Download Modification of Practice-dependent Plasticity in Human Motor Cortex

Cerebral Cortex August 2006;16:1106--1115
doi:10.1093/cercor/bhj052
Advance Access publication October 12, 2005
Modification of Practice-dependent
Plasticity in Human Motor Cortex by
Neuromodulators
Frank Meintzschel and Ulf Ziemann
Practice-dependent plasticity underlies motor learning in everyday
life and motor relearning after lesions of the nervous system.
Previous studies showed that practice-dependent plasticity is
modifiable by neuromodulating transmitters such as norepinephrine
(NE), dopamine (DA) or acetylcholine (ACh). Here we explored, for
the first time comprehensively and systematically, the modifying
effects of an agonist versus antagonist in each of these neuromodulating transmitter systems on practice-dependent plasticity in
healthy subjects in a placebo-controlled, randomized, double-blind
crossover design. We found that the agonists in all three neuromodulating transmitter systems (NE: methylphenidate; DA: cabergoline; ACh: tacrine) enhanced practice-dependent plasticity,
whereas the antagonists decreased it (NE: prazosin; DA: haloperidol;
ACh: biperiden). Enhancement of plasticity under methylphenidate
and tacrine was associated with an increase in corticomotoneuronal
excitability of the prime mover of the practice, as measured by the
motor evoked potential amplitude, but with a decrease under
cabergoline. Our findings demonstrate that agonists and antagonists in various neuromodulating transmitter systems produce
significant and oppositely directed modifications of practicedependent plasticity in human motor cortex. Enhancement of
plasticity occurred through different strategies that either favoured
extrinsic (NE, ACh) or intrinsic (DA) modulating influence on the
motor cortical output network.
ergic system disrupt cortical map reorganization and impair
motor skill acquisition (Conner et al., 2003).
In humans, practice-dependent motor cortical plasticity can
be studied non-invasively by various transcranial magnetic
stimulation (TMS) protocols (Classen and Cohen, 2003). One
particularly well-established protocol included subjects in
whom it was possible to induce with focal TMS of one motor
cortex isolated thumb movements of the contralateral hand
pointing consistently into one direction. If subjects then
practiced brisk thumb movements into the opposite direction,
thumb movements induced by TMS shifted into the direction
of the trained movements after the end of practice (Classen
et al., 1998). This suggested rapid changes in the cortical
representation of the thumb, which encode kinematic details
of the practiced movement and may reflect a first step towards
skill acquisition. This form of practice-dependent plasticity
is significantly reduced by dextromethorphan, an N-methyl-Daspartate (NMDA) receptor blocker, and by lorazepam, a positive
allosteric modulator of the GABAA receptor (Bütefisch et al.,
2000), suggesting that long-term potentiation like mechanisms
are involved. Several previous studies already tested the effects
of single drugs affecting neuromodulating neurotransmission
on this form of practice-dependent plasticity. It was found that
d-amphetamine, an indirect agonist of NE, DA and serotonin,
and levodopa, a precursor of DA enhanced practice-dependent
plasticity (Bütefisch et al., 2002; Sawaki et al., 2002b; Floel
et al., 2005a) while the antiadrenergic a1 receptor antagonist
prazosin (Sawaki et al., 2003) and the anticholinergic nonselective muscarinic receptor antagonist scopolamine (Sawaki
et al., 2002a) reduced it. These reports suggest that neuromodulating transmitters exert controlling influence on practicedependent plasticity in human motor cortex. However, no
study has systematically tested agonists versus antagonists in
the same neuromodulating transmitter system. Therefore, the
major aim of the present study was to explore the effects of
one agonist versus one antagonist in the NE (methylphenidate
versus prazosin), DA (cabergoline versus haloperidol) and ACh
system (tacrine versus biperiden) on practice-dependent motor
cortical plasticity of healthy subjects in a placebo-controlled,
randomized and double-blind crossover study design.
It is likely that the results of this study are pertinent to
practice-dependent plasticity in clinical settings like motor
relearning during stroke rehabilitation (Goldstein, 1998). The
few available studies suggest a beneficial role of NE and DA
agonists but the evidence is rather anecdotal due to small
patient sample sizes (Crisostomo et al., 1988; Grade et al., 1998;
Walker-Batson et al., 1995, 2001; Scheidtmann et al., 2001) and
not unanimous (Treig et al., 2003). One recent study showed
that a single oral dose of levodopa enhanced practice-dependent
Keywords: acetylcholine, human motor cortex, monoamines,
practice-dependent plasticity, transcranial magnetic stimulation
Introduction
Pyramidal neurons in the cerebral cortex transmit information
largely via the excitatory neurotransmitter glutamate along
intrinsic and cortico-cortical connections. Excitation is controlled by feedforward and feedback inhibition, mediated
by inhibitory interneurons via the neurotransmitter gammaaminobutyric acid (GABA). In addition, cortical function is
strongly influenced by neuromodulating transmitters like
norepinephrine (NE), dopamine (DA) or acetylcholine (ACh).
These systems have in common that their axons originate from
nuclei in the brainstem and project to all regions and layers of
cortex (Cooper et al., 2002). While broad evidence exists on
profound effects of neuromodulating transmitters on excitability and plasticity in sensory cortices (Gu, 2002) their effects on
motor cortex have been studied less extensively. The motor
cortex is a highly modifiable structure (Sanes and Donoghue,
2000) and repeated practice or skill learning are associated with
substantial representational plasticity (Pascual-Leone et al.,
1995; Nudo et al., 1996; Kleim et al., 1998; Liepert et al.,
1999). ACh is important for practice-dependent motor cortical
plasticity in rats because lesions of the basal forebrain cholin The Author 2005. Published by Oxford University Press. All rights reserved.
For permissions, please e-mail: [email protected]
Motor Cortex Laboratory, Department of Neurology,
J.W. Goethe-University Frankfurt, Schleusenweg 2--16,
D-60528 Frankfurt am Main, Germany
plasticity in chronic stroke patients when examined in the
present thumb movement practice protocol (Floel et al.,
2005b).
Materials and Methods
Subjects
Eight healthy right-handed subjects (mean age 25.5 ± 4.6 years, six
women) were included into the study. All subjects gave written
informed consent, and the study was approved by the local ethics
committee of the JW Goethe University hospital of Frankfurt, Germany.
All experiments conformed to the Declaration of Helsinki. Altogether 40
subjects were initially screened but only the eight subjects selected for
this study fulfilled all electrophysiological inclusion criteria (resting
motor threshold < 50% of maximum stimulator output, isolated and
consistent thumb movement elicited by TMS). The inclusion criteria
were more extensive (threshold criterion) and more strict (quantified
consistency criterion of TMS evoked thumb movements, see below for
details) than in previous experiments (Classen et al., 1998; Bütefisch
et al., 2000, 2002). This explains the lower inclusion rate in this study
(20%) compared with the other studies (45--83%).
Recording and Stimulation
Subjects were seated in a comfortable chair. Their dominant right arm
was adducted in the shoulder, 90 flexed in the elbow, and the semipronated forearm, the wrist and the four long fingers were immobilized
in a cast while the thumb was entirely unconstrained (Fig. 1A). Thumb
movements were recorded by two uni-axial accelerometers (Model
2256A-100, voltage sensitivity 100 mV/g, Endevco Corp., San Juan
Capistrano, CA) that were mounted on the proximal phalanx of the
thumb in orthogonal planes to detect acceleration in the abduction-adduction and extension--flexion axes, respectively (Fig. 1A). The raw
signal was amplified (Model 133 signal conditioner, Endevco), digitized
(A/D rate, 4 kHz, Micro 1401, Cambridge Electronic Design, Cambridge,
UK) and bandpass filtered (0.05--70 Hz, Spike 2 software, Cambridge
Electronic Design). In addition, electromyography (EMG) was recorded
by bipolar Ag--AgCl surface electrodes from two thumb muscles, the
abductor pollicis brevis (APB) and the flexor pollicis brevis (FPB)
(Fig. 1A). The EMG raw signal was amplified and bandpass filtered
(0.5--2 kHz, Counterpoint Mk2 Electromyograph, Dantec, 2740
Skovlunde, Denmark) and digitized (A/D rate 4 kHz, Micro 1401).
Digitized signals were fed into a laboratory computer for online visual
display and offline analysis, using customized Spike 2 software.
TMS of the hand area of the left primary motor cortex was achieved
by means of a figure-of-eight stimulating coil (outer diameter of each
wing, 90 mm) connected to a Magstim 200 magnetic stimulator with a
monophasic current waveform (The Magstim Company Ltd, Carmarthenshire, UK). The coil was held tangential to the scalp with the handle
pointing backwards and ~45 away from the midline. This is the optimal
orientation for activating the corticospinal system transsynaptically via
horizontal cortico-cortical connections (Di Lazzaro et al., 2004).
Time Line of an Experimental Session
The stimulating coil was moved in 1 cm steps around the suspected site
of the hand area of the left motor cortex to define the stimulation site
that produced consistently largest motor evoked potentials (MEPs) in
the APB and FPB of the right hand. Then resting motor threshold (RMT)
was determined at this site in decremental steps of 1% maximum
stimulator output. RMT was defined as the minimum stimulus intensity
that elicited MEPs >50 lV in the APB in at least 5 of 10 consecutive trials
(Rossini et al., 1999). Subjects had to meet an RMT < 50% of the
maximum stimulator output to be eligible for further testing because
higher thresholds indicate insufficient accessibility of the hand area of
the motor cortex by TMS. If a subject was tested for the first time,
additional inclusion criteria were checked in the next step: one
Figure 1. (A) Experimental set-up. (B) Time line of experiments.
Cerebral Cortex August 2006, V 16 N 8 1107
requirement was that it had to be possible to evoke isolated thumb
movements by TMS without overt movements of any of the other digits,
wrist or arm; the other requirement was that the direction of TMSinduced thumb movements was sufficiently consistent (Bütefisch et al.,
2000). Consistency was tested before drug intake (PRE1, Fig. 1B) by
obtaining 40 TMS-induced thumb movements (inter-trial interval, 10 s).
Acceleration vectors were constructed from the first-peak acceleration
measured by the two accelerometers in the orthogonal axes of
abduction--adduction and extension--flexion. All acceleration vectors
were then assigned a length of 1 in a unity circle defined by the
abduction--adduction and extension--flexion axes. Dispersion of the
TMS-induced thumb movement vectors is then given by the length of
the mean vector, and the requirement of sufficient consistency was
fulfilled if the dispersion was >0.7.
Immediately after PRE1, the subject took one of the seven study
drugs (see below). Two hours later, another block of 40 trials of TMSinduced thumb movements was obtained (PRE2, Fig. 1B). PRE2 served
as the baseline for calculation of practice-dependent plasticity during
(comparison of measurements D1--D5 with PRE2) and after the end
of practice (comparison of measurements P1--P6 with PRE2), and to
analyse whether there were any drug effects on TMS-induced thumb
movements before practice (comparison between PRE2 and PRE1).
Motor practice consisted of six blocks of 300 thumb movements each,
paced by a metronome at a rate of 1 Hz (duration of each block, 5 min).
Subjects were instructed to perform phasic thumb movements as fast
and brief as possible into the direction exactly opposite to (i.e. 180
away from) the direction of the mean vector of TMS-induced thumb
movements obtained during PRE2. These six practice blocks (T1--T6,
Fig. 1B) were interspersed with five blocks of TMS-induced thumb
movements (D1--D5), each consisting of 10 trials (inter-trial interval,
10 s) in order to obtain information on how fast practice-dependent
plasticity developed during practice. After the end of practice, another
6 blocks of TMS-induced thumb movements (P1--P6) were recorded,
each block consisting of 20 trials (inter-trial interval, 10 s), in order to
obtain information on the duration of practice-dependent plasticity
for the first 30 min after the end of practice (Fig. 1B).
All recordings of TMS-induced thumb movements were obtained
during full voluntary relaxation that was monitored by continuous
audio-visual EMG feedback at high gain (50 lV/D). Trials that were
contaminated by EMG activity were rejected online and discarded from
further analysis.
Analysis of Kinematic and MEP Data
Final analysis of the accelerometer data was performed offline by
programs written by one of the authors (U.Z.) in Matlab Version 6.1.0.
(The MathWorks, Inc., Natick, MA). TMS-induced thumb movements
during PRE1 and PRE2 were analysed by amplitude (length of the mean
acceleration vector, in m/s2) and dispersion (see above). Voluntary
thumb movements during motor practice were recorded by accelerometry during all blocks of practice (T1--T6, Fig. 1B). From these data
practice performance was evaluated by analysing amplitude (length
of the mean acceleration vector across all blocks of practice T1--T6, in
m/s2), dispersion and angle deviation of the mean vector of voluntary
thumb movements from the mean vector of TMS-induced thumb
movements during PRE2 (DPHI, in degrees). Practice-dependent
plasticity was analysed in two ways: (i) increase of the percentage of
TMS-induced thumb movements into the training target zone (TTZ),
which was defined by a zone of ±30 around the direction of the mean
acceleration vector of practiced thumb movements (Classen et al.,
1998; Bütefisch et al., 2000); and (ii) angle deviation of the mean vector
of TMS-induced thumb movements during (D1--D5) and after motor
practice (P1--P6) from the mean vector of TMS-induced thumb movements during baseline (PRE2). This angle deviation was normalized to
DPHI, i.e. the angle deviation defined by the comparison of mean vectors
of practice and PRE2 (wPHI, weighted PHI). A wPHI value of 1 would
therefore indicate that the mean vector of TMS-induced thumb movements at a given time point during or after practice was exactly in the
direction of the mean training vector. wPHI has the potential advantage
of detecting also small practice effects that are missed by the percentage
increase into the TTZ.
MEP amplitudes (in mV) of APB and FPB were analysed peak-to-peak
in the single trials and averages were calculated for baseline (PRE2) and
1108 Neuromodulation of Motor Plasticity
d
Meintzschel and Ziemann
all time points during (D1--D5) and after motor practice (P1--P6). Since
five subjects practiced thumb movements mainly in adduction-flexion
direction (sometimes in abduction--flexion direction), and 1 subject
practiced in abduction-extension direction, it was possible to assign to
each subject either the FPB (five subjects) or the APB (one subject) as
the prime mover muscle of the practice. Changes in MEP amplitude in
this prime mover muscle associated with practice were expressed by
normalizing MEP amplitudes during and after practice to MEP amplitude
during baseline (PRE2). It was not possible to classify one muscle as an
agonist and the other one as an antagonist of the practiced movement
due to significant volume conduction between these adjacent muscles,
and because, in some instances (practice in abduction--flexion direction), both muscles served as agonists of the practice.
Experimental Design
The drug effects on practice-dependent plasticity were tested in
a placebo-controlled, randomized and double-blind crossover design.
Each subject was tested for all six study drugs and placebo in different
sessions. Each drug was applied as a single oral dose. The minimum
interval between consecutive sessions in a given subject was one week
to avoid interaction between drugs or sessions. Main modes of action,
doses and pharmacokinetics of the study drugs are given in Table 1. The
single oral doses equalled typical daily doses for treatment of patients,
and/or have already demonstrated efficacy in previous TMS experiments
to alter motor cortical excitability or plasticity (Table 1).
Statistics
Differences between drugs regarding kinematics (amplitude, dispersion)
of TMS-induced thumb movements at baseline (PRE2) were evaluated
by one-way repeated-measures analyses of variance (ANOVAs), with
Drug as within-subject factor. Drug effects on kinematics (amplitude,
dispersion) of TMS-induced thumb movements were evaluated by
subjecting the differences between PRE2 and PRE1 to a one-way
repeated-measures ANOVA with Drug as within-subject factor. Differences between drugs regarding the training performance (amplitude,
dispersion and DPHI of the mean training vector) were analysed by oneway repeated-measures ANOVAs with Drug as within-subject factor.
Drug effects on practice-dependent plasticity (percentage increase into
TTZ, weighted PHI) were analysed by two-way repeated-measures
ANOVAs with Drug (7 levels) and Time (11 levels) as within-subject
factors. Additional two-way repeated-measures ANOVAs explored drug
effects restricted to time points during practice (D1--D5), or after end of
practice (P1--P6). Post hoc tests were conducted in case of significant
main effects. In case of a significant main effect of Drug, post-hoc tests
were restricted to compare practice-dependent plasticity under each
study drug with practice-dependent plasticity under placebo. The
Fisher’s protected least significant difference (PLSD) test was used to
correct for multiple comparisons. The relationship between MEP
amplitude in the prime mover muscle of the practice and the magnitude
of practice-dependent plasticity was assessed separately for each drug
by regression analysis. For all tests, significance was assumed if P < 0.05.
All statistics were computed with StatView for Windows (SAS Institute
Inc., Version 5.0.1).
Table 1
Study drugs
Drug
Placebo (PBO)
Prazosin (PRZ)
Main mode(s)
of action
a1 receptor antagonist
(NE antagonist)
Methylphenidate Indirect NE (and DA)
(MPH)
agonist
Haloperidol (HAL) D2 receptor antagonist
Cabergoline (CAB) D2 receptor agonist
Biperiden (BIP)
Tacrine (TAC)
Dose (mg) Plasma
peak (h)
Previous TMS
studies
1 mg
2
Sawaki et al. (2003)
40 mg
2
Ilic et al. (2003)
2.5 mg
2 mg
M1 receptor antagonist 8 mg
(ACh antagonist)
Acetylcholinesterase
40 mg
inhibitor (ACh agonist)
2--6
Ziemann et al. (1997)
2 (0.5--4) Unpublished own
observations
1.5
Unpublished own
observations
1.5
Korchounov et al. (2005)
Results
Two out of eight subjects dropped out of the study due to
adverse drug effects (both subjects experienced nausea and
vomiting under BIP). The remaining six subject tolerated the
drugs well and were capable of fully complying with all aspects
of the experiments. All reported data are based on these six
subjects.
RMT and Stimulus Intensities Used for TMS-induced
Thumb Movements
There was no difference between Drugs with respect to RMT
before drug intake [F (6,30) = 0.91, P = 0.50]. The grand mean
of RMT across all sessions and subjects was 42.7 ± 5.3% of
maximum stimulator output. There was also no difference
between Drugs with respect to the TMS intensity used to
induce thumb movements before drug intake [F (6,30) = 1.15,
P = 0.36]. The grand mean of TMS intensity across all sessions
and subjects was 47.3 ± 6.2% of maximum stimulator output.
RMT and TMS intensity remained unchanged 2 h after drug
intake (PRE2). Therefore, there were no differences between
Drugs in stimulus intensity that could have accounted for
the dissociating drug effects on practice-dependent plasticity
(see below).
Characteristics of TMS-induced Thumb Movements
before Training
Grand averages across all drugs of TMS-induced thumb movements at time point PRE2 (before training) revealed a mean
dispersion of 0.83 ± 0.06 and a mean percentage into the TTZ of
1.2 ± 2.8%, indicating that these movements were consistent
into one direction and that movements into the TTZ only very
rarely occurred in about 1% of the trials. Drugs had no
significant effect on dispersion [F (6,30) = 0.62, P = 0.71],
percentage into the TTZ [F (6,30) = 0.60, P = 0.72] or amplitude
[F (6,30) = 2.14, P = 0.078] at time point PRE2 (Table 2). There
were also no differences in characteristics of TMS-induced
thumb movements [dispersion: F (6,30) = 1.11, P = 0.38;
percentage into TTZ: F (6,30) = 0.77, P = 0.60; amplitude:
F (6,30) = 1.10, P = 0.39] when comparing PRE2 (2 h after
drug intake) with PRE1 (immediately before drug intake).
Therefore, it can be concluded that there were no consistent
drug effects on TMS-induced thumb movements before training
that accounted for the effects of drug on practice-dependent
plasticity.
Training Performance
Drugs had no effect on dispersion [F (6,30) = 1.05, P = 0.41] and
DPHI [F (6,30) = 1.17, P = 0.35] of voluntary thumb movements
during training (Table 3). There was a slight effect of Drug on
the amplitude of voluntary thumb movements [F (6,30) = 2.64,
P = 0.036], but post hoc tests showed no significant difference
of any of the drugs with placebo (Table 3). Thus, there were no
consistent drug effects on training performance that accounted
for the effects of drugs on practice-dependent plasticity.
Practice-dependent Plasticity -- Increase of TMS-induced
Thumb Movements into the TTZ
The two-way ANOVA across all time points during and after
training (D1-P6) revealed a significant effect of Drug [F (6,30) =
5.16, P = 0.0009]. Post hoc comparisons of the single drugs
with PBO showed that MPH (P < 0.001), CAB (P < 0.001) and
Table 2
Characteristics of TMS-induced thumb movements before training (PRE2)
Drug
Dispersion
% into TTZ
Amplitude (m/s2)
PBO
PRZ
MPH
HAL
CAB
BIP
TAC
0.86
0.83
0.80
0.84
0.86
0.84
0.83
0±0
2.1 ± 0.9
0±0
2.8 ± 1.1
2.0 ± 0.8
4.6 ± 1.9
4.5 ± 1.9
0.80
1.13
1.30
1.40
1.28
0.86
0.80
±
±
±
±
±
±
±
0.06
0.04
0.07
0.07
0.05
0.07
0.09
±
±
±
±
±
±
±
0.17
0.69
0.62
0.99
0.95
0.43
0.16
All data are means ± SD from six subjects.
Table 3
Training performance
Drug
Dispersion
DPHI ()
PBO
PRZ
MPH
HAL
CAB
BIP
TAC
0.91
0.87
0.89
0.90
0.91
0.89
0.91
171.3
173.5
169.8
166.7
156.7
159.1
146.7
±
±
±
±
±
±
±
0.02
0.04
0.03
0.03
0.04
0.05
0.03
±
±
±
±
±
±
±
Amplitude (m/s2)
11.0
7.7
10.6
3.2
45.7
11.6
35.0
5.3
6.5
4.7
6.3
5.0
5.3
5.8
±
±
±
±
±
±
±
2.8
2.0
2.5
3.8
2.0
1.4
2.8
All data are means ± SD from six subjects.
TAC (P = 0.001) resulted in an increase of practice-dependent
plasticity, while HAL (P = 0.001) and BIP (P = 0.007) resulted in
a decrease (Fig. 2A--D). Since the two-way ANOVA also showed
a significant interaction between Drug and Time [F (60,300) =
1.48, P = 0.019], additional ANOVAs were run that were
restricted to the time points either during training (D1--D5)
or after training (P1--P6). During training, there were significant effects of Drug [F (6,30) = 5.84, P = 0.0004] and Time
[F (4,20) = 4.01, P = 0.015], while the interaction between Drug
and Time was not significant [F (24,120) = 0.83, P = 0.70]. Post
hoc comparisons of the single drugs with PBO revealed that
practice-dependent plasticity occurred more rapidly under
MPH (P = 0.0001) and CAB (P = 0.0002), but developed to
a lesser extent under HAL (P = 0.023) and BIP (P = 0.025). In
addition, practice-dependent plasticity was non-significantly
enhanced under TAC (P = 0.052) (Fig. 2A--C,E). After the end
of training, there was a significant effect of Drug [F (6,30) = 3.41,
P = 0.011] and the interaction between Drug and Time
[F (30, 150) = 2.04, P = 0.0028]. Post hoc comparisons of the
single drugs with PBO showed that the gain in practicedependent plasticity observed during training was retained
for under CAB (P < 0.0001) and TAC (P = 0.01) but not under
MPH (P = 0.12). Practice-dependent plasticity remained less
under HAL (P = 0.014) when compared with practicedependent learning under PBO (Fig. 2A--C,F).
Practice-dependent Plasticity -- wPHI
Analysis of practice-dependent plasticity by increase of TMSinduced thumb movements into the TTZ is an all-or-none
procedure that has the potential disadvantage of missing small
training induced changes in the direction of TMS-induced
thumb movements. Therefore, an analysis of wPHI (see Materials
and Methods) was also performed. The two-way ANOVA across
all time points during and after training (D1--P6) revealed
a significant effect of Drug [F (6,30) = 9.67, P < 0.0001]. This
was explained in the post hoc tests by an enhancement of
practice-dependent plasticity under MPH (P < 0.0001), CAB
Cerebral Cortex August 2006, V 16 N 8 1109
Figure 2. Effects of neuromodulating drugs on practice-dependent plasticity quantified by the percentage increase of TMS-induced thumb movements into the training target zone
(TTZ) during (D1--D5) and after practice (P1--P6) compared with measurements prior to practice (PRE2). (A--C) Time course of TTZ increase under drugs in the norepinephrine (A),
dopamine (B) and acetylcholine system (C) compared with TTZ increase under PBO (thick curve in diagrams A--C). The dotted vertical line indicates end of practice. All data are
means of six subjects. (D--F) Summary box plots of TTZ increase (y-axis) averaged over all time points (D1--P6) (D), all time points during practice only (D1--D5) (E) and all time points
after practice only (P1--P6) (F) plotted against drug (x-axis). The horizontal dotted line indicates the median TTZ increase in the PBO condition. *P < 0.007, §P < 0.05 (Wilcoxon
signed rank tests, comparing single drugs with PBO).
(P < 0.0001) and TAC (P = 0.0003) but a suppression under HAL
(P = 0.0003) and BIP (P < 0.0001) (Fig. 3A--D). Restriction of the
ANOVA to the time points during training (D1--D5) demonstrated significant effects of Drug [F (6,30) = 7.83, P < 0.0001]
and Time [F (4,20) = 4.38, P = 0.011]. The post hoc tests revealed
that practice-dependent plasticity occurred more rapidly under
MPH (P < 0.0001), CAB (P < 0.0001) and TAC (P = 0.0068), but
developed to a lesser extent under BIP (P = 0.002) (Fig. 3A--C,E).
Finally, restriction of the ANOVA to the time points after the
end of training (P1--P6) showed again a significant effect of Drug
[F (6,30) = 4.71, P = 0.0017]. This was explained in the post hoc
tests by a retention of the gain in practice-dependent plasticity
under CAB (P < 0.0001) and TAC (P = 0.022) but not MPH
(P = 0.23), while practice-dependent plasticity remained low
under BIP (P = 0.0038) and declined away from the PBO level
under PRZ (P = 0.020) and HAL (P = 0.0009) (Fig. 3A--C,F).
1110 Neuromodulation of Motor Plasticity
d
Meintzschel and Ziemann
EMG Data
During PRE2, the grand mean MEP amplitude across all sessions
and subjects in the prime mover of the motor practice was
0.96 ± 0.76 mV, and there were no differences between Drugs
(P = 0.23). MEP amplitudes during and after practice (D1--P6)
normalized to the MEP amplitude during baseline (PRE2)
increased, as indicated by a significant effect of Time in the
two-way ANOVA [F (10,50) = 4.12, P = 0.0004] while there were
no significant effects of Drug (P = 0.17) or the interaction
between Drug and Time (P = 0.45) (Fig. 4). For some drugs the
time course of changes in MEP amplitude showed similarity
with the time course of practice-dependent plasticity (e.g. for
PBO and MPH in Figs 2A and 4A) while for other drugs the time
course was clearly different (e.g. CAB in Figs 2B and 4B). In
order to get more insight into the relation between changes
in MEP amplitude and practice-dependent plasticity during
Figure 3. Effects of neuromodulating drugs on practice-dependent plasticity quantified by angle shift of TMS-induced thumb movement during (D1--D5) and after practice (P1--P6)
compared with angle of TMS-induced thumb movement during PRE2 divided by angle shift of voluntary thumb movement compared with angle of TMS-induced thumb movement
during PRE2 (wPHI, y-axis). Otherwise, arrangement and conventions are the same as in Figure 2.
training, regression analyses were conducted for those drugs
that enhanced practice-dependent plasticity (MPH, CAB, TAC).
All regressions were significant but relations were quite
different: while it was logarithmic for MPH, it was inverse linear
for CAB and normal linear for TAC (Fig. 5). Regression analyses
were not significant for any of the other drugs (P > 0.05).
Discussion
The present experiments combine previously reported
results on pharmacological modulation of practice-dependent
plasticity in a single systematic double-blind placebo-controlled
crossover design. The major finding is that agonists and
antagonists of the main neuromodulating transmitters systems
(norepinephrine, dopamine, acetylcholine) produce significant
and oppositely directed modifications of practice-dependent
plasticity in human motor cortex. The agonists of all three
systems (methylphenidate, cabergoline, tacrine) enhanced
practice-dependent plasticity, while the antagonists (prazosin,
haloperidol, biperiden) reduced it.
Mechanisms of Practice-dependent Motor
Cortical Plasticity
We investigated practice-dependent plasticity by means of
a standardized TMS protocol (Classen et al., 1998). The site of
plasticity, i.e. the practice-induced increase of TMS-induced
thumb movements into the training target zone, is very likely in
the motor cortex because the post-training angular deviation of
thumb movements elicited with transcranial electrical stimulation (TES) was significantly smaller compared with thumb
movements elicited with TMS (Classen et al., 1998). The
implication is that TES activates the corticomotoneuronal
system predominantly directly rather than transsynaptically
(Day et al., 1989). Therefore, a plasticity effect visible with
Cerebral Cortex August 2006, V 16 N 8 1111
benzodiazepine lorazepam, an allosteric positive modulator at
the GABAA receptor (Bütefisch et al., 2000). This indirectly
supported the LTP hypothesis further because disinhibition
through local application of a GABAA receptor antagonist
facilitated LTP in motor cortical slice experiments (Hess and
Donoghue, 1994; Castro-Alamancos et al., 1995; Hess et al.,
1996). In summary, the available data are compatible with the
idea that this form of practice-dependent plasticity as studied in
the present experiments relies on LTP-like strengthening of
synaptic efficacy. The following paragraphs discuss, in this
context of an LTP-dependent process, some of the basic
mechanisms that might underlie the observed modifying effects
of agonists and antagonists in the three neuromodulating
transmitter systems.
Modification of Practice-dependent Plasticity in the
Norepinephrine System
NE enhanced LTP evoked by theta-burst stimulation in slices of
rat visual cortex by increasing the depolarizing response to the
tetanus, and in turn, by increasing NMDA receptor-gated
conductances during this response (Bröcher et al., 1992). The
authors suggested that this mode of action accounts for the
facilitatory effects of NE on use-dependent synaptic plasticity in
the visual cortex (Bear and Singer, 1986). In rat motor cortex,
NE increased the excitability of large pyramidal cells in layer V
through a reduction of slow K+ currents, and through an
+
increase of the persistent inward Na current (Foehring et al.,
1989). It is likely that these NE effects are capable of promoting
LTP in motor cortex but this has not been tested yet in slice
experiments.
In humans, MPH increases corticomotoneuronal excitability
and decreases GABAA ergic intracortical inhibition (Ilic et al.,
2003). Both effects may have been involved in the significant
enhancement of practice-dependent plasticity by MPH observed in the present study. It is very likely that this enhancement of plasticity is at least in part mediated through the a1
receptor because the a1 receptor antagonist PRZ reduced
practice-dependent plasticity in the present experiments and in
one previous study (Sawaki et al., 2003) while the non-selective
b-blocker propranolol showed only a clearly weaker and nonsignificant trend towards reduction of practice-dependent
plasticity (Sawaki et al., 2003).
Figure 4. Time course of mean MEP amplitude (six subjects) of the prime mover of
practice during (D1--D5) and after practice (P1--P6), normalized to MEP amplitude
during PRE2 (nMEP, y-axis) under neuromodulating drugs in the norepinephrine (A),
dopamine (B) and acetylcholine system (C). MEP data in the PBO condition are
indicated by the thick curve in all diagrams. The vertical dotted line denotes end of
practice.
TMS but not TES points to a site upstream of the corticomotoneuronal axon. Previous experiments showed that this
form of practice-dependent plasticity was blocked by the
NMDA receptor antagonist dextromethorphan (Bütefisch
et al., 2000). This led to the idea that a long-term potentiation
(LTP)-like strengthening of excitatory synapses in motor
cortical circuits was involved (Bütefisch et al., 2000) because
LTP is an important mechanism of plasticity (Sanes and
Donoghue, 2000) that, in the motor cortex, depends on the
activation of NMDA receptors (Hess et al., 1996). Furthermore,
this form of practice-dependent plasticity was prevented by the
1112 Neuromodulation of Motor Plasticity
d
Meintzschel and Ziemann
Modification of Practice-dependent Plasticity in the
Dopamine System
In monkeys, the motor cortex receives the greatest density of
dopaminergic fibres of all cortical areas (Lewis et al., 1987;
Williams and Goldman-Rakic, 1993). A prominent effect of
iontophoretic application of DA to cortical neurons is to
depress their activity (Krnjevic and Phillis, 1963). This effect
is most likely mediated by dopaminergic D2 receptors
(Gulledge and Jaffe, 1998). In vitro studies in human cortical
tissue showed that DA reduced neuronal excitability by decreasing neurotransmission through non-NMDA glutamate
receptors (Cepeda et al., 1992). In contrast, DA increased
neurotransmission through NMDA receptors (Cepeda et al.,
1992). This important study strongly supports the idea that DA
is capable of enhancing the signal-to-noise ratio in a neuronal
network by suppressing unwanted inputs (noise) but strengthening pathways that conduct repeated and consistent inputs
(Huda et al., 2001). Therefore, it is not a paradox that LTP
Figure 5. Regression plots of MEP amplitude (6 subjects) obtained during training (time points D1--D5) and normalized to MEP amplitude during PRE2 (nMEP, x-axis) versus
practice-dependent plasticity (wPHI, y-axis) for PBO and for the three drugs (MPH, CAB, TAC) that enhanced practice-dependent plasticity.
dependent processes such as practice-dependent plasticity are
enhanced by DA although neuronal excitability as determined
by fast excitatory post-synaptic potentials mediated through
non-NMDA glutamate receptors is decreased.
In accord with these studies at the cellular level, TMS
experiments at the systems level of human motor cortex
showed that the D2 receptor agonist CAB significantly depressed the MEP intensity curve, while the D2 receptor
antagonist HAL increased it (U. Ziemann et al., unpublished
observations). The MEP intensity curve is a measure of corticomotoneuronal excitability, reflecting TMS excitation of extrinsic inputs to motor cortex through cortico-cortical axons and
non-NMDA glutamate receptors (Amassian et al., 1987; Di
Lazzaro et al., 2003). The present experiments are the first
to show that, dissociated from the effects of CAB vs. HAL on
corticomotoneuronal excitability, CAB enhanced practicedependent plasticity while HAL depressed it. These findings
are in line with the enhancing effect of levodopa on practicedependent plasticity (Floel et al., 2005a). Since dopamine is an
agonist at both the D1/D5 and D2 receptor families, it is not
clear whether these receptors were differentially involved in
the plasticity modulating effect of levodopa (Floel et al., 2005a).
The present experiments specify that the D2 receptor plays
a significant role in this form of motor cortical plasticity.
Modification of Practice-dependent Plasticity in the
Acetylcholine System
ACh facilitates, through activation of muscarinic receptors,
in particular the M1 receptor, pyramidal cell discharge in
neocortex and the responsiveness of these cells to excitatory
inputs (McCormick and Prince, 1986; Schwindt et al., 1988; Cox
et al., 1994). This cholinergic modulation is associated with enhancement of neurotransmission through the NMDA receptor
(Bröcher et al., 1992). Accordingly, in slice experiments of
rat motor cortex, pharmacological blockade of muscarinic
receptors by atropine prevented the induction of LTP after
theta-burst stimulation but rather promoted the induction of
long-term depression (Hess and Donoghue, 1999). ACh is also
important for practice-dependent motor cortical plasticity in
rats because lesions of the basal forebrain cholinergic system
disrupted cortical map reorganization and impaired motor skill
acquisition (Conner et al., 2003).
In human motor cortex, the ACh-esterase inhibitor TAC
shifts the balance from inhibition to excitation by increasing
short-interval intracortical facilitation, a measure of the excit-
ability of fast glutamatergic input to motor cortical output
neurons, and by decreasing short-interval intracortical inhibition (Korchounov et al., 2005). In accord with these data, the
present experiments showed that TAC facilitated practicedependent plasticity whereas BIP suppressed it. BIP is a selective
M1 receptor antagonist. Therefore, the present findings confirm
and extend one previous study that reported a suppression of
practice-dependent plasticity under the non-selective M1/M2
receptor antagonist scopolamine (Sawaki et al., 2002a).
Time Course of Neuromodulating Effects on
Practice-dependent Plasticity
Our findings (Figs 2 and 3) show that the enhancement of
practice-dependent plasticity developed similarly during training under MPH, CAB and TAC, and was maintained for at least 30
min after the end of training under CAB and TAC but not under
MPH. Only one previous study had explored the time course of
a drug modulating effect on this form of practice-dependent
plasticity after the end of training (Bütefisch et al., 2002). It was
found that d-amphetamine resulted in a long-lasting enhancement ( >60 min). Since D-amphetamine results in a strong
increase in extracellular DA concentration (Kuczenski and
Segal, 2001), those data and the present CAB data are in close
agreement. The time courses of depressant effects on practicedependent plasticity by PRZ, HAL and BIP also differed slightly.
Interference with the development of practice-dependent
plasticity during training was most conspicuous under BIP
while after the end of training all three drugs resulted in less
plasticity than under PBO. Mechanisms of these differences in
time courses of practice-dependent plasticity modulation are
unclear at present. It is also unknown whether the different
time courses have any practical relevance, but it may be
speculated that they favour DA and ACh over NE if long-lasting
facilitation of training effects is desired, as during neurorehabilitation of stroke patients.
Relation between Motor Cortical Excitability and
Practice-dependent Plasticity
The regression analysis between practice-dependent changes in
MEP amplitude of the prime mover muscle of the practice and
practice-dependent plasticity (wPHI) demonstrated that the
relation between corticomotoneuronal excitability and practicedependent plasticity is not uniform (Fig. 5). While practicedependent plasticity under MPH and TAC was associated
with an increase in MEP amplitude of the prime mover,
Cerebral Cortex August 2006, V 16 N 8 1113
practice-dependent plasticity under CAB was associated with
a decrease. A proper assessment of the APB and FDI acting as
agonists vs. antagonists of the motor practice was not possible
due to the problem of volume conduction between the EMG
recordings, and because in some instances when thumb movements were practiced in abduction--flexion direction, both
muscles were training agonists. However, this does not limit
data interpretation because even when information of MEP
amplitudes of true agonists and antagonists of the practice was
available in previous studies, it was generally found that the ratio
of MEP amplitudes of agonists over antagonists was not closely
linked with the magnitude of practice-dependent plasticity as
measured by the increase of TMS-induced thumb movements
into the training target zone (Bütefisch et al., 2000, 2002; Floel
et al., 2005a). This strongly suggests that an increase in
corticomotoneuronal excitability of the agonist of motor
practice is neither sufficient (Floel et al., 2005a) nor necessary
(present data) to explain the practice-dependent shift in the
direction of TMS-induced thumb movements. The question
arises of how it is possible, as observed under CAB, that
enhancement of practice-dependent plasticity is associated
with a decrease in MEP amplitude of the training agonist. One
possibility is that an even stronger decrease in excitability of
corticomotoneuronal representations of the training antagonists occurred, leading to an improved signal-to-noise ratio in
favour of the training agonist.
The contrasting properties observed here with respect to the
relation of MEP amplitude and practice-dependent plasticity
under MPH and TAC (normal relation) versus CAB (inverse
relation) are compatible with the effects of these drugs on
corticomotoneuronal cell activity per se and the responsiveness
of these cells to external input: MPH and TAC increase it, while
CAB decreases it (see above). This suggests that enhancement
of practice-dependent plasticity by neuromodulating transmitters can occur through fundamentally different strategies that
either favour extrinsic (NE, ACh) or intrinsic (DA) modulating
influence on the motor cortical output network (Hasselmo,
1995). Whether one of these strategies is more effective in
supporting motor rehabilitation in the clinical setting is unknown yet, as it was shown in lesion experiments in animals (for
a review, see Feeney and Sutton, 1987) and in humans after
stroke that agonists in all three neuromodulating transmitter
systems facilitate sensorimotor recovery (Crisostomo et al.,
1988; Walker-Batson et al., 1995, 2001; Grade et al., 1998;
Scheidtmann et al., 2001; Floel et al., 2005b) while antagonists
impede it (for a review, see Goldstein, 1998).
Notes
This work was supported by grant ZI 542/2--1 from the Deutsche
Forschungsgemeinschaft (DFG).
Address correspondence to Prof. Ulf Ziemann. Department of Neurology, Johann Wolfgang Goethe-University Frankfurt, Schleusenweg
2--16, D-60528 Frankfurt am Main, Germany. Email: u.ziemann@em.
uni-frankfurt.de.
References
Amassian VE, Stewart M, Quirk GJ, Rosenthal JL (1987) Physiological
basis of motor effects of a transient stimulus to cerebral cortex.
Neurosurgery 20:74--93.
Bear MF, Singer W (1986) Modulation of visual cortical plasticity by
acetylcholine and noradrenaline. Nature 320:172--176.
Bröcher S, Artola A, Singer W (1992) Agonists of cholinergic and
noradrenergic receptors facilitate synergistically the induction of
1114 Neuromodulation of Motor Plasticity
d
Meintzschel and Ziemann
long-term potentiation in slices of rat visual cortex. Brain Res
573:27--36.
Bütefisch CM, Davis BC, Wise SP, Sawaki L, Kopylev L, Classen J,
Cohen LG (2000) Mechanisms of use-dependent plasticity in the
human motor cortex. Proc Natl Acad Sci USA 97:3661--665.
Bütefisch CM, Davis BC, Sawaki L, Waldvogel D, Classen J, Kopylev L,
Cohen LG (2002) Modulation of use-dependent plasticity by damphetamine. Ann Neurol 51:59--68.
Castro-Alamancos MA, Donoghue JP, Connors BW (1995) Different
forms of synaptic plasticity in somatosensory and motor areas of the
neocortex. J Neurosci 15:5324--5333.
Cepeda C, Radisavljevic Z, Peacock W, Levine MS, Buchwald NA (1992)
Differential modulation by dopamine of responses evoked by
excitatory amino acids in human cortex. Synapse 11:330--341.
Classen J, Cohen LG (2003) Practice-induced plasticity in the human
motor cortex. In: Plasticity in the human nervous system. Investigations with transcranial magnetic stimulation (Boniface SJ and
Ziemann U, eds), pp. 90--106. Cambridge: Cambridge University Press.
Classen J, Liepert J, Wise SP, Hallett M, Cohen LG (1998) Rapid plasticity
of human cortical movement representation induced by practice.
J Neurophysiol 79:1117--1123.
Conner JM, Culberson A, Packowski C, Chiba AA, Tuszynski MH (2003)
Lesions of the basal forebrain cholinergic system impair task
acquisition and abolish cortical plasticity associated with motor skill
learning. Neuron 38:819--829.
Cooper JR, Bloom FE, Roth RH (2002) The biochemical basis of
neuropharmacology. New York: Oxford University Press.
Cox CL, Metherate R, Ashe JH (1994) Modulation of cellular excitability
in neocortex:muscarinic receptor and second messenger-mediated
actions of acetylcholine. Synapse 16:123--136.
Crisostomo EA, Duncan PW, Propst M, Dawson DV, Davis JN (1988)
Evidence that amphetamine with physical therapy promotes recovery of motor function in stroke patients. Ann Neurol 23:94--97.
Day BL, Dressler D, Maertens de Noordhout A, Marsden CD, Nakashima
K, Rothwell JC, Thompson PD (1989) Electric and magnetic
stimulation of human motor cortex:surface EMG and single motor
unit responses. J Physiol (Lond) 412:449--473.
Di Lazzaro V, Oliviero A, Profice P, Pennisi MA, Pilato F, Zito G,
Dileone M, Nicoletti R, Pasqualetti P, Tonali PA (2003) Ketamine
increases motor cortex excitability to transcranial magnetic stimulation. J Physiol 547:485--496.
Di Lazzaro V, Oliviero A, Pilato F, Saturno E, Dileone M, Mazzone P,
Insola A, Tonali PA, Rothwell JC (2004) The physiological basis of
transcranial motor cortex stimulation in conscious humans. Clin
Neurophysiol 115:255--266.
Feeney DM, Sutton RL (1987) Pharmacotherapy for recovery of function
after brain injury. Crit Rev Neurobiol 3:135--197.
Floel A, Breitenstein C, Hummel F, Celnik P, Gingert C, Sawaki L,
Knecht S, Cohen LG (2005a) Dopaminergic influences on formation
of a motor memory. Ann Neurol 58:121--130.
Floel A, Hummel F, Breitenstein C, Knecht S, Cohen LG (2005b)
Dopaminergic effects on encoding of a motor memory in chronic
stroke. Neurology 65:472--474.
Foehring RC, Schwindt PC, Crill WE (1989) Norepinephrine selectively
reduces slow Ca2+- and Na+-mediated K+ currents in cat neocortical
neurons. J Neurophysiol 61:245--256.
Goldstein LB (1998) Potential effects of common drugs on stroke
recovery. Arch Neurol 55:454--46.
Grade C, Redford B, Chrostowski J, Toussaint L, Blackwell B (1998)
Methylphenidate in early poststroke recovery:a double-blind,
placebo-controlled study. Arch Phys Med Rehabil 79:1047--1050.
Gu Q (2002) Neuromodulatory transmitter systems in the cortex and
their role in cortical plasticity. Neuroscience 111:815--835.
Gulledge AT, Jaffe DB (1998) Dopamine decreases the excitability of
layer V pyramidal cells in the rat prefrontal cortex. J Neurosci
18:9139--9151.
Hasselmo ME (1995) Neuromodulation and cortical function: modeling
the physiological basis of behavior. Behav Brain Res 67:1--27.
Hess G, Donoghue JP (1994) Long-term potentiation of horizontal
connections provides a mechanism to reorganize cortical motor
maps. J Neurophysiol 71:2543--2547.
Hess G, Donoghue JP (1999) Facilitation of long-term potentiation in
layer II/III horizontal connections of rat motor cortex following
layer I stimulation:route of effect and cholinergic contributions. Exp
Brain Res 127:279--290.
Hess G, Aizenman CD, Donoghue JP (1996) Conditions for the induction
of long-term potentiation in layer II/III horizontal connections of the
rat motor cortex. J Neurophysiol 75:1765--1778.
Huda K, Salunga TL, Matsunami K (2001) Dopaminergic inhibition of
excitatory inputs onto pyramidal tract neurons in cat motor cortex.
Neurosci Lett 307:175--178.
Ilic TV, Korchounov A, Ziemann U (2003) Methylphenydate facilitates
and disinhibits the motor cortex in intact humans. Neuroreport
14:773--776.
Kleim JA, Barbay S, Nudo RJ (1998) Functional reorganization of the rat
motor cortex following motor skill learning. J Neurophysiol
80:3321--3325.
Korchounov A, Ilic TV, Schwinge T, Ziemann U (2005) Modification of
motor cortical excitability by an acetylcholine-esterase inhibitor.
Exp Brain Res 164:399--405.
Krnjevic K, Phillis JW (1963) Iontophoretic studies of neurones in the
mammalian cerebral cortex. J Physiol 165:274--304.
Kuczenski R, Segal DS (2001) Locomotor effects of acute and repeated
threshold doses of amphetamine and methylphenidate: relative
roles of dopamine and norepinephrine. J Pharmacol Exp Ther
296:876--883.
Lewis DA, Campbell MJ, Foote SL, Goldstein M, Morrison JH (1987) The
distribution of tyrosine hydroxylase-immunoreactive fibers in
primate neocortex is widespread but regionally specific. J Neurosci
7:279--290.
Liepert J, Terborg C, Weiller C (1999) Motor plasticity induced by synchronized thumb and foot movements. Exp Brain Res 125:435--439.
McCormick DA, Prince DA (1986) Mechanisms of action of acetylcholine in the guinea-pig cerebral cortex in vitro. J Physiol 375:169--194.
Nudo RJ, Milliken GW, Jenkins WM, Merzenich MM (1996) Usedependent alterations of movement representations in primary
motor cortex of adult squirrel monkeys. J Neurosci 16:785--807.
Pascual-Leone A, Nguyet D, Cohen LG, Brasil-Neto JP, Cammarota A,
Hallett M (1995) Modulation of muscle responses evoked by transcranial magnetic stimulation during the acquisition of new fine
motor skills. J Neurophysiol 74:1037--1045.
Rossini PM, Berardelli A, Deuschl G, Hallett M, Maertens de Noordhout
AM, Paulus W, Pauri F (1999) Applications of magnetic cortical
stimulation. Electroencephalogr Clin Neurophysiol Suppl 52:
171--185.
Sanes JN, Donoghue JP (2000) Plasticity and primary motor cortex.
Annu Rev Neurosci 23:393--415.
Sawaki L, Boroojerdi B, Kaelin-Lang A, Burstein AH, Butefisch CM,
Kopylev L, Davis B, Cohen LG (2002a) Cholinergic influences on
use-dependent plasticity. J Neurophysiol 87:166--171.
Sawaki L, Cohen LG, Classen J, Davis BC, Butefisch CM (2002b)
Enhancement of use-dependent plasticity by D-amphetamine. Neurology 59:1262--1264.
Sawaki L, Werhahn KJ, Barco R, Kopylev L, Cohen LG (2003) Effect of an
alpha(1)-adrenergic blocker on plasticity elicited by motor training.
Exp Brain Res 148:504--508.
Scheidtmann K, Fries W, Muller F, Koenig E (2001) Effect of levodopa in
combination with physiotherapy on functional motor recovery after
stroke: a prospective, randomised, double-blind study. Lancet
358:787--790.
Schwindt PC, Spain WJ, Foehring RC, Chubb MC, Crill WE (1988) Slow
conductances in neurons from cat sensorimotor cortex in vitro
and their role in slow excitability changes. J Neurophysiol 59:
450--467.
Treig T, Werner C, Sachse M, Hesse S (2003) No benefit from Damphetamine when added to physiotherapy after stroke: a randomized, placebo-controlled study. Clin Rehabil 17:590--599.
Walker-Batson D, Smith P, Curtis S, Unwin H, Greenlee R (1995)
Amphetamine paired with physical therapy accelerates motor
recovery after stroke. Further evidence. Stroke 26:2254--2259.
Walker-Batson D, Curtis S, Natarajan R, Ford J, Dronkers N, Salmeron E,
Lai J, Unwin DH (2001) A double-blind, placebo-controlled study of
the use of amphetamine in the treatment of aphasia. Stroke 32:
2093--2098.
Williams SM, Goldman-Rakic PS (1993) Characterization of the dopaminergic innervation of the primate frontal cortex using a dopaminespecific antibody. Cereb Cortex 3:199--222.
Ziemann U, Tergau F, Bruns D, Baudewig J, Paulus W (1997) Changes
in human motor cortex excitability induced by dopaminergic and
anti-dopaminergic drugs. Electroencephalogr Clin Neurophysiol
105:430--437.
Cerebral Cortex August 2006, V 16 N 8 1115