Dopaminergic striatal innervation predicts interlimb transfer of a visuomotor skill.
ABSTRACT We investigated whether dopamine influences the rate of adaptation to a visuomotor distortion and the transfer of this learning from the right to the left limb in human subjects. We thus studied patients with Parkinson disease as a putative in vivo model of dopaminergic denervation. Despite normal adaptation rates, patients showed a reduced transfer compared with age-matched healthy controls. The magnitude of the transfer, but not of the adaptation rate, was positively predicted by the values of dopamine-transporter binding of the right caudate and putamen. We conclude that striatal dopaminergic activity plays an important role in the transfer of visuomotor skills.
IstitutiClinicidiPerfezionamento,20126Milano,Italy,3Universita ¨tsklinikWu ¨rzburg,NeurologischeKlinikundPoliklinik,97080Wu ¨rzburg,Germany,
right to the left limb in human subjects. We thus studied patients with Parkinson disease as a putative in vivo model of dopaminergic
denervation. Despite normal adaptation rates, patients showed a reduced transfer compared with age-matched healthy controls. The
Motor learning relies on the intact function of dopaminergic
transmission (Knowlton et al., 1996; Seidler et al., 2006; Seidler
and Noll, 2008; Karabanov et al., 2010). In particular, dopamine
neurons play an important role in coding reinforcement predic-
tion errors, a key signal in many learning models (Sutton and
Barto, 1998; Maia, 2009). Prediction errors are used to learn the
select optimal actions (Sutton and Barto, 1998). At the cellular
and synaptic level, such learning is thought to occur through
long-term changes in synaptic strength at striatal synapses, with
dopamine release as an essential signaling event starting the pro-
cess (Montague et al., 2004; Calabresi et al., 2007).
Adaptation of reaching movements to visuomotor rotation is
while the discrepancy between the desired and the executed tra-
jectory gradually diminished (Krakauer, 2009). Several studies
have suggested a right-hemisphere dominance in the acquisition
of this motor skill (Ghilardi et al., 2000; Huber et al., 2004), but
the role of dopamine and its basal ganglia innervation in visuo-
motor adaptation has been poorly investigated. Previous studies
have shown that adaptation but not retention is normal in pa-
and Sanes, 2011; Venkatakrishnan et al., 2011), but have not
evidence in normal subjects suggests that the striatum plays an
important role in the formation and retrieval of this motor skill
(Ghilardi et al., 2000; Seidler et al., 2006; Seidler and Noll, 2008).
When learning is accomplished with one limb through task
untrained limb can also improve. This process is referred to in-
terlimb transfer and has been shown to apply to visuomotor ad-
aptation (Sainburg and Wang, 2002). Interlimb transfer implies
that the limb-specific motor memory, stored during adaptation,
can be retrieved and applied to the other limb with different
callosum is likely involved in this process (for review, see Hals-
band and Lange, 2006). However, given their important role in
motor learning, dopamine and the striatum could be also in-
volved in such a skill, but their function has not been directly
The aim of this study is to determine whether the adaptation to
visuomotor rotation and its transfer to the untrained hand depend
on dopamine levels. Thus, we investigated the time course of adap-
left hand in drug-naive patients with PD and in age-matched con-
trols. We then correlated the indices of learning and transfer to
range, 38–66 years) and a control group of 10 neurologically intact
adults (three males; median age, 52 years; range, 42–79 years). Median
age of PD patients at motor symptoms onset was 47 years (33–64 years).
rology,UniversityofWu ¨rzburg,Wu ¨rzburg,Germany)forcriticallyreadingthismanuscript.
14458 • TheJournalofNeuroscience,October12,2011 • 31(41):14458–14462
All subjects were right-handed, as assessed by a modified Edinburgh
Brain Bank criteria and patients evaluated with the Unified Parkinson
Disease Rating Scale motor part (UPDRS-III). Two additional UPDRS
sub-subscores were calculated (Isaias et al., 2007). Median UPDRS-III
score was 12 (range, 6–20). Median akinetic-rigid score (UPDRS-AK)
was 5 (range, 2–11) and median UPDRS tremor score (UPDRS-T) was 1
Clinical inclusion criteria for subjects with PD were as follows: (1)
years; (4) Hoehn and Yahr scale, stage 2; (5) drug naive (patients had
never been treated with any antiparkinsonian drugs); (6) no psychiatric
disorders or other neurological diseases other than PD; and (7) absence
of any signs indicative for atypical parkinsonism (e.g., gaze abnormali-
ties, autonomic dysfunction, psychiatric disturbances, etc.).
All subjects (patients and controls) had no cognitive decline as well as
no deficit in visual attention, task switching, memory, or learning strat-
egies, as assessed by the Mini-Mental State examination, Clock Drawing
pan learning task, Corsi Recall, and Trail Making Test (A, B, and A-B).
An MRI was also performed and only subjects with normal results (i.e.,
no sign of white matter lesion or atrophy) were enrolled in the study.
loss of consciousness, epilepsy, brain surgery, systemic illness, or exces-
sive drug or alcohol consumption at any time during their life. Partici-
pants were instructed not to drink any beverages containing caffeine or
alcohol during the 24 h before the experiment. The local institutional
review board approved the study.
Task and experimental design. The motor tasks have been extensively
described in previous papers (Ghilardi et al., 2000; Huber et al., 2004;
Marinelli et al., 2009). Briefly, subjects moved a cursor with their domi-
nant or nondominant hand on a digitizing tablet and performed out-
and-back movements toward one of eight targets presented on the
computer screen every 1.5 s. Vision of both the hand and arm was pre-
vented by an opaque panel, but the position of the cursor on the screen
point and were presented in blocks of 48 (block duration, 72 s). Hand
trajectory was sampled at 200 Hz.
on the screen and the hand position on the tablet corresponded; and a
visuomotor adaptation task (ROT), in which the cursor position on the
screen was rotated 30° counterclockwise to the actual hand movement.
In the main experiment, after familiarization with the apparatus, sub-
jects performed two blocks of baseline condition with each hand; no
ROT with the dominant (right) hand, followed by three blocks of ROT
with the nondominant (left) hand.
Three weeks later, seven patients (six women; median age, 50 years;
58.5 years; range, 42–66 years) were retested, in the same clinical condi-
tions, with one block (48 movements) of the baseline motor task per-
formed with the left hand to assess long-term aftereffects.
first measured the initial planning of the movement direction as direc-
tional error at peak velocity, which is the difference between the target
direction and the movement direction at peak velocity. For each hand,
subtracting the mean error in the corresponding baseline motor task
where no rotation was applied.
We then computed the average percentage adaptation to the applied
distortion for each ROT block as: percentage adaptation ? 100 * (1 ?
tigate the degree of online correction as the absolute difference between
the directional error at peak velocity and that at the reversal point.
To measure the degree of total adaptation achieved with the right
hand, we computed the difference in percentage adaptation between the
ence between the last adaptation block with the right hand and the first
with the left hand for both indices.
well as changes in curvature, by performing a mixed-model ANOVA
(? ? 0.05) on both variables with Group (PD, controls) as the between-
subject factor and Block (1–10) as the within-subject factor.
The between-group differences in the degree of total adaptation
achieved and the difference in curvature, as well as for the interlimb
transfer of both these variables, were assessed using a one-way ANOVA
with Group as main factor.
SPECT data acquisition and reconstruction. SPECT data acquisition
and reconstruction has been described in detail previously (Isaias et al.,
SPECT with FP-CIT. Intravenous administration of 110–185 MBq of
123I-FP-CIT (DaTSCAN; GE Healthcare) was performed 30–40 min af-
ter thyroid blockade (10–15 mg of Lugol solution per os) in all patients.
Data were compared with data from a group of 15 healthy subjects
curvature at an initial level of adaptation (see line 1, top left panel). a, b, Time course of
Isaiasetal.•DopamineandVisuomotorSkillTransferJ.Neurosci.,October12,2011 • 31(41):14458–14462 • 14459
(four males). Brain SPECT was performed 3–4 h later by means of a
with low-energy, ultra-high-resolution fan beam collimators (four sub-
sets of acquisitions; matrix size, 128 ? 128; radius of rotation, 12.9–13.9
cm; continuous rotation; angular sampling, 3°; duration, 28 min) in
patient and control groups. Brain sections were reconstructed with an
iterative algorithm (ordered subset expectation maximization, four iter-
ations and 15 subsets), followed by 3D filtering of sections obtained
(Butterworth, order 5, cutoff 0.31 Ny) and attenuation correction
(Chang method, factor 0.12).
Imaging data processing. The reconstructed images were analyzed for
regionally specific FP-CIT binding using Statistical Parametric Mapping
(SPM2; Wellcome Department of Imaging Neuroscience, London, UK)
in conjunction with MATLAB version R2007a (Mathworks).
First, we created a group-specific123I-FP-CIT SPECT template with
SPM2 by spatially normalizing the FP-CIT images of 15 healthy subjects
the FP-CIT images of all subjects were spatially normalized onto this
FP-CIT template and smoothed with a FWHM 10 mm Gaussian kernel
to increase the signal-to-noise ratio and to account for subtle variations
in anatomic structures. For each individual FP-CIT SPECT image, a
parametric binding ratio image was calculated using the ImCalc toolbox
in SPM. Binding values for each FP-CIT image were computed in a
gion in the occipital cortex was defined using the volume-of-interest of
superior, middle, and inferior occipital gyri and calcarine gyri of the
18F-FP-CIT PET MNI-based template as previously described
Wake Forest University PickAtlas 2.4 software.
Voxelwise statistical analysis. A general linear model was used to per-
subjects. The analysis was applied to SPECT images by means of single-
subject: conditions and covariates design. The PD patients and healthy
acquisition and transfer for both adaptation and curvature. In addition,
we performed a covariance analysis between the transfer scores and FP-
CIT SPECT images. In every analysis, we used no global normalization,
no grand mean scaling, and threshold masking absolute of ?1. For t test
in PD versus healthy controls (HC), p ? 0.001 with false discovery rate
correction was considered significant and for covariance analysis, p ?
0.01 uncorrected was significant, both at clusters of at least 50 voxels. All
coordinates are reported in MNI space.
the Shapiro-Wilks test. Gender distribution among groups was tested
two-group test. A multivariate pairwise correlation analysis was used to
investigate statistical dependence among SPECT binding values demo-
with the JMP statistical package, version 8.0.2 (SAS Institute).
In the first 10 blocks, patients and controls gradually decreased
their directional error at peak velocity and adapted to the imposed
rotation at a similar rate (Block: F(9,171)? 165.52, p ? 0.00001;
0.99; Fig. 1a). The degree of total adaptation achieved was
comparable in patients (44.1% ? 2.7%) and controls (45.7% ?
Both groups showed a similar and significant reduction in
curvature across blocks (Block: F(9,171)? 15.77, p ? 0.00001;
Group: F(1,19)? 0.59, p ? 0.45; Block ? Group: F(9,171)? 0.31,
p ? 0.97; Fig. 1b), further indicating that adaptation indeed re-
The transfer of adaptation to the performance with the left
hand was lower in patients compared with controls (PD: 71.4 ?
the transfer of curvature was similar in the two groups (PD: 2 ?
0.6 vs HC: 1.9 ? 0.6, mean ? SE; F(1,19)? 0.07, p ? 0.80).
aftereffects were significantly larger in controls (?7.49 ? 3.40°)
(?0.29 ? 3.78°; F(1,13)? 15.01; p ? 0.002).
was found between the 3 week aftereffects and right-to-left hand
No correlation was found between behavioral and clinical or
demographic data. In particular, we found no correlations be-
0.64), suggesting that the learning and transfer indices are not
predicted by clinical signs of PD. In addition, transfer of adapta-
tion did not correlate with age (? ? ?0.33, p ? 0.31) or disease
duration (? ? ?0.06, p ? 0.84).
right putamen (x, y, z: 32, 4, ?2). c, d, A volume of interest analysis confirming a positive
CNright CNleftPTright PTleft
14460 • J.Neurosci.,October12,2011 • 31(41):14458–14462 Isaiasetal.•DopamineandVisuomotorSkillTransfer
Binding values are listed in Tables 1 and 2. On average, PD
caudate, 25% in the left caudate, and 32% in both right and left
between left and right striatum.
Whole-brain SPM analysis revealed a selective positive corre-
lation between the transfer of adaptation, but not of curvature,
and DAT binding values of the right caudate and putamen only
(Fig. 2, a and b, respectively). These results were confirmed by a
volume of interest analysis (transfer of adaptation and right cau-
date: ? ? 0.74, p ? 0.01; transfer of adaptation and right puta-
men: ? ? 0.71, p ? 0.01; Fig. 2, c and d, respectively).
No correlation was found between the adaptation rate of the
right hand and DAT binding of any brain areas.
The main result of this study is that the transfer of visuomotor
learning correlated with DAT binding of the right striatum, sug-
gesting, for the first time, that the levels of striatal dopamine
influence the degree of interlimb transfer of a visuomotor skill.
In agreement with previous studies with similar paradigms
(Marinelli et al., 2009; Be ´dard and Sanes, 2011; Venkatakrishnan
et al., 2011) or prism adaptation (Weiner et al., 1983; Stern et al.,
1988), patients with PD adapted their movements to an applied
visual distortion similarly to healthy subjects. This visuomotor
hand path curvature. The decrement of both measures suggests
that adaptation was achieved by the progressive modification of
the motor plan and not by the constant use of online corrections
of the trajectory.
When we tested the left hand, PD patients showed a reduced
ing of the right striatum, but was not predicted by the UPDRS
scores. Therefore, the observed deficit in transfer cannot be as-
cribed to a disease-related motor impairment, but depends on
the dopaminergic innervation itself.
tor rotation is likely to involve both effector-independent and
effector-specific processes. The former consist of the progressive
creation of new mapping between the direction of the hand tra-
jectory and of the target, expressed in visual coordinates and
therefore independent of the characteristics of the actual effector
(i.e., the limb). The latter consist of the selection and implemen-
tation of the appropriate dynamic motor commands that trans-
late the new motor plan into the actual muscle-activation
patterns, which are specific for the effector involved. Training
visuospatial memory, which can be shared by different effectors,
and an effector-specific visuomotor memory. Therefore, we can
assume that interlimb transfer is possible as the untrained hand
can access the newly formed visual mapping. The fact that trans-
the formation of an effector-specific memory is also essential to
both the formation and retrieval of the new visuospatial map, as
well as in the efficient conversion of such a map to the untrained
arm. Of note, the clinical signs in our patients were bilateral and
of comparable severity, as also shown by similar DAT binding
loss in both right and left striatum. Therefore, the reduced inter-
limb transfer should not be ascribed to a differential impairment
of the two limbs. In this and previous studies (Marinelli et al.,
2009), we also found that PD patients display an impairment of
the long-term retention of this visuomotor skill that, in the pres-
ent patient population, is highly correlated with the degree of
of a general deficit in skill formation, retention, and retrieval.
Despite adaptation rates within normal limits, it is possible that
with PD, thus impairing short- and long-term memory pro-
cesses. Accordingly, animal studies suggested a central role of
striatal dopaminergic innervation in skill formation (Graybiel,
1998) and strengthening of synaptic plasticity (Calabresi et al.,
2000; Lovinger et al., 2003).
The correlation found between the magnitude of the transfer
lateralization could be explained by the direction of the transfer,
from the right to the left hand. However, other theories should
consider the right-hemisphere dominancy for this task (Ghilardi
et al., 2000; Huber et al., 2004; Seidler et al., 2008) and for visu-
ospatial abilities in general (Heilman et al., 1986). Future studies
on the transfer in the opposite direction (left hand toward right
task. So far, studies with our task (Ghilardi et al., 2000; Huber et
al., 2004) or similar paradigms (Seidler at al. 2008) showed that
activity in the right-hemisphere, and in particular in the right
parietal cortex, is essential for the formation and the retention of
a new visuospatial mapping. Retrieval of the learned visuospatial
right. It is important to note that this study aimed at specifically
related anatomical network. Future studies will investigate whether
such a transfer relies on transcallosal projections from the cortex
(e.g., right parietal cortex) to the ipsilateral and contralateral stria-
tum, or a direct interstriatal transfer through the anterior commis-
Be ´dard P, Sanes JN (2011) Basal ganglia-dependent processes in recalling
learned visual-motor adaptations. Exp Brain Res 209:385–393.
Calabresi P, Gubellini P, Centonze D, Picconi B, Bernardi G, Chergui K, Sven-
ningsson P, Fienberg AA, Greengard P (2000) Dopamine and cAMP-
CalabresiP,PicconiB,TozziA,DiFilippoM (2007) Dopamine-mediatedreg-
son’s and Alzheimer’s disease. Brain Res 876:112–123.
Graybiel AM (1998) The basal ganglia and chunking of action repertoires.
Neurobiol Learn Mem 70:119–136.
HalsbandU,LangeRK (2006) Motorlearninginman:areviewoffunctional
and clinical studies. J Physiol Paris 99:414–424.
Heilman KM, Bowers D, Valenstein E, Watson RT (1986) The right hemi-
sphere: neuropsychological functions. J Neurosurg 64:693–704.
Huber R, Ghilardi MF, Massimini M, Tononi G (2004) Local sleep and
learning. Nature 430:78–81.
A (2007) [123I]FP-CITstriatalbindinginearlyParkinson’sdiseasepatients
Pezzoli G, Eidelberg D, Antonini A (2010) Imaging essential tremor.
Mov Disord 25:679–686.
Karabanov A, Cervenka S, de Manzano O, Forssberg H, Farde L, Ulle ´n F
U S A 107:7574–7579.
Isaiasetal.•DopamineandVisuomotorSkillTransferJ.Neurosci.,October12,2011 • 31(41):14458–14462 • 14461
Kas A, Payoux P, Habert MO, Malek Z, Cointepas Y, El Fakhri G, Chaumet-
RiffaudP,IttiE,RemyP (2007) Validationofastandardizednormaliza-
tion template for statistical parametric mapping analysis of123I-FP-CIT
images. J Nucl Med 48:1459–1467.
Knowlton BJ, Mangels JA, Squire LR (1996) A neostriatal habit learning
system in humans. Science 273:1399–1402.
Krakauer JW (2009) Motor learning and consolidation: the case of visuo-
motor rotation. Adv Exp Med Biol 629:405–421.
Lovinger DM, Partridge JG, Tang KC (2003) Plastic control of striatal glu-
and targets for drugs of abuse. Ann N Y Acad Sci 1003:226–240.
Ma Y, Dhawan V, Mentis M, Chaly T, Spetsieris PG, Eidelberg D (2002)
Parametric mapping of [18F]FPCIT binding in early stage Parkinson’s
disease: a PET study. Synapse 45:125–133.
Maia TV (2009) Reinforcement learning, conditioning, and the brain: suc-
cesses and challenges. Cogn Affect Behav Neurosci 9:343–364.
Marinelli L, Crupi D, Di Rocco A, Bove M, Eidelberg D, Abbruzzese G,
Ghilardi MF (2009) Learning and consolidation of visuomotor adapta-
tion in Parkinson’s disease. Parkinsonism Relat Disord 15:6–11.
MontaguePR,HymanSE,CohenJD (2004) Computationalrolesfordopa-
mine in behavioural control. Nature 431:760–767.
Sainburg RL, Wang J (2002) Interlimb transfer of visuomotor rotations:
independence of direction and final position information. Exp Brain Res
Seidler RD, Noll DC (2008) Neuroanatomical correlates of motor acquisi-
tion and motor transfer. J Neurophysiol 99:1836–1845.
SeidlerRD,NollDC,ChintalapatiP (2006) Bilateralbasalgangliaactivation
associated with sensorimotor adaptation. Exp Brain Res 175:544–555.
Steiner H, Morgan S, Huston JP (1985) Effect of forebrain commissurot-
omy on recovery from unilateral 6-OHDA lesions of the substantia nigra
and circling induced by apomorphine. Behav Brain Res 17:245–249.
Stern Y, Mayeux R, Hermann A, Rosen J (1988) Prism adaptation in Par-
kinson’s disease. J Neurol Neurosurg Psychiatry 51:1584–1587.
Sutton RS, Barto AG (1998) Reinforcement learning: an introduction.
Cambridge, MA: MIT.
croix N, Mazoyer B, Joliot M (2002) Automated anatomical labeling of
activations in SPM using a macroscopic anatomical parcellation of the
MNI MRI single-subject brain. Neuroimage 15:273–289.
Venkatakrishnan A, Banquet JP, Burnod Y, Contreras-vidal JL (2011) Par-
kinson’s disease differentially affects adaptation to gradual as compared
to sudden visuomotor distortions. Hum Mov Sci 30:760–769.
Weiner MJ, Hallett M, Funkenstein HH (1983) Adaptation to lateral dis-
14462 • J.Neurosci.,October12,2011 • 31(41):14458–14462Isaiasetal.•DopamineandVisuomotorSkillTransfer