end of the experiment
after 60 gambles. To ensure task competence, subjects were trained
on the task outside the scanner (10–15 trials).
Functional magnetic resonance imaging
data acquisition and analysis
Functional MRI scanning was performed on a 3 T MRI Scanner
(Siemens Trio, Siemens) with a 12-channel head coil. Thirty-eight
transversal slices (slice thickness 3 mm) were acquired in each
volume (repetition time: 2.5 s; echo time 34 ms; ﬂip angle: 90
of view 216 mm) using gradient echo T
*-weighted echo planar ima-
ging. The ﬁrst three volumes of each participant were discarded to
saturation effects. High-resolution (1 mm
-weighted images were acquired for each subject, using a
Our regions of interest in the basal ganglia are vulnerable to accu-
mulation of iron in Parkinson’s disease (Bartzokis et al., 1994;
Pfefferbaum et al., 2010). We therefore compared the individual
signal strength in the basal ganglia (deﬁned according to WFU
Pickatlas; Maldjian et al., 2003) between groups to rule out whether
Table 1 Demographics, test scores and task performance of
patients with Parkinson’s disease and
Number (males) 13 (8 males) 12 (5 males)
Age (years) 58 ( 10) 60 ( 7)
Disease duration (years) 3.0 Not applicable
UPDRS motor score (SD) 25.6 ( 8.7) 0.1 ( 0.3)
MMSE (SD) 29.7 ( 0.7) 29.6 ( 0.8)
BIS 66.0 ( 5.6) 65.3 ( 5.8)
GAQ 0.3 ( 1.1) 0.25 ( 0.62)
Mean response times (s) 1.06 ( 0.19) 1.08 ( 0.23)
Missed card choices % (range) 3.3 (0–11.7) 0.8 (0–11.7)
BIS = Barratt Impulsiveness Scale; GAQ = Gambling Addiction Questionnaire;
MMSE = Mini-Mental State Examination; UPDRS = Uniﬁed Parkinson’s
Disease Rating Scale.
1194 | Brain 2013: 136; 1192–1203 J. P. M. van der Vegt et al.
at Staats - und Universitaetsbibliothek Hamburg on June 23, 2013http://brain.oxfordjournals.org/Downloaded from
blood oxygen level-dependent signal changes in the basal ganglia
were due to structural or morphological confounds.
Data preprocessing and analysis were performed using statistical
parametric mapping 8 (SPM8; Wellcome Department of Imaging
Neuroscience, London, UK). Data preprocessing consisted of realign-
ment (rigid body motion correction), segmentation of the high-
image, to which the functional images then were
co-registered. All images were spatially normalized to Montreal
Neurological Institute (MNI) space using the normalization parameters
obtained from the segmentation procedure and subsequently
smoothed with a Gaussian kernel of 8 mm full-width at half maximum.
First level data analysis was performed on each subject using the
general linear model in which events of interest were modelled as stick
functions convolved with a canonical haemodynamic response
function, as implemented in SPM8. To model the choice phase, we
constructed two regressors time-locked to the onset of the choice to
independently model high and low stake trials. Note that the choice
phase included both the button-press and a period of outcome antici-
pation, which could not be separated in this design due to their
complete co-linearity. To model the outcome phase we constructed
four regressors (time-locked to onset of the outcome) for all factorial
combinations of outcome (win versus loss), and value (high versus
low). Twenty-four movement regressors were extracted to model
residual effects of movement after rigid body realignment (Friston
et al., 1996). Modelling of residual effects of movement after rigid
body realignment was handled by adding a Volterra expansion of the
movement parameters as nuisance regressors in the general linear
model. This ﬁlter contains the six motion parameters estimated from
the rigid body realignment procedure as well as the parameters from
the previous volume to take care of spin history effects. Also the ﬁlter
is expanded to second order (movement parameters squared) giving a
total of 24 additional free parameters in the estimation of the general
After model estimation the planned contrasts for each event type
were computed using one sample t-tests (unless otherwise speciﬁed).
The contrast images from each subject were entered in a group-level
random effects analysis. We computed one-way ANOVAs separately
for all choice and outcome events. To compare motor activity at the
time of button press in the choice phase, we created a ﬁrst order
contrast for (Choice) between groups on the second level. We created
a ﬁrst-order parametric linear t-contrast for (wins versus losses) for the
groups separately and between groups.
All statistical inferences applied a signiﬁcance threshold of P 5 0.05
after correction for multiple comparisons. Correction was performed
using the family-wise error (FWE) at the cluster level using the
family-wise error correction method as implemented in SPM. We
used an uncorrected threshold of P 5 0.001 to deﬁne the extent of
The mesolimbic and mesocortical regions deﬁned as regions of inter-
est, included the ventral tegmental area, ventral striatum, putamen,
caudate nucleus, thalamus, hippocampus and medial orbitofrontal
cortex. Where region of interest analysis was performed, correction
for number of regions of interest was performed, unless otherwise
stated. For each region of interest we used the anatomical region as
deﬁned in the WFU Pickatlas (Maldjian et al., 2003). For activations
outside the predeﬁned regions of interest, FWE correction considered
all voxels in the brain. Note that all statistical parametric maps shown
were thresholded at an uncorrected P 5 0.001 for display purposes.
Relative blood oxygen level-dependent signal changes were computed
using the rfxplot toolbox (Glascher, 2009), and x, y, z in ﬁgures refer
to the coordinates of the peak voxel in MNI stereotactic space. Uniﬁed
Parkinson’s Disease Rating Scale motor scores and Barratt
Impulsiveness Scale scores were taken to the random effects level as
covariates of interest, where age was treated as a nuisance covariate.
Reaction times and other behavioural data were statistically analysed
using SPSS (SPSS Inc.). For behavioural data analyses, signiﬁcance level
was set at P 5 0.05 and group data are given as mean standard
Behavioural data and motor scores
The clinical data as well as the group data for each test are listed
in Table 1. Thirteen dopamine-naive patients with Parkinson’s dis-
ease and 12 healthy control subjects completed the experiment
(additionally one patient with Parkinson’s disease and six control
subjects were excluded due to non-compliance and technical
problems). Mean Uniﬁed Parkinson’s Disease Rating Scale motor
score of the 13 drug-naive patients was 25.6 ( 8.7 SD). At the
time of study, clinical tests and a detailed clinical interview yielded
no evidence of depressive disorder (Beck Depression Inventory II
mean 5.8 4.6 SD, maximal Beck Depression Inventory II score:
63), dementia (Mini-Mental State Examination 29.7 0.7 SD,
cut-off point: 25), increased risk-taking behaviour (Barratt
Impulsiveness Scale 66 5.6 SD, maximal Barratt Impulsiveness
Scale score: 120), or pathological gambling (Gambling Addiction
Questionnaire 0.3 1.1 SD, maximal Gambling Addiction
Questionnaire score: 20).
Response times for gamble performance did not differ between
groups [patients with Parkinson’s disease: 1.06 0.19 s versus
healthy control subjects: 1.08 0.23 s; two-sample t-test:
Figure 1 Design of the gambling task. At trial onset (choice
phase) participants were dealt two playing cards, alongside
iconic representation of the money at stake, either 2 E
(low-stake) or 5 E (high-stake). Subjects were instructed to
select, with a right-hand button press (index ﬁnger for left card,
middle for right), which card to select within 3 s. During a jittered
period of anticipation (1–7 s) the card was revealed resulting in
the monetary gain or loss of the stake (red card signalled
winning outcomes, black losses). Between trials there is a jittered
period of rest (1–7 s). A cumulative total was displayed above
the card at all times during the trial. Probability of winning was
50% and remained constant throughout.
Reduced reward sensitivity in PD Brain 2013: 136; 1192–1203 | 1195
P = 0.81, conﬁdence interval (CI): 0.16–0.20] and there was no
signiﬁcant difference in choice probability between right or left
card choices within (paired t-test: patients with Parkinson’s dis-
ease: P = 0.38, CI: 10.3–4.3; healthy control subjects: P = 0.94
CI: 10.7–10.0) and between groups (two-sample t -test: Right:
P = 0.57, CI: 7.9–4.5; Left: P = 0.73, CI: 4.7–6.7). The per-
centage of trials in which the choice period expired without a
choice was negligible (median, patients with Parkinson’s dis-
ease = 3.3%, control subjects = 0.8%) and not signiﬁcantly differ-
ent between groups (Mann–Whitney U-test, Z = 1.44, P = 0.15,
healthy control subjects mean rank: 10.88, patients with
Parkinson’s disease mean rank: 14.96).
Functional magnetic resonance imaging
Comparison of signal strength
We compared the signal strength in the basal ganglia between
groups, to evaluate whether blood oxygen level-dependent
signal changes in our regions of interest (putamen and caudate
nucleus) were not due to structural or morphological differences.
We found no signiﬁcant difference for the signal strength in pu-
tamen between patients and healthy control subjects (Mann–
Whitney U-test Z = 0.54, P=0.59, healthy control subjects mean
rank: 12.17, patients with Parkinson’s disease mean rank: 13.77)
and caudate nucleus (Mann–Whitney U-test Z = 0.49, P=0.62,
healthy control subjects mean rank: 12.25, patients with
Parkinson’s disease mean rank: 13.69).
As this was a very simple task, no differences in the movement-
related blood oxygen level-dependent response between the two
groups were expected. The comparison of the activation induced
by the button press did not show any signiﬁcant differences in
activation of the motor areas between control subjects and pa-
tients. However, patients showed a weak trend towards a higher
activation in the pre-supplementary motor area when the statis-
tical model included individual Uniﬁed Parkinson’s Disease Rating
Scale score and age as regressors (peak difference: Z = 2.89 at x,
y, z =3, 1, 61).
Increases in regional activity with reward outcome value
The main aim of our analysis was to identify brain regions where
regional activity showed a linear increase with reward outcome.
Therefore, analysis focused on the gamble outcome phase.
Because our statistical model included separate regressors for
each outcome value (from high losses to high wins), we were
able to compute weighted contrasts that test for the positive
linear effect of outcome value on regional activity. As expected,
this contrast showed a widespread distribution of functional acti-
vation for healthy control subjects (Fig. 2). Activations included
many of the core hedonic and affective regions of interest
within the meso-cortical-limbic system, which are expected to be
critically involved in processing of reward outcome value. Linear
increases in activity with reward outcome were found in the ven-
tral striatum, ventral tegmental area, caudate nucleus, thalamus,
hippocampus and medial orbitofrontal cortex (Table 2). Region of
interest analysis revealed that positive linear responses in the
hippocampus and ventral tegmental area were signiﬁcant. For
ventral striatum, caudate nucleus, thalamus, and medial orbito-
frontal cortex, the linear increases were signiﬁcant even after cor-
rection for multiple comparisons across the whole brain.
In contrast, patients showed no signiﬁcant activations in any of
the predeﬁned regions of interest or elsewhere in the brain, even
at an exploratory threshold (P 5 0.001 uncorrected). Only when
we applied a very liberal threshold (P 5 0.01 uncorrected), the
ventral putamen (bilateral), orbitofrontal cortex (right) and the
occipital lobe (bilateral) displayed weak statistical trends towards
a linear increase in activity with reward outcome value (Fig. 2).
Equivalent contrasts testing the negative linear effect of outcome
value did not show any signiﬁcant effects for either group, even at
Between-group differences in reward related activity
Within the predeﬁned regions of interest, patients with Parkinson’s
disease showed a signiﬁcantly reduced neural response to increas-
ing reward outcome values compared with healthy control sub-
jects. The positive linear relationship between reward outcome and
outcome-related activity was attenuated in the ventral and dorsal
putamen, ventral tegmental area, thalamus, the caudate nucleus,
hippocampus, medial frontal gyrus, inferior frontal gyrus and oc-
cipital visual areas (P 5 0.05 FWE, Table 2). The results show that
core regions of the meso-cortico-limbic dopaminergic system,
including the ventral tegmental area, ventral striatum, and
medial orbitofrontal cortex, are already signiﬁcantly compromised
in the early stages of the disease. Additionally, the insula, cerebel-
lum, premotor and superior frontal area showed a similar trend
towards a reduced responsiveness to reward outcome value at a
more liberal exploratory threshold (P 5 0.001 uncorrected), but
these decreases did not survive whole-brain correction (Fig. 3).
The same group comparison for the negative linear effect of out-
come value did not show any signiﬁcant effect, even at trend
Attenuation in the patients’ linear response to reward outcome
could be due to a deﬁcit in the magnitude of responses to either
losses, gains or to both. To distinguish these possibilities we per-
formed the same contrast independently for wins and losses.
Testing for the between group difference (healthy control sub-
jects 4 patients with Parkinson’s disease) in the positive linear re-
sponses to value for wins, patients showed signiﬁcantly attenuated
responses in the dorsal putamen, caudate nucleus, thalamus, ven-
tral tegmental area, posterior parietal cortex, inferior and medial
frontal gyrus and the left motor cortex and right cerebellum
(Fig. 4A). Isolating the high magnitude wins from the low
showed this effect was mainly produced by the high magnitude
outcomes. The converse contrast, testing the negative linear effect
for wins, did not show any signiﬁcant effect.
Testing for group differences (healthy control subjects 4 pa-
tients with Parkinson’s disease) in the positive linear response to
losses, we found no signiﬁcant effect. The converse contrast test-
ing the negative linear response to losses, showed signiﬁcantly less
deactivation in patients with Parkinson’s disease compared with
control subjects in the ventral putamen, parahippocampal gyrus
and hippocampus, thalamus and medial and superior frontal
gyrus (Fig. 4B). Separating high losses and low losses shows this
effect was mainly carried by high losses. Statistical conjunction of
1196 | Brain 2013: 136; 1192–1203 J. P. M. van der Vegt et al.
linear effects and a more liberal inclusive mask contrast for both
wins and losses showed no signiﬁcant regions.
Increases in reward related activity with Uniﬁed
Parkinson’s Disease Rating Scale or Barratt
Impulsiveness Scale scores
In the patient group, we regressed the individual Uniﬁed
Parkinson’s Disease Rating Scale score against the outcome
value-based parameter estimates to identify brain regions where
neural responses to reward outcome showed a linear relation with
clinical impairment. Outcome-related activity in the bilateral
ventral premotor region (left 4 right) centred on the junction be-
tween inferior frontal sulcus and precentral sulcus—also referred
to as the inferior frontal junction region—and the right inferior
frontal gyrus showed a trend towards a positive linear increase
with outcome value (P 5 0.001 uncorrected). This statistical
trend suggests increased responsivity to reward outcome values
with severity of motor symptoms. The converse contrast for nega-
tive linear reward responses showed no signiﬁcant activations. As
with the analysis above, we computed the Uniﬁed Parkinson’s
Disease Rating Scale regression independently for wins and
losses. Surprisingly, for wins-only we did not ﬁnd any region
Figure 2 Linear effect of outcome value. The effect of outcome value on outcome-related neural activity tested by computing the
weighted contrasts of the separate regressors set for each outcome value (from high losses to high wins). (A) Statistical parametric maps
showing widespread increases in activity with reward outcome value, including many of the hedonic and affective regions of interest
within the basal ganglia and mesocortical dopamine system. The statistical maps are thresholded at P 5 0.001 (uncorrected). The bar gives
the colour coding of T-values for each voxel. P = posterior; A = anterior; L = left; R = right. (B) The corresponding statistical parametric
maps in patients with Parkinson’s disease showed only trend activations in ventral putamen, right orbitofrontal cortex and occipital visual
areas bilaterally, when applying a more liberal threshold [P 5 0.01 (uncorrected)]. (C) Activation proﬁle of outcome-related activity for
regional peak activation in right ventral striatum. Healthy controls (left) show a stronger increase in outcome-related activity with outcome
value than drug-naive de novo patients with Parkinson’s disease (right, Z = 2.94). PD = Parkinson’s disease.
Reduced reward sensitivity in PD Brain 2013: 136; 1192–1203 | 1197
that correlated (positively or negatively) with Uniﬁed Parkinson’s
Disease Rating Scale. The loss-speciﬁc contrast showed the same
proﬁle of regions as the full value (wins and losses) regression
indicating that it is the loss-speciﬁc response that was carrying
To identify brain regions where the reward response covaried
with risk-taking propensities (across subjects) we regressed the
individual Barratt Impulsiveness Scale scores onto the
subject-speciﬁc linear effect of outcome value. In right dorsal pu-
tamen, left thalamus, left insula and right inferior frontal gyrus, the
linear increase in neural response with outcome value correlated
positively with individual Barratt Impulsiveness Scale scores (cluster
level, P 5 0.05 FWE, Fig. 5). Neither the converse contrast for
negative linear reward responses, nor the independent analyses
for wins or losses showed a signiﬁcant linear relationship with in-
dividual Barratt Impulsiveness Scale scores.
This is the ﬁrst functional neuroimaging study to investigate
the neural basis of reward sensitivity in a group of recently
diagnosed, drug-naive patients with Parkinson’s disease. By
including only untreated patients with Parkinson’s disease, we
avoided any confounding effects of anti-parkinsonian medication
that would modify dopaminergic transmission. We found
that early Parkinson’s disease is associated with a marked and
widespread attenuation of the neural response to gamble
outcomes across a broad distribution of the mesocortical and
mesolimbic systems, extending into classical motor areas (Fig. 2).
Compared with healthy control subjects, DOPA-naı¨ve patients
with Parkinson’s disease showed either a substantially attenuated
or undetectable linear representation of rewards and punishments
in the ventral putamen, ventral tegmental area, thalamus
and subthalamic nucleus, the caudate nucleus, hippocampus,
insula, medial frontal, inferior frontal and superior frontal
areas (Fig. 3). Additionally, deﬁcits were evident in motor cortices,
the ventral premotor cortex and cerebellum (anterior lobe) and
even in the visual cortical areas of the occipital lobe. The ﬁnding
that patients with Parkinson’s disease expressed signiﬁcantly atte-
nuated neurometric reward response functions was further corro-
borated by the absence of a linear main effect of outcome value in
any of the mesocortical or mesolimbic networks of interest. The
lack of discernable signals is particularly remarkable given that
monetary losses or gains have consistently been shown to
induce strong and reproducible effects on blood oxygen
level-dependent responses in these regions (Knutson et al.,
2000, 2001; Yacubian et al., 2006; Schott et al., 2008; Urban
et al., 2012).
Table 2 Functional MRI results of reward outcome
-stat Cluster size
Control group: linear increase in regional activity with reward outcome value (
_ 0.05, FWE corrected for whole brain)
Right anterior putamen 15, 8, 2 8.72 297
Left anterior putamen 15, 11, 1 9.30 163
Right thalamus 9, 16, 1 7.03 297
Left thalamus 9, 16, 1 8.83 61
Right occipital cortex 36, 88, 7 10.00 2134
Left occipital cortex 27, 94, 10 9.57 2134
Medial orbitofrontal gyrus 6, 41, 5 8.15 76
Left inferior frontal gyrus 39, 50, 4 6.79 434
Right caudate nucleus 12, 11, 2 7.83 95
Left caudate nucleus 12, 11, 2 8.28 78
Right hippocampus 30, 13, 17 6.04 20
Left hippocampus 33, 19, 17 5.44 32
Right ventral tegmental area 3, 19, 14 4.97 7
Left ventral tegmental area 3, 19, 14 5.24 7
Stronger increase in reward outcome related activity in the control group relative to the patient group (
_ 0.05, FWE after region of
interest analyses corrected for number of regions of interest)
Right putamen 18, 8, 2 4.74 143
Left putamen 18, 11, 1 4.68 153
Right thalamus 6, 19, 1 4.97 143
Left thalamus 12, 13, 13 4.98 120
Medial orbitofrontal gyrus 6, 41, 5 4.62 77
Left inferior frontal gyrus 42, 53, 4 4.60 49
Right caudate nucleus 15, 8, 2 4.53 13
Left caudate nucleus 15, 11, 1 4.80 13
Right hippocampus 30, 16, 14 4.80 37
Left ventral tegmental area 3, 19, 11 3.98 4
Right occipital cortex 36, 76, 28 4.83 12
Anatomical areas with their (x, y, z) coordinates and statistical values indicated.
1198 | Brain 2013: 136; 1192–1203 J. P. M. van der Vegt et al.
Figure 3 Differences in the linear responses to reward outcome value between healthy control subjects and patients with Parkinson’s
disease. (A) Axial statistical parametric maps displaying regions showing a stronger increase in activity with reward outcome value for
control subjects than for patients. Signiﬁcant value related differences for healthy control subjects versus patients with Parkinson’s disease
are present in the ventral and dorsal putamen, ventral tegmental area, thalamus and subthalamic nucleus, the caudate nucleus,
hippocampus, insula, cerebellum, medial frontal, inferior frontal and superior frontal areas, premotor and occipital visual areas. The
statistical maps are thresholded at P 5 0.001 (uncorrected), extent threshold 50 voxels. The bar gives the colour coding of T-values for
each voxel. P = posterior; A = anterior; L = left; R = right. (B–D) Parameter estimates for outcome-related activity for regional peak
activation in left putamen (B), left ventral tegmental area (C) and right hippocampus (D). All areas show a ﬂattened or undetectable linear
increase in neural response with outcome value in patients with Parkinson’s disease, whereas healthy control subjects show a clear linear
reward value related activity in these key regions of the mesolimbic system. PD = Parkinson’s disease.
Reduced reward sensitivity in PD Brain 2013: 136; 1192–1203 | 1199
In all of the aforementioned regions, attenuation in the patient’s
linear response to outcome values was present for both gains
and losses. In mesolimbic structures, the caudate nucleus and
ventral tegmental area showed a marked attenuation of neural
responses to gain magnitude, whereas the ventral putamen
showed a signiﬁcantly reduced responsiveness to loss magnitude
(Fig. 4) and no region expressed a statistical conjunction of
attenuation effects for both wins and losses. This shows
that early in the presentation of Parkinson’s disease, speciﬁc
subregions of the mesolimbic system become more insensitive to
losses whereas others selectively lose their sensitivity to gains
(Fig. 4). One possible underlying cause of the diminished
linear response would be that the neurodegenerative process
in Parkinson’s disease induced substantial non-linearity in the
neurometric response function to outcome value. Although our
paradigm only elicited two magnitudes of gains/losses and
therefore does not allow for non-linear inference, our parameter-
ization of the response function does allow independent estima-
tion of the response to each magnitude. The four independent
main effects for each outcome value show substantially
the same result as discussed above, mainly carried by high wins
and high losses, and thus the between group difference can-
not be due to suboptimal parameterization of the response
Figure 4 Differences in the linear responses to reward outcome value between healthy control subjects and patients with Parkinson’s
disease for wins and losses, respectively. (A) Axial statistical parametric map showing signiﬁcantly higher win related activation for healthy
control subjects versus patients with Parkinson’s disease, in the dorsal putamen, caudate nucleus, thalamus, ventral tegmental area,
posterior parietal cortex, inferior and medial frontal gyrus and the left motor cortex and right cerebellum. (B) Axial statistical parametric
map showing signiﬁcantly less loss-related deactivation in patients with Parkinson’s disease compared with healthy control subjects in the
ventral putamen, parahippocampal gyrus and hippocampus, thalamus and medial and superior frontal gyrus. The statistical maps are
thresholded at P 5 0.001 (uncorrected). The bar reﬂects the colour coding of T-values for each voxel. P = posterior; A = anterior; L = left;
R = right.
Figure 5 Interindividual differences in risk-taking behaviour as reﬂected by the Barratt Impulsiveness Scale score are associated with
increased reward-value related activity in the right putamen and left thalamus in the patient group. (A) Axial parametric map showing a
cluster in the right putamen (peak t-score = 7.97 at x = 24, y = 10, z = 7, cluster extent = 46 voxels) and left thalamus (peak
t-score = 7.34 at x = 18, y = 16, z = 7, cluster extent = 46 voxels), where reward-related activity showed a positive linear relationship
with the individual Barratt Impulsiveness Scale score. The statistical maps are thresholded at P 5 0.001 (uncorrected). The bar reﬂects the
colour coding of T-values for each voxel. P = posterior; A = anterior; L = left; R = right. (B) The scatter plot illustrates the positive linear
increase in the estimated reward related blood oxygen level-dependent response with the Barratt Impulsiveness Scale score for the peak
voxel of the right putamen, indicating higher sensitivity to reward outcome value with increased risk-taking behaviour. BOLD = blood
1200 | Brain 2013: 136; 1192–1203 J. P. M. van der Vegt et al.
To test whether intersubject variability in clinical severity corre-
lated with neural response to gamble outcomes, we tested for a
linear relationship between the individual Uniﬁed Parkinson’s
Disease Rating Scale III score and regional response proﬁle to
reward value (to both gains and losses). Activity in the right in-
ferior frontal gyrus and inferior frontal junction region only
showed a trend towards increased responsiveness to reward out-
come values with severity of motor symptoms. Intersubject vari-
ability in risk-taking behaviour correlated with neural responses to
gamble outcomes in patients. The individual Barratt Impulsiveness
Scale scores showed a positive linear relationship with reward out-
come value responses in the right dorsal putamen, left thalamus,
left insula and right inferior frontal gyrus. This relation indicates
higher reward responsiveness in the right dorsal putamen and left
thalamus in patients with stronger risk-taking behaviour (Fig. 5).
This ﬁnding shows that the pre-existing risk-taking trait enhances
the responsiveness of cortical and subcortical brain regions to re-
warding outcomes. We speculate that such enhanced responsive-
ness might inﬂuence the individual susceptibility to impulse control
disorders in response to dopamine therapy. Since the present
study was not designed to address potential links between
pre-existing impulsivity and dopamine-triggered impulse control
disorders, this interesting question needs to be addressed in
larger prospective functional MRI studies
Taken together, the evidence presented here suggests that the
encoding of reward and punishment outcomes is already signiﬁ-
cantly impoverished in newly diagnosed patients with Parkinson’s
disease before the initiation of dopamine replacement pharmaco-
therapy. It shows that the remaining reward sensitivity may be
curtailed down from large swathes of mesolimbic, mesocortical,
motor and occipital regions down to a few islands within orbito-
frontal cortex, ventral putamen and occipital cortex. It is of inter-
est that even for these remaining regions, there is a signiﬁcant
reduction in the response magnitude compared with healthy con-
trol subjects (Fig. 2). Thus, the results indicate that this attenuated
responsiveness to reward outcome value is widespread and in-
volves the majority of regions within the reach of dopaminergic
transmission. This includes classical reward structures of the basal
ganglia and medial orbitofrontal cortex, but also extending into
classical motor structures.
Our ﬁndings are of importance for current pathophysiological
concepts of Parkinson’s disease for a number of reasons. As
pointed out above, it has been postulated that the mesolimbic
system is only marginally affected at the early stages of
Parkinson’s disease due to a later involvement of the ventral stri-
atum relative to dorsal striatum (Fearnley and Lees, 1991; Morrish
et al., 1996; Cools et al., 2001; Braak et al., 2004). Our results
challenge the concept of relatively intact limbic circuits in the ear-
liest phases by showing that the reward responses of the meso-
limbic and mesocortical system are already signiﬁcantly impaired.
This has implications for the dopamine ‘overdose theory’, which
predicts that dopamine medication causes aberrant reinforcement
behaviour by excessive stimulation of a relatively intact reward
processing in the mesolimbic system. Our data suggest that in
early stages of Parkinson’s disease there is a signiﬁcantly reduced
reward responsivity in the ventral striatum before dopamine re-
placement therapy has started. This could be analogous to the
ﬁndings in pathological gamblers (without Parkinson’s disease),
who show decreased reward activity in the mesolimbic system
(Reuter et al., 2005; van Holst et al., 2010; Cilia and van
Eimeren, 2011; Miedl et al., 2012). The enhanced level of dopa-
mine induced by the dopamine medication leading to pathological
gambling in patients with Parkinson’s disease could consequently
be analogous to the heightening of dopamine release in the meso-
limbic system in pathological gamblers caused by gambling. This
aberrant increase in dopamine transmission could trigger errone-
ous expectancy coding and beliefs regarding the probability of
winning and thus contribute to continuation of gambling despite
heavy losses (Schultz, 2007; Clark et al., 2009; van Eimeren et al.,
2010), as has been suggested before (van Eimeren et al., 2010;
O’Sullivan et al., 2011). This, in combination with higher loss sen-
sitivity correlated with Uniﬁed Parkinson’s Disease Rating Scale,
could explain why patients with Parkinson’s disease without dopa-
mine medication tend to learn better from punishment and show
loss avoidant behaviour (i.e. ‘learning by stick’). This would then
convert to increased risk-seeking behaviour and learning from
positive rewards after the initiation of dopamine medication (i.e.
‘learning by carrot’), in accordance with what was also recently
shown in a behavioural study in mainly drug naı¨ve patients with
Parkinson’s disease (Frank et al., 2004, 2007; Schott et al., 2007;
Bodi et al., 2009), which still supports the basic tenet of the ‘over-
The behavioural correlates of this early neuronal deﬁcit remain
to be fully tested, and will be the target of future investigation. Of
particular clinical importance will be assessing the degree to which
these functional responses are clinically useful as an endopheno-
typic predictor of the response to dopamine treatment and its side
effects, as well as predicting pathological and behavioural trajec-
tories. Neurobiological insight into the drug-naive state thus
provides an essential window into the nascence of Parkinson’s
disease and its future remedy.
This work was supported by the Netherlands Organisation for
Scientiﬁc Research (NWO; VIDI grant No. 16.076.352 to B.R.B.)
and a grant of excellence by the Lundbeck Foundation on the
Control of Action (ContAct; grant No. R59 A5399 to H.R.S.)
Aarsland D, Pahlhagen S, Ballard CG, Ehrt U, Svenningsson P. Depression
in Parkinson disease—epidemiology, mechanisms and management
[Review]. Nat Rev Neurol 2012; 8: 35–47.
Abou-Sleiman PM, Muqit MM, McDonald NQ, Yang YX, Gandhi S,
Healy DG, et al. A heterozygous effect for PINK1 mutations in
Parkinson’s disease? Ann Neurol 2006; 60: 414–9.
Alonso A, Rodriguez LA, Logroscino G, Hernan MA. Use of antidepres-
sants and the risk of Parkinson’s disease: a prospective study. J Neurol
Neurosurg Psychiatry 2009; 80: 671–4.
Ambermoon P, Carter A, Hall WD, Dissanayaka NN, O’Sullivan JD.
Impulse control disorders in patients with Parkinson’s disease receiving
dopamine replacement therapy: evidence and implications for the
addictions ﬁeld [Review]. Addiction 2011; 106: 283–93.
Reduced reward sensitivity in PD Brain 2013: 136; 1192–1203 | 1201
Antonini A, Siri C, Santangelo G, Cilia R, Poletti M, Canesi M, et al.
Impulsivity and compulsivity in drug-naive patients with Parkinson’s
disease. Mov Disord 2011; 26: 464–8.
Balarajah S, Cavanna AE. The pathophysiology of impulse control dis-
orders in Parkinson disease. Behav Neurol 2012. Advance Access pub-
lished on May 24, 2012, doi: 10.3233/BEN-2012-120266.
Bartzokis G, Mintz J, Sultzer D, Marx P, Herzberg JS, Phelan CK, et al.
In vivo MR evaluation of age-related increases in brain iron. AJNR Am
J Neuroradiol 1994; 15: 1129–38.
Berridge KC. The debate over dopamine’s role in reward: the case for
incentive salience [Review]. Psychopharmacology (Berl) 2007; 191:
Bodi N, Keri S, Nagy H, Moustafa A, Myers CE, Daw N, et al.
Reward-learning and the novelty-seeking personality: a between-
and within-subjects study of the effects of dopamine agonists on
young Parkinson’s patients. Brain 2009; 132: 2385–95.
Booij J, Tissingh G, Winogrodzka A, van Royen EA. Imaging of the
dopaminergic neurotransmission system using single-photon emission
tomography and positron emission tomography in patients with par-
kinsonism [Review]. Eur J Nucl Med 1999; 26: 171–82.
Braak H, Ghebremedhin E, Rub U, Bratzke H, Del Tredici K. Stages in the
development of Parkinson’s disease-related pathology. Cell Tissue Res
2004; 318: 121–34.
Braak H, Del Tredici K, Rub U, de Vos RA, Jansen Steur EN, Braak E.
Staging of brain pathology related to sporadic Parkinson’s disease.
Neurobiol Aging 2003; 24: 197–211.
Chen W, Xu ZM, Wang G, Chen SD. Non-motor symptoms of
Parkinson’s disease in China: a review of the literature. Parkinsonism
Relat Disord 2012; 18: 446–52.
Cilia R, Cho SS, van Eimeren T, Marotta G, Siri C, Ko JH, et al.
Pathological gambling in patients with Parkinson’s disease is associated
with fronto-striatal disconnection: a path modeling analysis. Mov
Disord 2011; 26: 225–33.
Cilia R, van Eimeren T. Impulse control disorders in Parkinson’s disease:
seeking a roadmap toward a better understanding [Review]. Brain
Struct Funct 2011; 216: 289–99.
Clark L, Lawrence AJ, Astley-Jones F, Gray N. Gambling near-misses
enhance motivation to gamble and recruit win-related brain circuitry.
Neuron 2009; 61: 481–90.
Cools R, Barker RA, Sahakian BJ, Robbins TW. Enhanced or
impaired cognitive function in Parkinson’s disease as a function of
dopaminergic medication and task demands. Cereb Cortex 2001; 11:
Cools R, Barker RA, Sahakian BJ, Robbins TW. L-Dopa medication
remediates cognitive inﬂexibility, but increases impulsivity in patients
with Parkinson’s disease. Neuropsychologia 2003; 41: 1431–41.
Czernecki V, Pillon B, Houeto JL, Pochon JB, Levy R, Dubois B.
Motivation, reward, and Parkinson’s disease: inﬂuence of dopatherapy.
Neuropsychologia 2002; 40: 2257–67.
Dayan P, Balleine BW. Reward, motivation, and reinforcement learning
[Review]. Neuron 2002; 36: 285–98.
Fearnley JM, Lees AJ. Ageing and Parkinson’s disease: substantia nigra
regional selectivity. Brain 1991; 114 (Pt 5): 2283–301.
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state". A practical
method for grading the cognitive state of patients for the clinician.
J Psychiatr Res 1975; 12: 189–98.
Frank MJ, Samanta J, Moustafa AA, Sherman SJ. Hold your horses: im-
pulsivity, deep brain stimulation, and medication in parkinsonism.
Science 2007; 318: 1309–12.
Frank MJ, Seeberger LC, O’Reilly RC. By carrot or by stick:
cognitive reinforcement learning in parkinsonism. Science 2004; 306:
Friston KJ, Williams S, Howard R, Frackowiak RS, Turner R.
Movement-related effects in fMRI time-series. Magn Reson Med
1996; 35: 346–55.
Frosini D, Pesaresi I, Cosottini M, Belmonte G, Rossi C, Dell’Osso L, et al.
Parkinson’s disease and pathological gambling: results from a func-
tional MRI study. Mov Disord 2010; 25: 2449–53.
Gallagher DA, Lees AJ, Schrag A. What are the most important
nonmotor symptoms in patients with Parkinson’s disease and are we
missing them? Mov Disord 2010; 25: 2493–500.
Gallagher DA, Schrag A. Psychosis, apathy, depression and anxiety in
Parkinson’s disease [Review]. Neurobiol Dis 2012; 46: 581–9.
Glascher J. Visualization of group inference data in functional neuroima-
ging. Neuroinformatics 2009; 7: 73–82.
Glimcher PW. Understanding dopamine and reinforcement learning: the
dopamine reward prediction error hypothesis [Review]. Proc Natl Acad
Sci USA 2011; 108 (Suppl 3): 15647–54.
Goetz CG, Fahn S, Martinez-Martin P, Poewe W, Sampaio C,
Stebbins GT, et al. Movement Disorder Society-sponsored revision of
the Uniﬁed Parkinson’s Disease Rating Scale (MDS-UPDRS): process,
format, and clinimetric testing plan. Mov Disord 2007; 22: 41–7.
Goetz CG, Poewe W, Rascol O, Sampaio C, Stebbins GT, Counsell C,
et al. Movement Disorder Society Task Force report on the Hoehn and
Yahr staging scale: status and recommendations. Mov Disord 2004;
Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality.
Neurology 1967; 17: 427–42.
Housden CR, O’Sullivan SS, Joyce EM, Lees AJ, Roiser JP. Intact
reward learning but elevated delay discounting in Parkinson’s
disease patients with impulsive-compulsive spectrum behaviors.
Neuropsychopharmacology 2010; 35: 2155–64.
Jacob EL, Gatto NM, Thompson A, Bordelon Y, Ritz B. Occurrence of
depression and anxiety prior to Parkinson’s disease. Parkinsonism Relat
Disord 2010; 16: 576–81.
Kano O, Ikeda K, Cridebring D, Takazawa T, Yoshii Y, Iwasaki Y.
Neurobiology of depression and anxiety in Parkinson’s disease.
Parkinsons Dis 2011; 2011: 143547.
Kirsch-Darrow L, Fernandez HH, Marsiske M, Okun MS, Bowers D.
Dissociating apathy and depression in Parkinson disease. Neurology
2006; 67: 33–8.
Knutson B, Fong GW, Adams CM, Varner JL, Hommer D. Dissociation of
reward anticipation and outcome with event-related fMRI.
Neuroreport 2001; 12: 3683–7.
Knutson B, Westdorp A, Kaiser E, Hommer D. FMRI visualization of brain
activity during a monetary incentive delay task. Neuroimage 2000; 12:
Kobayakawa M, Koyama S, Mimura M, Kawamura M. Decision
making in Parkinson’s disease: analysis of behavioral and physio-
logical patterns in the Iowa gambling task. Mov Disord 2008; 23:
Kobayakawa M, Tsuruya N, Kawamura M. Sensitivity to reward and
punishment in Parkinson’s disease: an analysis of behavioral patterns
using a modiﬁed version of the Iowa gambling task. Parkinsonism
Relat Disord 2010; 16: 453–7.
Langston JW. The Parkinson’s complex: parkinsonism is just the tip of the
iceberg [Review]. Ann Neurol 2006; 59: 591–6.
Lyons KE, Pahwa R. The impact and management of nonmotor symp-
toms of Parkinson’s disease [Review]. Am J Manag Care 2011; 17
(Suppl 12): S308–14.
Maldjian JA, Laurienti PJ, Kraft RA, Burdette JH. An automated method
neuroanatomic and cytoarchitectonic atlas-based interrogation of
fMRI data sets. Neuroimage 2003; 19: 1233–9.
Miedl SF, Peters J, Buchel C. Altered neural reward representations in
pathological gamblers revealed by delay and probability discounting.
Arch Gen Psychiatry 2012; 69: 177–86.
Mimura M, Oeda R, Kawamura M. Impaired decision-making in
Parkinson’s disease. Parkinsonism Relat Disord 2006; 12: 169–75.
Montague PR, McClure SM, Baldwin PR, Phillips PE, Budygin EA,
Stuber GD, et al. Dynamic gain control of dopamine delivery in
freely moving animals. J Neurosci 2004; 24: 1754–9.
Morrish PK, Sawle GV, Brooks DJ. Regional changes in [18F]dopa me-
tabolism in the striatum in Parkinson’s disease. Brain 1996; 119 (Pt 6):
O’Sullivan SS, Wu K, Politis M, Lawrence AD, Evans AH, Bose SK, et al.
Cue-induced striatal dopamine release in Parkinson’s
1202 | Brain 2013: 136; 1192–1203 J. P. M. van der Vegt et al.
disease-associated impulsive-compulsive behaviours. Brain 2011; 134:
Patton JH, Stanford MS, Barratt ES. Factor structure of the Barratt im-
pulsiveness scale. J Clin Psychol 1995; 51: 768–74.
Perretta JG, Pari G, Beninger RJ. Effects of Parkinson disease on two
putative nondeclarative learning tasks: probabilistic classiﬁcation and
gambling. Cogn Behav Neurol 2005; 18: 185–92.
Pfefferbaum A, Adalsteinsson E, Rohlﬁng T, Sullivan EV. Diffusion tensor
imaging of deep gray matter brain structures: effects of age and iron
concentration. Neurobiol Aging 2010; 31: 482–93.
Reuter J, Raedler T, Rose M, Hand I, Glascher J, Buchel C. Pathological
gambling is linked to reduced activation of the mesolimbic reward
system. Nat Neurosci 2005; 8: 147–8.
Robinson TE, Berridge KC. The neural basis of drug craving: an
incentive-sensitization theory of addiction [Review]. Brain Res Rev
1993; 18: 247–91.
Ross GW, Abbott RD, Petrovitch H, Morens DM, Grandinetti A,
Tung KH, et al. Association of coffee and caffeine intake with the
risk of Parkinson disease. JAMA 2000; 283: 2674–9.
Schonberg T, O’Doherty JP, Joel D, Inzelberg R, Segev Y, Daw ND.
Selective impairment of prediction error signaling in human dorsolateral
but not ventral striatum in Parkinson’s disease patients: evidence from
a model-based fMRI study. Neuroimage 2010; 49: 772–81.
Schott BH, Minuzzi L, Krebs RM, Elmenhorst D, Lang M, Winz OH, et al.
Mesolimbic functional magnetic resonance imaging activations during
reward anticipation correlate with reward-related ventral striatal dopa-
mine release. J Neurosci 2008; 28: 14311–9.
Schott BH, Niehaus L, Wittmann BC, Schutze H, Seidenbecher CI,
Heinze HJ, et al. Ageing and early-stage Parkinson’s disease affect
separable neural mechanisms of mesolimbic reward processing. Brain
2007; 130: 2412–24.
Schultz W. Behavioral dopamine signals [Review]. Trends Neurosci 2007;
Schultz W, Preuschoff K, Camerer C, Hsu M, Fiorillo CD, Tobler PN,
et al. Explicit neural signals reﬂecting reward uncertainty. Philos
Trans R Soc Lond B Biol Sci 2008; 363: 3801–11.
Schwab RS, England AC Jr. Projection techniques for evaluating surgery
in Parkinson’s Disease. Edinburgh: Royal College of Surgeons in
Soh SE, Morris ME, McGinley JL. Determinants of health-related quality
of life in Parkinson’s disease: a systematic review [Review].
Parkinsonism Relat Disord 2011; 17: 1–9.
Steeves TD, Miyasaki J, Zurowski M, Lang AE, Pellecchia G, Van
Eimeren T, et al. Increased striatal dopamine release in Parkinsonian
patients with pathological gambling: a [11C] raclopride PET study.
Brain 2009; 132: 1376–85.
Thiel A, Hilker R, Kessler J, Habedank B, Herholz K, Heiss WD. Activation
of basal ganglia loops in idiopathic Parkinson’s disease: a PET study. J
Neural Transm 2003; 110: 1289–301.
Urban NB, Slifstein M, Meda S, Xu X, Ayoub R, Medina O, et al.
Imaging human reward processing with positron emission tomography
and functional magnetic resonance imaging. Psychopharmacology
(Berl) 2012; 221: 67–77.
van Eimeren T, Ballanger B, Pellecchia G, Miyasaki JM, Lang AE,
Strafella AP. Dopamine agonists diminish value sensitivity of the orbi-
tofrontal cortex: a trigger for pathological gambling in Parkinson’s
disease? Neuropsychopharmacology 2009; 34: 2758–66.
van Eimeren T, Pellecchia G, Cilia R, Ballanger B, Steeves TD, Houle S,
et al. Drug-induced deactivation of inhibitory networks predicts patho-
logical gambling in PD. Neurology 2010; 75: 1711–6.
van Holst RJ, van den Brink W, Veltman DJ, Goudriaan AE. Brain ima-
ging studies in pathological gambling [Review]. Curr Psychiatry Rep
2010; 12: 418–25.
Vilas D, Pont-Sunyer C, Tolosa E. Impulse control disorders in Parkinson’s
disease [Review]. Parkinsonism Relat Disord 2012; 18 (Suppl 1):
Voon V, Mehta AR, Hallett M. Impulse control disorders in Parkinson’s
disease: recent advances [Review]. Curr Opin Neurol 2011; 24:
Voon V, Pessiglione M, Brezing C, Gallea C, Fernandez HH, Dolan RJ,
et al. Mechanisms underlying dopamine-mediated reward bias in com-
pulsive behaviors. Neuron 2010; 65: 135–42.
Weintraub D, Koester J, Potenza MN, Siderowf AD, Stacy M, Voon V,
et al. Impulse control disorders in Parkinson disease: a cross-sectional
study of 3090 patients. Arch Neurol 2010; 67: 589–95.
Wolters E, van der Werf YD, van den Heuvel OA. Parkinson’s
disease-related disorders in the impulsive-compulsive spectrum
[Review]. J Neurol 2008; 255 (Suppl 5): 48–56.
Wu Q, Chen L, Zheng Y, Zhang C, Huang L, Guo W, et al. Cognitive
impairment is common in Parkinson’s disease without dementia in the
early and middle stages in a Han Chinese cohort. Parkinsonism Relat
Disord 2012; 18: 161–5.
Yacubian J, Glascher J, Schroeder K, Sommer T, Braus DF, Buchel C.
Dissociable systems for gain- and loss-related value predictions and
errors of prediction in the human brain. J Neurosci 2006; 26: 9530–7.
Yu RL, Wu RM, Tai CH, Lin CH, Cheng TW, Hua MS.
Neuropsychological proﬁle in patients with early stage of Parkinson’s
disease in Taiwan. Parkinsonism Relat Disord 2012; 18: 1067–72.
Reduced reward sensitivity in PD Brain 2013: 136; 1192–1203 | 1203