A JOURNAL OF NEUROLOGY
Compensatory premotor activity during
affective face processing in subclinical carriers
of a single mutant Parkin allele
Silke Anders,1Benjamin Sack,1Anna Pohl,2,3Thomas Mu ¨nte,1Peter Pramstaller,4Christine Klein1
and Ferdinand Binkofski1,5
1 Department of Neurology, University of Lu ¨beck, 23538 Lu ¨beck, Germany
2 Department of Psychiatry and Psychotherapy, RWTH Aachen University, 52056 Aachen, Germany
3 JARA - Translational Brain Medicine, Germany
4 Centre for Biomedicine, European Academy, 39100 Bolzano, Italy
5 Section for Cognitive Neurology, RWTH Aachen University, 52056 Aachen, Germany
Correspondence to: Silke Anders,
Department of Neurology,
University of Lu ¨beck,
Ratzeburger Alle 160,
23538 Lu ¨beck,
Patients with Parkinson’s disease suffer from significant motor impairments and accompanying cognitive and affective dysfunc-
tion due to progressive disturbances of basal ganglia–cortical gating loops. Parkinson’s disease has a long presymptomatic
stage, which indicates a substantial capacity of the human brain to compensate for dopaminergic nerve degeneration before
clinical manifestation of the disease. Neuroimaging studies provide evidence that increased motor-related cortical activity
can compensate for progressive dopaminergic nerve degeneration in carriers of a single mutant Parkin or PINK1 gene, who
show a mild but significant reduction of dopamine metabolism in the basal ganglia in the complete absence of clinical motor
signs. However, it is currently unknown whether similar compensatory mechanisms are effective in non-motor basal ganglia–
cortical gating loops. Here, we ask whether asymptomatic Parkin mutation carriers show altered patterns of brain activity during
processing of facial gestures, and whether this might compensate for latent facial emotion recognition deficits. Current theories
in social neuroscience assume that execution and perception of facial gestures are linked by a special class of visuomotor
neurons (‘mirror neurons’) in the ventrolateral premotor cortex/pars opercularis of the inferior frontal gyrus (Brodmann area
44/6). We hypothesized that asymptomatic Parkin mutation carriers would show increased activity in this area during processing
of affective facial gestures, replicating the compensatory motor effects that have previously been observed in these individuals.
Additionally, Parkin mutation carriers might show altered activity in other basal ganglia–cortical gating loops. Eight asymptom-
atic heterozygous Parkin mutation carriers and eight matched controls underwent functional magnetic resonance imaging and
a subsequent facial emotion recognition task. As predicted, Parkin mutation carriers showed significantly stronger activity in
the right ventrolateral premotor cortex during execution and perception of affective facial gestures than healthy controls.
Furthermore, Parkin mutation carriers showed a slightly reduced ability to recognize facial emotions that was least severe in
individuals who showed the strongest increase of ventrolateral premotor activity. In addition, Parkin mutation carriers showed a
significantly weaker than normal increase of activity in the left lateral orbitofrontal cortex (inferior frontal gyrus pars orbitalis,
Brodmann area 47), which was unrelated to facial emotion recognition ability. These findings are consistent with the hypothesis
doi:10.1093/brain/aws040 Brain 2012: 135; 1128–1140 |
Received July 26, 2011. Revised December 14, 2011. Accepted December 23, 2011. Advance Access publication March 20, 2012
? The Author (2012). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0),
which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
that compensatory activity in the ventrolateral premotor cortex during processing of affective facial gestures can reduce im-
pairments in facial emotion recognition in subclinical Parkin mutation carriers. A breakdown of this compensatory mechanism
might lead to the impairment of facial expressivity and facial emotion recognition observed in manifest Parkinson’s disease.
Keywords: Parkinson’s disease; functional MRI; emotional facial expression; mirror neurons; functional reorganization
Abbreviation: OFC = orbitofrontal cortex
Progressive loss of dopaminergic nerve cells in the substantia
nigra leads to Parkinson’s disease, a common neurodegenerative
disorder. In addition to a characteristic triad of motor symptoms,
patients with Parkinson’s disease often show cognitive and affect-
ive impairments. In particular, a reduced ability to decode facial
expressions of emotion has been reported in a number of studies
(Gray and Tickle-Degnen, 2010).
bradykinesia) are a result of imbalance of neural activity in basal
ganglia–thalamocortical motor gating loops, caused by loss of dopa-
minergic nerve cells in the pars compacta of the substantia nigra and
subsequent nerve degeneration in the putamen. However, in add-
ition to the well-described motor loops, the basal ganglia have nu-
merous interconnections with other cortical areas (Alexander et al.,
1986, 1990; Lehericy et al., 2004; DeLong and Wichmann, 2007,
Parkinson’s disease have often been ascribed todisturbances in ‘cog-
nitive’ or ‘limbic’ basal ganglia–cortical gating loops (Holthoff-Detto
et al., 1997; Sprengelmeyer et al., 2003; Clark et al., 2008; van
Beilen et al., 2008; Gray and Tickle-Degnen, 2010), but the patho-
physiology underlying cognitive and affective dysfunction in
Parkinson’s disease is still not well understood.
Parkinson’s disease has a long and not well-defined presympto-
matic course of disease. Based on PET with
it has been estimated that first characteristic motor signs become
apparent ?5 years after onset of the pathophysiological process,
when dopamine metabolism in the basal ganglia is reduced by
30–50% (Morrish et al., 1996; Hilker et al., 2005). This long
presymptomatic period in Parkinson’s disease suggests that the
human motor system has a substantial capacity to compensate
for loss of nigrostriatal dopaminergic nerve cells. Empirical support
for this assumption comes from functional MRI studies in individ-
uals who carry a single mutation in the Parkin (PARK2) or in the
PINK1 (PARK6) gene. Mutations in these genes are a common
cause of early-onset Parkinson’s disease (Klein et al., 2007).
While heterozygous carriers of a single Parkin or PINK1 mutation
are usually free of clinical motor symptoms, it is now well estab-
lished that these asymptomatic mutation carriers show a signifi-
cant reduction of18F-fluoro- L-DOPA metabolism in the putamen
(Hilker et al., 2001, 2002; Khan et al., 2002, 2005; Scherfler
et al., 2004; Pavese et al., 2009; Guo et al., 2011). Two recent
functional MRI studies have indicated that asymptomatic Parkin
and PINK1 mutation carriers show a stronger increase of cortical
motor-related activity during execution of self-initiated move-
ments than non-mutation carriers (Buhmann et al., 2005;
van Nuenen et al., 2009a). This stronger than normal increase
in cortical activity and concomitant changes in functional connect-
ivity in the motor system have been interpreted as evidence for
a large-scale reorganization of the motor system in the presymp-
tomatic stage of Parkinson’s disease (Buhmann et al., 2005;
Schneider et al., 2008; van Nuenen et al., 2009a, b). Whether
similar compensatory mechanisms are effective in non-motor basal
ganglia–cortical gating loops is currently unknown.
Here, we examine whether asymptomatic Parkin mutation
carriers show altered patterns of brain activity during processing
of facial gestures, and whether such altered patterns of brain
activity can compensate for latent deficits in facial emotion recog-
nition. Current theories in cognitive neuroscience suggest that
motor execution and action perception are strongly linked by a
special class of visuomotor neurons, so-called ‘mirror neurons’.
Mirror neurons, defined by their property to fire not only during
motor execution, but also during action perception, were first
described in the premotor cortex F5 of the macaque Macaca
nemestrina (di Pelligrino et al., 1992). Overlapping activity
during action execution and action observation in functional MRI
studies has subsequently been taken as evidence that homologue
mirror neuron areas exist in the human brain (Iacoboni et al.,
1999; Shmuelof and Zohary, 2006; Gazzola and Keysers, 2009;
Schippers et al., 2009). In particular, it has been suggested that
mirror neurons in the ventrolateral premotor cortex in the pars
opercularis of the inferior frontal gyrus link execution and percep-
tion of facial gestures and thereby help a receiver to decode
another person’s facial expression (Carr et al., 2003; Leslie
et al., 2004; Hennenlotter et al., 2005; van der Gaag et al.,
2007). In Parkinson’s disease, a reduced ability to decode facial
expressions is almost always associated with reduced facial expres-
sivity, and there are observations that indicate a positive relation
between reduced expressivity and facial emotion recognition
deficits (Jacobs et al., 1995). In sum, these findings could point
to a common cause behind reduced facial expressivity and facial
emotion recognition deficits in Parkinson’s disease.
In the current study, we asked whether asymptomatic carriers of
a single mutant Parkin gene would show a stronger than normal
increase of activity in ventrolateral premotor cortex during execution
and observation of facial gestures, mirroring the stronger than
normal increase of motor-related activity observed in Parkin and
PINK1 mutation carriers during execution of self-initiated finger
movements. Furthermore, we examined whether the strength of
activity in ventrolateral prefrontal cortex would be positively corre-
lated with the participants’ ability to decode facial emotional expres-
sions. In other words, we tested whether those Parkin mutation
carriers who show a strong increase of ventrolateral premotor
Compensatory brain activity in Parkin mutation carriersBrain 2012: 135; 1128–1140 |
activity during processing of facial gestures would show less impair-
ment in facial emotion recognition than those Parkin mutation car-
riers who show weaker ventrolateral premotor activity. This would
speak for a beneficial effect of stronger than normal ventrolateral
premotor activity on facial emotion recognition in Parkin mutation
carriers. Finally, we explored whether Parkin mutation carriers
would show altered brain activity in limbic and/or higher cognitive
areas associated with affective processing. Such a finding could
point towards compensatory
‘cognitive’ basal ganglia–thalamocortical gating loops.
Materials and methods
Eight asymptomatic individuals with a single mutation in one allele of
the Parkin gene participated in the study (four males, four females;
age range 35–50 years; mean age of males 43 years, mean age of
females 46 years). Mutation carriers were recruited from a large family
(Family LA) from the German-spoken part of northern Italy (Tyrol)
with familial adult-onset parkinsonism caused by mutations in the
Parkin gene. Four individuals had a deletion of exon 7 and four indi-
viduals carried a 1-bp deletion in exon 9. Details of the genetic analysis
of the core branch of Family LA have been described elsewhere (Klein
et al., 2000). Six of the mutation carriers had previously undergone
PET, showing a small but statistically significant decrease of18F-fluoro-
L-DOPA uptake in the putamen as reported above (Hilker et al., 2001,
2002). All Parkin mutation carriers scored within the normal range on
all subscales of the Unified Parkinson Disease Rating Scale [UPDRS I/II
(cognitive function/daily activities) range 0–1, mean 0.5; UPDRS III
(motor abilities) range 0–5, mean 2.25] and the Beck Depression
Inventory (Beck, 1961) (range 0–8, mean 1.875). An overview of clin-
ical data of all Parkin mutation carriers is given in Table 1.
A group of eight age- and sex-matched healthy individuals (four
males, four females; age range 35–55 years; mean age of males
44.25 years, mean age of females 46.75 years) recruited from
Lu ¨beck and the surrounding area were examined as controls.
Functional MRI data of two healthy participants (one male, one
female) were discarded because one participant showed large head
movements during scanning (410mm) and the other reported that
observing and executing the facial expressions elicited subjective ex-
perience of other emotions than joy (see below). Functional MRI data
of these two participants were replaced with functional MRI data from
two additional age- and sex-matched control participants.
All participants were native German speakers, had normal or
corrected-to-normal vision and no history of neurological or neuro-
psychiatric disease; none reported to have received any dopaminergic
or anti-parkinsonian drug treatment. All participants gave their written
informed consent before participation and the study was approved by
the local ethics committee (University of Lu ¨beck, Germany).
Overview of design
To compare processing of facial gestures in Parkin mutation carriers
and healthy controls at the behavioural and cerebral level, we con-
ducted a behavioural emotion recognition test and a functional
MRI experiment. The behavioural test required participants to name
blends of emotional facial expressions in a forced-choice paradigm. In
the functional MRI experiment, participants were asked to execute
and observe neutral and affective dynamic facial expressions, but no
explicit emotion recognition was required. This way, we could assess
emotion recognition ability and brain activity independently. We also
intended to manipulate facial expressivity and pleasantness independ-
ently by including a highly positive expressive facial gesture (a smile)
along with a slightly positive gesture (a lip protrusion indicating a kiss).
However, post-scan joy ratings indicated that participants experienced
‘kiss’ gestures as equally joyful as ‘smile’ gestures, thus these
two conditions were fused to one condition (see below). Results
of the behavioural task will be reported first although all participants
underwent functionalMRI scanning
To measure the participants’ ability to decode emotions from
facial expressions, we used a set of facial stimuli taken from the Facial
Expression of Emotions: Stimuli and Test (FEEST; Young et al., 2002).
Each stimulus of this set is a computer-transformed blend (‘morph’) of
two different, ‘neighbouring’, emotional facial expressions of one actor
‘J.J’. The set includes five different blends (90–10%, 70–30%, 50–50%,
30–70%, 10–90%) for each pair of neighbouring emotions in the series
surprise–fear–sadness–disgust–anger–happiness–surprise, giving a total
of 30 different stimuli. Stimuli were presented on a computer screen
with five replications in randomized order, giving a total of 150 trials.
During each trial, participants were asked to choose the emotion that
best described the facial expression on the screen from a set of six target
emotions (surprise, fear, sadness, disgust, anger and happiness). Written
German labels (‘U¨berraschung’, ‘Furcht’, ‘Trauer’, ‘Ekel’, ‘Wut’ and
‘Freude’) for these six emotions were provided throughout the ex-
periment next to each other at the bottom of the computer screen in a
pseudorandomized order that was balanced across participants.
Participants indicated their choice by verbally naming the selected emo-
tion. Participants were asked to respond quickly, and each facial expres-
sion disappeared after 5s, but there was no upper limit of response time.
Choices were entered into a computer by a lab member (B.S.) the next
face appeared immediately after the response was given. Stimuli were
presented in five runs with a short break in between. Data collection was
preceded by 30 test trials to familiarize participants with the task. Both
90–10% (‘clear-cut’) and 70–30% (‘fuzzy’) morphs were included in the
analyses, and a response was defined as ‘correct’ if the label chosen by
morph and as ‘incorrect’ otherwise. Thus, a total of 10 trials were derived
for each emotion at either level of difficulty.
Table 1 Overview of clinical data of Parkin mutation
Code SexAgeMutation UPDRSIIIBDI
BDI = Beck Depression Inventory; F = female; M = male; UPDRSIII = Unified
Parkinson Disease Rating Scale, subscale motor abilities.
Brain 2012: 135; 1128–1140 S. Anders et al.
Functional magnetic resonance imaging
For the functional MRI experiment, short video clips of different facial
gestures wereused asstimuli.Video clips wererecorded from24actors in
an in-house multi-media centre (RWTH Aachen University, Germany).
Actors were filmed in portrait format, including their head and shoulders
but nottheir arms, in front of a greybackground with a commercial video
camera (Sony DVX 2000, spatial resolution 720 ? 576 pixels). The
actors’ hair was fixed and covered with a black scarf. For each video
clip, the actor was asked to relax, then to express a facial gesture for
3s (indicated by a visual sign by a lab member), and then to relax
again. After recording, video clips were cut such that each sequence
started ?1s before onset of the facial gesture and terminated ?1s
after offset of the facial gesture, resulting in a total length of 5s for
each video clip. Each actor produced several instances of six affective
facial expressions (surprise, fear, sadness, disgust, anger and happiness)
and a number of communicative and meaningless facial gestures (lip,
cheek and eye movements). After recording, all videos were categorized
according to facial gesture by 30 naive observers. Three types of gestures
were selected for the current study: ‘smile’ (the actor showing a smile),
‘kiss’ (the actor showing a lip protrusion) and ‘neutral’ (the actor showing
a relaxed expression). Only positive facial gestures were selected in order
to keep stress for the participants during scanning as low as possible. For
each of the 24 actors, the most accurate expression of each category was
selected (i.e. the video with the highest recognition rate by the naive
observers), giving a total of 72 videos. In addition to these 72 original
video clips, a scrambled version was produced of each clip by random-
ization of down-sampled pixels (1/40 of the original resolution) of the
foreground of each frame (i.e. the actor’s head and shoulder). In
the resulting video clips, the shape of the actor was retrieved, but the
facial gesture was no longer visible (Fig. 1).
The functional MRI experiment was designed in a 2 ? 3 factorial
design, the first factor being the participant’s task [the participant
was either asked to express a given facial gesture (‘do’) or to observe
the facial gesture shown by the actor (‘view’)] and the second factor
being the type of facial gesture (neutral, kiss or smile) that was to
be executed or observed. Video clips were presented in blocks of
four 5-s video clips of the same experimental condition (do-neutral,
do-kiss, do-smile, view-neutral, view-kiss, or view-smile), giving six
20-s blocks for each experimental condition. These blocks were pre-
sented with a stimulus onset asynchrony of 28.8s (corresponding to
12 scans), thus each block was followed by a 8.8s baseline (black
fixation cross on grey background). Blocks of videos were presented
in randomized order. After every sixth video block an additional 33.6s
baseline (corresponding to 14 scans) was inserted. Scanning was
divided in two runs, each lasting ?10min, with a short break in
between (Fig. 1).
Participants were instructed to execute a facial gesture (‘do’) when-
ever they saw a scrambled video and to attentively watch the actor
(‘view’) whenever they saw an unscrambled video. Scrambled (rather
than unscrambled) videos were used in the ‘do’ condition in order to
clearly separate brain activity associated with the execution of a facial
gesture from brain activity associated with the perception of a facial
gesture. A coloured fixation cross (blue, red or green) superimposed
on the actor’s scrambled face from 1s after video onset to 1s before
video offset indicated the participant which facial gesture (neutral, kiss
or smile) they were to execute.
After scanning, participants were asked to rate how much joy they
had experienced during each condition on a visual analogue scale
(1, not at all, to 7, very intense). Additionally, participants were
asked to indicate if they had experienced any other emotion than
joy during any condition.
Two hundred and sixty-two echo-planar T2*-weighted images (EPI, 33
horizontal slices, tilt angle ?30?, slice thickness 3 + 1mm gap, in
plane resolution 3 ? 3mm2, echo time 30ms, repetition time 2.4s)
were acquired with a 3.0T scanner (Philips) during each functional
imaging run. Functional imaging was preceded by 16 functional
scans not included in the analysis to allow for T1saturation and par-
ticipant habituation. Additionally, a T1-weighted anatomical image
Figure 1 Design of the functional MRI study. The bar at the bottom represents one experimental run. Each participant underwent two
runs. Colours indicate the six experimental conditions (green, do-smile; light green, view-smile; red, do-kiss; light red, view-kiss; blue,
do-neutral; light blue, view-neutral). Note that ‘smile’ and ‘kiss’ conditions were fused in the analysis (see text).
Compensatory brain activity in Parkin mutation carriers Brain 2012: 135; 1128–1140 |
(magnetization-prepared rapid acquisition gradient echo, 1-mm iso-
tropic voxels) was acquired from each participant that was used for
spatial normalization of individual data.
Analysis of functional magnetic
resonance imaging and behavioural data
Functional MRI data were analysed with SPM5 (The Wellcome
Department ofImaging Neuroscience,
University College London, UK) following a standard procedure.
Pre-processing included slice acquisition time correction, concurrent
spatial realignment and unwarping concurrent spatial realignment
and correction of image distortions (Anderson et al., 2001), normal-
izationinto standard anatomical
Institute, 3-mm isotropic voxels) and spatial smoothing (8-mm
A linear model that accounted for first-order autocorrelations and
low-frequency drifts (high pass cut off period 600s) was used to
estimate blood oxygen level-dependent signal amplitudes during
each experimental condition for each participant. Each block was mod-
elled as box car function (representing the full length of a video
block, 20s) convolved with a standard canonical haemodynamic
response function as implemented in SPM5. Condition-wise averaging
of the estimated parameter maps resulted in six parameter maps for
each participant, one for each experimental condition (do-neutral,
do-kiss, do-smile, view-neutral, view-kiss, view-smile). Since joy rat-
ings in Parkin mutation carriers and controls did not differ for ‘kiss’
and ‘smile’ gestures (see ‘Results’ section), parameter estimates for
‘kiss’ and ‘smile’ were averaged to one stimulus condition (positive
facial gestures), separately for ‘do’ and ‘view’ conditions. The resulting
four parameter maps for each participant (do-neutral, do-positive,
view-neutral, view-positive) were used for group analysis.
A 2 ? 2 ? 2 ANOVA with between-subject factor group and
within-subject factors task (‘do’ or ‘view’) and type of facial gesture
(‘neutral’ or ‘positive’) was used for group analysis. Unequal variance
was assumed for all conditions.
space (Montreal Neurological
First, we wanted to test whether the experimental paradigm used
in the current study reliably reproduced patterns of brain activity
reported in previous studies. In particular, we wanted to test whether
both execution and observation of facial gestures reliably activated
putative mirror neuron areas in the ventrolateral premotor cortex.
For this purpose, we used a conjunction analysis across ‘do’ and
‘view’ contrasts, which tests the logical AND, i.e. the null hypothesis
that any of the two contrasts (‘do’ or ‘view’) does not show an effect.
In other words, for an effect to be significant at the conjoint level it
has to be significant in each and every contrast (‘conjoint’ conjunction
in SPM terminology, Nichols et al., 2005). For this initial analysis, we
combined data across all participants (i.e. group statistics were com-
puted across Parkin mutation carriers and controls neglecting any pos-
and (iii) ‘do-positive-minus-neutral’ AND ‘view-positive-minus-neutral’.
Next, we searched for brain activity that was significantly altered
during processing of facial gestures in Parkin mutation carriers relative
to controls. For this, we used a conjunction analysis that tests the null
hypothesis that both contrasts show no effect. Since in this analysis it
is assumed that all contrasts included in the conjunction show
consistent effects, for the conjoint effect to be significant all contrasts
have to survive a threshold that decreases with the power of the
number of contrasts included (‘global’ conjunction in SPM termin-
ology, Friston et al., 2005). Although some authors have argued
that this conjunction tests a less stringent hypothesis than the ‘con-
joint’ conjunction (Nichols et al., 2005), we opted for this analysis for
the group comparison because a ‘global’ conjunction is more sensitive
than a ‘conjoint’ conjunction analysis (Friston et al., 2005). Since we
assumed unequal variance across conditions, the global conjunction
analysis required that ‘do’ and ‘view’ contrasts were orthogonalized
relative to one another. All ‘do’ contrasts were orthogonalized relative
to ‘view’ contrasts because we reasoned that any effects in visuomotor
regions (our main hypothesis) would be stronger for ‘do’ than for
‘view’ contrasts (Leslie et al., 2004). Three global conjunctions were
computed: (i) ‘parkin-do-neutral’ versus ‘controls-do-neutral’ AND
‘parkin-view-neutral’ versus ‘controls-view-neutral’; (ii) ‘parkin-do-
versus ‘controls-view-positive’; and (iii) ‘parkin-do-positive-minus-neu-
tral’ versus ‘controls-do-positive-minus-neutral’ AND ‘parkin-view-
positive-minus-neutral’ versus ‘controls-view-positive-minus-neutral’.
All group comparisons were computed in both directions, i.e.
increased or decreased activity in Parkin mutation carriers relative to
controls. To test our main hypothesis that Parkin mutation carriers
show stronger than normal increase of activity in the right ventrolat-
eral premotor cortex, we used a false discovery rate (Genovese et al.,
2002) of P = 0.05 within a region of interest that included the pars
opercularis of the right inferior frontal gyrus as defined by the auto-
mated anatomic labelling (AAL, Tzourio-Mazoyer et al., 2002) Atlas.
A false discovery rate of P = 0.05 for the whole brain was used to
assess statistical significance of altered brain activity outside the right
inferior frontal gyrus pars opercularis.
Finally, we were interested whether the level of activity in any brain
region that showed altered brain activity during facial gesture process-
ing in Parkin mutation carriers relative to controls would be positively
correlated with an individual’s ability to decode emotional facial
expressions. This would provide evidence that an increased (or
decreased) level of activity in the respective region facilitates
decoding of facial emotional expressions. To test this, we extracted
parameter estimates for each condition and participant (do-neutral,
do-positive, view-neutral, view-positive) from the peak of each acti-
vated cluster and fused them to one contrast for each participant
(positive-minus-neutral). Two different types of regression analyses
were performed. First, we asked whether there was a relation be-
tween activity in a given region and each participant’s ability to
decode emotional facial expressions. To ensure that correlations
would not simply be due to differences between groups, group aver-
ages were removed from the data in this analysis. Secondly, we asked
whether the relation between activity and emotion recognition abil-
ity would be altered in Parkin mutation carriers. In order to test this,
we performed separate regression analyses for the two groups and
tested whether the slope of regression would differ between groups
(please note that for this analysis it is irrelevant whether group differ-
ences are removed). In addition to the regression analysis with emo-
tion recognition data, we performed similar regression analyses for
post-scan joy ratings. For this, we fused post-scan joy ratings to a
single value for each participant that corresponded to the contrast of
brain activity used for the correlation analysis activity (‘positive-
Brain 2012: 135; 1128–1140S. Anders et al.
Both controls and Parkin mutation carriers showed above-chance
emotion recognition accuracy for both clear-cut (90–10%) and
fuzzy (70–30%) morphed emotional facial expressions (Fig. 2;
clear-cut morphs, controls 85% correct, Parkin mutation carriers
84% correct; fuzzy morphs, controls 82% correct, mutation car-
riers 76% correct; chance 16%). There was no overall statistically
significant difference between Parkin mutation carriers and con-
trols [T(14) = ?0.7], but Parkin mutation carriers showed a sig-
nificantly greater decline from clear-cut to fuzzy emotional
expressionthan controls[T(14) = 2.0,
A 2 ? 2 ? 6 ANOVA with between-subject factor group and
within-subjects factors difficulty (clear-cut versus fuzzy morphs)
and type of emotion did not reveal a significant group-by-
level-by-emotioninteraction[F(5,70) = 1.3,
Parkin mutation carriers showed a particular impairment for
fuzzy facial expression that was not limited to any specific
P = 0.03, one-tailed].
P = 0.30].Thus,
First, we asked whether the six experimental conditions elicited
similar joy responses in Parkin mutation carriers and controls at
the subjective level and found that this was the case. Pair-wise
group comparisons of post-scan joy ratings revealed no significant
differences between Parkin mutation carriers and controls for any
condition [F(1,14]54.0, P40.05 for all pair-wise comparisons,
Fig. 3]. This was confirmed by a 2 ? 2 ? 3 ANOVA with factors
group, task and type of facial gesture that revealed no significant
main effect of group [F(1,14] = 0.7, P40.30], no significant
group-by-facial gesture interaction [F(1,14] = 1.0, P40.30] and
[F(1,14] = 0.8, P40.30]. Thus, Parkin mutation carriers did not
differ from controls in how much joy they experienced during the
different experimental conditions.
Next, we tested whether the three different types of facial ges-
tures (neutral, kiss, smile) elicited the intended increasing joy
responses in both groups. Both groups showed the expected
significant increase in joy ratings from ‘neutral’ to ‘kiss’ gestures
T(7) = 3.4,
T(7) = 2.0, P = 0.04], but there was no additional increase in joy
ratings from ‘kiss’ to ‘smile’ facial gestures [Parkin mutation car-
riers, T(7) = ?0.8; controls, T(7) = 1.5, P = 0.09]. Due to this lack
of significant differences in joy ratings for the two positive facial
gestures, we fused functional MRI data for the ‘kiss’ and ‘smile’
P = 0.006;controls,
Figure 2 Facial emotion recognition in controls and Parkin mutation carriers. (A) Average emotion recognition rates did not differ
significantly between Parkin mutation carriers and controls; however, mutation carriers showed a significantly larger decrease in emotion
recognition from clear-cut (90–10%) to fuzzy (70–30%) morphs. (B) There was no significant group ? level ? emotion interaction,
indicating that the slight impairment of Parkin mutation carriers was not limited to any specific emotion. The asterisk indicates a significant
effect (*P50.05); n.s = not significant. Parkin MC = Parkin mutation carriers.
Figure 3 Post-scan joy ratings. Parkin mutation carriers did not
differ significantly from controls in self-reported joy in any
Compensatory brain activity in Parkin mutation carriersBrain 2012: 135; 1128–1140 |
conditions to two conditions (do-positive and view-positive) (see
As intended, data fusion led to significant differences between
the resulting types of facial gestures in both groups [Parkin
mutation carriers, T(7) = 4.0, P = 0.003; controls, T(7) = 2.9,
P = 0.01, note that these comparisons do not constitute valid stat-
istics and T- and P-values are reported for descriptive purposes
only]. Importantly, joy ratings remained very similar across
groups, i.e. no significant pair-wise differences between groups,
P40.10for all pair-wise comparisons],no
significant main effect of group [F(1,14) = 0.8, P40.30], no sig-
nificant group-by-facial gesture
P40.50] and no significant group-by-task-by-facial gesture inter-
action in a 2 ? 2 ? 2 ANOVA [F(1,14) = 0.4, P40.50].
interaction [F(1,14) = 0.3,
Common brain activity during execution
and observation of facial gestures
Next, we wanted to test whether the experimental paradigm used
in the current study reliably reproduced patterns of brain activity
Figure 4 Common BOLD activity during execution and observation of facial gestures in all participants. Statistical parametric maps for
execution of facial gestures and for observation of facial gestures were individually thresholded at a false discovery rate of 0.05 (corrected
for the whole volume) and inclusively masked such that only voxels are highlighted that show significant activity in both conditions. Only
clusters that comprise at least 10 voxels in both contrasts are shown. IFG = inferior frontal gyrus; Put = putamen; STS = superior temporal
sulcus; TPJ = temporoparietal junction.
Table 2 Common brain activity during execution and observation of positive versus neutral facial gestures in all participants
Location of clusterCoordinates at peak T-value at peakCluster size (k)Percentage of voxels per anatomical structure
Temporoparietal junction L
?60 ?42 24 4.28840
Superior temporal gyrus La
Supramarginal gyrus L
Middle temporal gyrus L
Inferior parietal gyrus L
Inferior frontal gyrus, pars opercularis L
Inferior frontal gyrus, pars orbitalis La
Inferior frontal gyrus, pars opercularis R
Rolandic operculum Ra
Superior temporal gyrus Ra
Supramarginal gyrus R
Frontoinsular cortex L
?36 18 ?3 4.378
Frontoinsular cortex R63 9 94.1 26
Temporoparietal junction R66 ?42 214.216
Basal ganglia R 24 0 9 4.2 14
Ordering of clusters is by size. Anatomical structures are labelled with the AAL atlas (Tzourio-Mazoyer et al., 2002). Statistical parametric maps for execution of facial
gestures and for observation of facial gestures were individually thresholded at a false discovery rate of 0.05 (corrected for the whole volume) and inclusively masked such
that only voxels are highlighted that show significant activity in both conditions. Listed are clusters that comprise at least 10 voxels in both contrasts and anatomical
structures that contain at least 10% of all voxels in a cluster. Coordinates are in MNI space.
a The anatomical structure that contains the highest activated voxel.
L = left hemisphere; R = right hemisphere.
Brain 2012: 135; 1128–1140 S. Anders et al.
reported in previous studies. For this initial analysis, we neglected
possible group differences and treated all participants as belonging
to a single group. Processing of neutral facial gestures (versus
baseline) led to significant activity in a large cluster that comprised
lateral and medial occipito-temporal cortex in both hemispheres
(Fig. 4). Processing of positive facial gestures (versus baseline)
additionally activated two large fronto-temporal clusters that com-
prised prefrontal, premotor, insular and anterior temporal cortex,
part of the basal ganglia and the amygdala. In addition, three
smaller lateral parieto-temporal clusters and two smaller frontome-
dial clusters were observed, comprising supplementary motor and
premotor cortex (Fig. 4). Direct comparison of positive and neutral
facial gestures revealed stronger activity during processing of posi-
tive facial gestures in bilateral inferior frontal cortex, extending
into the insula and orbitofrontal cortex in the left hemisphere,
and extending into the precentral gyrus and rolandic operculum
in the right hemisphere. Additionally, this comparison revealed
stronger activity during processing of positive facial gestures in
the left and right temporoparietal junction and in the basal ganglia
(Fig. 4 and Table 2).
Altered brain activity in Parkin
Having ensured that our experimental paradigm reliably repro-
duced the pattern of overlapping activity during execution and
observation of facial gestures reported in previous studies, we
proceeded to search for altered brain activity in Parkin mutation
carriers relative to controls. As predicted, a region-of-interest ana-
lysis of the pars opercularis of the right inferior frontal gyrus
revealed a significantly stronger than normal increase of brain
activity in Parkin mutation carriers during processing of positive
facial gestures in this area [inferior frontal gyrus pars opercularis,
Brodmann area 44/6, x = 60, y = 15, z = 6, T(14) = 2.9/2.2
(T execution/observation), conjoint cluster size k = 20, Fig. 5].
No other stronger than normal increase of brain activity was
observed in Parkin mutation carriers. The reverse comparison re-
vealed a significantly weaker than normal increase of brain activity
in Parkin mutation carriers in the right fusiform gyrus during pro-
cessing of neutral facial gestures [Brodmann area 18/19, ? = 21,
y = ?78, z = ?15, T(14) = 4.3/3.7, conjoint cluster size k = 7;
Fig. 5. Note that this activity was not predicted and is reported
for completeness only] and in the left lateral orbitofrontal cortex
during processing of positive versus neutral facial gestures [inferior
frontal gyrus pars orbitalis, Brodmann area 47, x = ?42, y = 30,
z = ?18, T(14) = 3.4/3.4, conjoint cluster size k = 3, Fig. 5].
Parameter estimates in the ventrolateral premotor cortex and the
lateral orbitofrontal cortex indicate similar levels of activity during
execution and observation within either group (Fig. 5).
Correlation between altered brain
activity and emotion recognition ability/
Finally, we asked whether altered brain activity in Parkin mutation
carriers would be linked to an individual’s ability to decode
Figure 5 Altered BOLD activity during processing of facial gestures in Parkin mutation carriers relative to controls. For visualization,
conjoint statistical parametric maps for execution and observation of facial gestures are thresholded at a voxel-wise height threshold
of P = 0.005, but only clusters are shown whose most significantly activated voxel does not exceed a false discovery rate of 0.05
(see text). The histogram at the bottom of each panel shows activity at the most significantly activated voxel in each map. Red
bars = controls; green bars = Parkin mutation carriers; filled bars = positive facial expressions; open bars = neutral facial expressions. Error
bars indicate standard error of the mean. FFG = fusiform gyrus; IFG op = inferior frontal gyrus, pars opercularis; ORB = inferior frontal
gyrus, pars orbitalis.
Compensatory brain activity in Parkin mutation carriersBrain 2012: 135; 1128–1140 |
emotional facial expressions. In this analysis, we focused on the
two spots in the ventrolateral premotor cortex and the lateral
orbitofrontal cortex, respectively, that showed altered activity in
Parkin mutation carriers. We found a significant positive correl-
ation between brain activity (‘positive-minus-neutral’) and emo-
tion recognition scores across all participants in the ventrolateral
premotor cortex [r = 0.52, T(1,13) = 2.3, P = 0.02, Fig. 6A].
Notably, separate regression analyses for Parkin mutation carriers
and controls revealed a significantly flatter slope of regression be-
tween inferior premotor activity and emotion recognition scores
in Parkin mutation carriers than in controls [Parkin mutation car-
riers, slope = 0.8, controls slope = 2.3, T(1,12) = ?1.8, P = 0.04;
Fig. 6C]. In other words, individuals in the Parkin group had to
produce a greater increase in brain activity in the ventrolateral
premotor cortex in order to gain a similar increase in facial recog-
nition ability as individuals in the control group. No significant
correlation between brain activity and emotion recognition
scores was observed in the lateral orbitofrontal cortex (r = 0.01,
not significant, Fig. 6B and D). To test for the possibility that
lateral orbitofrontal activity was more closely related to affective
evaluation of facial gestures than to physical decoding, we also
correlated brain activity (‘positive-minus-neutral’) in the ventrolat-
eral premotor cortex and the lateral orbitofrontal cortex with
post-scan joy ratings (‘positive-minus-neutral’). In the ventrolateral
premotor cortex, we found no correlation between brain activity
and post-scan joy ratings (r = ?0.40, not significant; Fig. 6E and
G). However, there was a significant positive correlation between
brain activity and post-scan joy ratings across all participants in the
lateral orbitofrontal cortex [r = 0.54, T(1,13) = 2.4, P = 0.02;
Fig. 6F]. The slope of regression between lateral orbitofrontal
activity and post-scan joy ratings was similar in Parkin mutation
carriers and controls [Parkin mutation carriers, slope = 1.4, controls
slope = 3.0, T(1,12) = ?0.8, not significant; Fig. 6H].
The current study investigated facial emotion recognition ability
and brain activity during processing of facial gestures in asymp-
tomatic Parkin mutation carriers relative to controls. As predicted,
Figure 6 Correlation of BOLD activity and facial emotion recognition ability/self-reported joy. (A and B) Overall correlation between
BOLD activity and facial emotion recognition accuracy in all participants (group differences are removed from BOLD and behavioural
data). (C and D) Slope between BOLD activity and facial emotion recognition accuracy in controls (red squares) and Parkin mutation
carriers (green circles). Projections of the group means (indicated by the plus) on the x- and y-axes, respectively, indicate the group mean
of BOLD/behavioural data. (E and F) Overall correlation between BOLD activity and post-scan joy ratings in all participants (group
differences are removed from BOLD and behavioural data). (G and H) Slope between BOLD activity and post-scan joy ratings in controls
(red squares) and Parkin mutation carriers (green circles). Projections of the group means (indicated by the plus) on the x- and y-axes,
respectively, indicate the group mean of BOLD/behavioural data. X-axes represent the contrast of parameter estimates
‘positive-minus-neutral’, averaged across ‘do’ and ‘view’. Y-axes represent emotion recognition scores for fuzzy morphs (70–30%)/post-
scan joy ratings (scale 1–7, ‘positive-minus-neutral’, see text), averaged across ‘do’ and ‘view’. Asterisks indicate a significant correlation
(A, B, E and F) or a significant difference between slopes for controls and Parkin mutation carriers (C, D, G and H).
Brain 2012: 135; 1128–1140 S. Anders et al.
Parkin mutation carriers were slightly impaired in facial emotion rec-
ognition. This slight impairment did not seem to be limited to any
particular facial expression. Furthermore, Parkin mutation carriers
showed a stronger than normal increase of activity in the right ven-
trolateral premotor cortex (inferior frontal gyrus pars opercularis,
Brodmann area 44/6) pars opercularis of the right inferior frontal
gyrus (inferior frontal gyrus pars opercularis, Brodmann area 44/6)
during processing of affective facial gestures, whereby a stronger
increase in inferior frontal gyrus pars opercularis activity during pro-
cessing of facial gestures predicted less impairment at the behav-
ioural level. In addition, mutation carriers showed a weaker than
normal increase of activity during facial emotion processing in the
left lateral orbitofrontal cortex (inferior frontal gyrus pars orbitalis,
Brodmann area 47), which was unrelated to facial emotion recogni-
tion ability. This suggests that compensatory activity in putative
human mirror neuron areas during processing of affective facial ges-
tures might have a beneficial effect on facial emotion recognition
ability in subclinical Parkin mutation carriers.
The ventrolateral premotor cortex
The pars opercularis of the inferior frontal gyrus forms part of the
human ventrolateral premotor cortex and is thought to be homo-
logue to monkey premotor area F5, that part of the monkey
cortex where ‘mirror neurons’ were first detected (di Pelligrino
etal., 1992). Overlapping blood
(BOLD) activity in this area during imitation/production and
mere observation of facial expressions in functional MRI studies
in humans has been interpreted as evidence that similar visuo-
motor ‘mirror neurons’ exist in the human brain (Carr et al.,
2003; Leslie et al., 2004; Hennenlotter et al., 2005; van der
Gaag et al., 2007), and that these neurons might not only be
involved in action understanding, but also in decoding of facial
expressions (Adolphs et al., 2000; Gallese, 2003; Decetey and
Jackson, 2004; Baastiansen et al., 2009; Iacoboni, 2009). In line
with these studies, we found a significant overlap of BOLD activity
during execution and observation of affective facial gestures in
bilateral ventrolateral premotor cortex in our participants.
In line with our hypothesis, direct comparison of asymptomatic
Parkin mutation carriers and healthy controls revealed that activ-
ity in this area was significantly enhanced during processing of
affective facial gestures in Parkin mutation carriers. This provides
evidence that compensatory mechanisms in asymptomatic Parkin
mutation carriers are not limited to motor-related activity asso-
ciated with finger movements (Buhmann et al., 2005; van
Nuenen et al., 2009a), but extend to ventrolateral premotor
activity associated with facial gestures. Importantly, a stronger
than normal increase of activity in this area in Parkin mutation
carriers was not only observed during execution, but also during
observation of affective facial gestures. This suggests that similar
compensatory mechanisms might be effective during execution
and perception of facial gestures and thereby supports ‘mirror
neuron’ theories of facial gesture processing (see Jacobs et al.,
1995 for an early related account).
The second important finding of the current study is the positive
correlation between ventrolateral premotor activity and emotion
recognition ability across participants. Notably, this positive
relation was observed even though brain activity was measured
during processing of positive facial expressions only, while emotion
recognition scores reflected an individual’s ability to identify a
large range of different emotions. This suggests that increased
neural activity in the ventrolateral premotor cortex during facial
gesture processing indeed facilitates facial emotion recognition.
Importantly, however, the slope of regression between ventrolat-
eral premotor activity and emotion recognition ability was flatter in
Parkin mutation carriers than in controls. This means that individ-
uals in the Parkin group had to produce a greater increase in brain
activity in the ventrolateral premotor cortex, or, to ‘work harder’,
in order to gain a similar increase in facial recognition accuracy as
individuals in the control group.
The lateral orbitofrontal cortex
In addition to the stronger than normal increase of activity in
the right ventrolateral premotor cortex, Parkin mutation car-
riers showed a significantly weaker than normal increase of activity
during processing of affective facial gestures in the left lat-
eral orbitofrontal cortex (inferior frontal gyrus pars orbitalis/
Brodmann area 47). Although activity in this region is sometimes
(Sprengelmeyer et al., 1998; Wildgruber et al., 2004; Ethofer
et al., 2009; Lotze et al., 2009) this region appears to be primarily
involved invalue representation
(Kringelbach and Rolls, 2004). In line with this interpretation we
found a positive correlation between lateral orbitofrontal activity
and the participants’ joy ratings, but not with their ability to
decode facial emotional expressions.
Interestingly, three previous studies have reported reduced grey
matter or altered neural activity in patients with Parkinson’s disease
in clustersremarkablyclose tothepeakofweakerthannormallateral
orbitofrontal activity in the current study (Le Jeune et al., 2008:
x = ?36, y = 31, z = ?5; Ibarretxe-Bilbao et al., 2009: x = ?36,
y = 40, z = ?18; Lotze et al., 2009: x = ?54, y = 24, z = ?9; cur-
rent study: x = ?42, y = 30, z = ?18). Only the first of these studies
(Le Jeune et al., 2008) found a positive relation between lateral
orbitofrontal activity (glucose metabolism measured with PET) and
facial emotion recognition in patients with Parkinson’s disease. The
other twostudies assessedrecognition of emotional gestures, but did
not find a significant correlation between BOLD activity during ob-
servation of emotional gestures and emotional gesture recognition
ability (Lotze et al., 2009) or grey matter volume and facial emotion
recognition ability (Ibarretxe-Bilbao et al., 2009; note, however, that
these authors report a positive correlation between grey matter loss
in more distributed regions of the orbitofrontal cortex and emotion
recognition impairment). Thus, orbitofrontal grey matter and neural
activity seem to be altered in Parkinson’s disease but these changes
might not have a direct impact on social emotion recognition ability
in these patients.
of affective social signals
Two different compensatory
The pattern of findings described above raises the question why
Parkin mutation carriers show stronger than normal activity in the
Compensatory brain activity in Parkin mutation carriers Brain 2012: 135; 1128–1140 |
right ventrolateral premotor cortex (where activity was positively
linked to emotion recognition ability), but weaker than normal
activity in left orbitofrontal cortex (where activity was positively
linked to self-reported joy). One matter that makes it difficult to
tackle this question is the fact that the non-motor loops that con-
nect the basal ganglia with human prefrontal cortex are consider-
ably less well understood than basal ganglia–cortical motor loops.
Brodmann area 44/monkey area F5—is generally assumed to be
part of the motor basal-ganglia cortical gating loop (DeLong and
Wichmann, 2007) that projects from premotor, motor and som-
atosensory cortex via the putamen back to the supplemental
motor area (Alexander et al., 1986). The stronger than normal
activity in the inferior frontal gyrus pars opercularis in the current
study can thus be interpreted as a compensatory response caused
by nerve degeneration in the putamen.
The situation is less clear for the orbitofrontal cortex. This is
partly due to the fact that most current knowledge about
cortico-basal ganglia–cortical gating loops stems from studies in
non-human primates (or even rodents) and that human orbito-
frontal cortex—and particularly Brodmann area 47 where weaker
than normal activity was observed in the current study—cannot
easily be mapped onto monkey prefrontal cortex (Kringelbach and
Rolls, 2004). This area has been discussed to be part of at least
two alternative cortico-basal ganglia–cortical gating loops. Lotze
et al. (2009) suggested that this area forms part of the ‘lateral
orbitofrontal gating loop’ described by Alexander et al. (1986)
that receives input from the lateral orbitofrontal cortex and super-
ior and inferior temporal cortex and projects, via the head of the
caudate nucleus, back to the inferior frontal gyrus pars orbitalis.
This assumption is supported by a diffusion tensor imaging study
in healthy human participants, which found anatomical connec-
tions from the anterior putamen/head of the caudate nucleus to
Brodmann area 47 (Lehericy et al., 2004). Alternatively, as pointed
out by Kringelbach and Rolls (2004), Brodmann area 47 might be
part of a cortical area that in fact is homologue to medial orbito-
frontal cortex in monkeys. If this was true, then this area might be
part of the ‘anterior cingulate gating loop’ of Alexander et al.
(1986). This loop receives inputs from medial prefrontal, enthor-
inal, perirhinal and temporo-polar cortex as well as the amygdala
and hippocampus and projects, via the ventral striatum, back to
medial prefrontal cortex. Interestingly, behavioural studies have
often ascribed emotion recognition deficits in Parkinson’s disease
to this latter loop (which is often referred to as ‘mesolimbic gating
loop’) (e.g. Sprengelmeyer et al., 2003; Clark et al., 2008;
Gray and Tickle-Degnen, 2010). Both the caudate nucleus and
the ventralstriatum have been
Parkinson’s disease (e.g. Morrish et al., 1996; Hilker et al.,
2001; Kumajura et al., 2010), but the current study does not
permit to directly link one of these basal ganglia sites to the
observed weaker than normal activity in the lateral orbitofrontal
It is possible that non-motor basal ganglia–cortical gating loops
have less capacity to compensate for dopaminergic nerve degen-
eration than motor basal ganglia–cortical gating loops. Thus,
reduced (rather than amplified) lateral orbitofrontal activation
might be observed already at very early stages of the disease.
found to beaffected in
Another intriguing possibility is that dopaminergic imbalance
leads to heightened (rather than diminished) sensitivity in the
‘mesolimbic gating loop’ early in the disease and that the lower
level of inferior frontal gyrus pars orbitalis activation in Parkin
mutation carriers is in fact a compensatory response to such heigh-
tened sensitivity. In line with this reasoning, a recent PET study
demonstrated that dopaminergic activity of the ‘mesolimbic’
system is heightened, rather than diminished, at least in some
stages of Parkinson’s disease (Kumakura et al., 2010), and there
is first evidence that heightened amygdala activity resulting from
deep brain stimulation in the substantia nigra can have a detri-
mental effect on facial emotion recognition (Le Jeune et al.,
2008). However, this evidence is clearly still very limited and
further studies a needed to examine these questions in more
The current study demonstrates altered processing of affective
facial gestures in asymptomatic Parkin mutation carriers at the
behavioural and cerebral level and thereby extends previous stu-
dies that have shown altered motor-related activity in these indi-
viduals. However, the current study also shares some limitations
with previous studies that used asymptomatic mutation carriers as
a human model for presymptomatic Parkinson’s disease. First, all
Parkin mutation carriers investigated in the current study were
members of one family living in a rural area in northern Italy.
To keep logistical effort reasonable, other studies have used a
similar approach (Hilker et al., 2001, 2002; Khan et al., 2002,
2005; Scherfler et al., 2004; Buhmann et al., 2005). However,
until findings from these and the current study have been repli-
cated in a larger sample, including individuals from different
pedigrees, the possibility remains that the altered pattern of
cerebral processing observed in those and the current study
did not result from the gene mutations in question, but from
some other genetic or environmental factors shared by all mu-
tation carriers in a particular study. Secondly, altered patterns of
brain activity in the current study could not be directly linked to
altered dopamine metabolism in circumscribed nodes of the
basal ganglia. Current developments in PET technology and
data analysis permit detailed investigations of dopamine metab-
olism at high spatial resolution (e.g. Kumakura et al., 2010).
Future studies should aim to integrate these techniques with
functional MRI in the same individuals to examine the neuro-
biological processes underlying altered patterns of cerebral pro-
cessing in the presymptomatic and clinical stages of Parkinson’s
disease in more detail.
The current study provides evidence for altered processing of
affective facialgestures in the
Parkinson’s disease. Most importantly, our findings demonstrate
for the first time a link between increased activity in the ventro-
lateral premotor cortex (inferior frontal gyrus pars opercularis,
Brodmann area 44/6) and facial emotion recognition ability in
Brain 2012: 135; 1128–1140 S. Anders et al.
these individuals and thereby provide direct evidence for a com-
pensatory effect of increased ventrolateral premotor activity on
facial emotion recognition deficits. A breakdown of this mechan-
ism might lead to the impairment of facial expressivity and facial
emotion recognition observed in manifest Parkinson’s disease. In
addition, we observed significantly weaker than normal activity in
Parkin mutation carriers in lateral orbitofrontal cortex (inferior
frontal gyrus pars opercularis, Brodmann area 47), an area that
is probably associated with stimulus evaluation and value repre-
sentation. Further studies combining PET and functional MRI are
needed to track the neurobiological processes underlying these
changes in cortical activity.
The authors thank Christian Erdmann for assistance with scanning,
Jana Heussen and Jan Hu ¨lle for help with acquisition of behav-
ioural data, and Norbert Bru ¨ggemann for taking care of clinical
Bundesministerium fu ¨r Bildung und Forschung (Federal Ministry of
Education and Research, Grant
and 01GQ1105 to S.A.); Deutsche Forschungsgemeinschaft,
Sonderforschungsbereich 654, A11 (German Research Council,
Special Research Area 654, A11) to S.A. and F.B. Volkswagen
Foundation (career development awards to C.K.); Hermann and
Lilly Schilling Foundation (career development awards to C.K.).
01GW0751, 01GW0752 to F.B.
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