Cerebral Cortex November 2009;19:2605--2615
doi:10.1093/cercor/bhp013
Advance Access publication February 20, 2009
Stimulus--Response Profile during SinglePulse Transcranial Magnetic Stimulation
to the Primary Motor Cortex
Takashi Hanakawa1,2, Tatsuya Mima3, Riki Matsumoto4,
Mitsunari Abe3, Morito Inouchi4, Shin-ichi Urayama3,
Kimitaka Anami5, Manabu Honda1,6 and Hidenao Fukuyama3
We examined the stimulus--response profile during single-pulse
transcranial magnetic stimulation (TMS) by measuring motorevoked potentials (MEPs) with electromyographic monitoring and
hemodynamic responses with functional magnetic resonance
imaging (fMRI) at 3 Tesla. In 16 healthy subjects, single TMS
pulses were irregularly delivered to the left primary motor cortex at
a mean frequency of 0.15 Hz with a wide range of stimulus
intensities. The measurement of MEP proved a typical relationship
between stimulus intensity and MEP amplitude in the concurrent
TMS-fMRI environment. In the population-level analysis of the
suprathreshold stimulation conditions, significant increases in
hemodynamic responses were detected in the motor/somatosensory network, reflecting both direct and remote effects of TMS, and
also the auditory/cognitive areas, perhaps related to detection of
clicks. The stimulus--response profile showed both linear and
nonlinear components in the direct and remote motor/somatosensory network. A detailed analysis suggested that the nonlinear
components of the motor/somatosensory network activity might be
induced by nonlinear recruitment of neurons in addition to sensory
afferents resulting from movement. These findings expand our
basic knowledge of the quantitative relationship between TMSinduced neural activations and hemodynamic signals measured by
neuroimaging techniques.
In fact, the combined use of TMS with positron emission
tomography (PET) (Fox et al. 1997; Paus et al. 1997; Siebner
et al. 1998, 2001; Speer et al. 2003), single photon emission
computed tomography (Okabe et al. 2003), or functional
magnetic resonance imaging (fMRI) (Bohning et al. 1998, 1999;
Baudewig et al. 2001; Bestmann et al. 2004) has been emerging
in the field of noninvasive human brain mapping. The stimulus-response relationship between various stimulus parameters and
evoked hemodynamic signals is important for the interpretation of findings from simultaneous TMS-imaging studies. Several
studies have already addressed intensity-dependent effects on
brain activity, by incorporating more than 2 different levels of
stimulus intensity into the experimental paradigm (Baudewig
et al. 2001; Nahas et al. 2001; Bestmann et al. 2003; Speer et al.
2003; Fox et al. 2006). Peculiarly, at first glance, the directly
stimulated area in these studies consistently requires a stronger
stimulus for the induction of significantly increased brain
activation measurable with neuroimaging techniques than do
remote, nonstimulated areas. In response to TMS to the primary
motor cortex (M1), for example, activity in the supplementary
motor areas (SMA) is increased during both subthreshold and
suprathreshold TMS, whereas activity in the directly stimulated
M1 is induced only by suprathreshold TMS. Although these
observations are extremely interesting, they might reflect
complex interactions between intensity, frequency and train
length rather than pure effects of intensity, as almost all
intensity-response studies have employed rTMS paradigms.
Evidence suggests that the effects of rTMS on brain activity may
last for days (Hayashi et al. 2004), and thus caution must be
paid to interpret brain activity changes from repeated runs of
rTMS protocols. Meanwhile, Komssi and colleagues recorded
electroencephalographic (EEG) responses immediately after
delivery of single TMS pulses to the M1 at various stimulus
intensities (Komssi et al. 2004). By taking advantage of the fine
temporal resolution of the technique, the authors were able to
demonstrate both linear and nonlinear aspects in the intensityresponse profile. However, the neural correlates of the
source(s) of these brain responses remain to be specified.
The purpose of the present study was to investigate the
stimulus--response profile during single-pulse TMS in the
directly stimulated and remote regions in the whole brain.
Hemodynamic signals and motor-evoked potentials (MEPs) in
response to single TMS pulses were sampled at a wide range of
stimulus intensities. To achieve online monitoring of surface
electromyography (EMG) during concurrent TMS-fMRI, we
employed the stepping stone sampling (SSS) method developed
Keywords: functional connectivity, functional MRI, motor-evoked
potentials, multidisciplinary brain mapping, transcranial magnetic stimulation
Introduction
Transcranial magnetic stimulation (TMS) is a noninvasive technique that stimulates a localized brain region underneath the
coil and thereby modulates brain activity. Single-pulse TMS can
temporarily affect motor, sensory or cognitive behavior, and
repetitive TMS (rTMS) protocols such as theta burst stimulation
(Huang et al. 2005) can induce long-lasting plastic changes.
Because of these unique properties, TMS has been widely applied
to basic neuroscience research and various clinical settings.
Nevertheless, the actions of TMS, presumptively involving both
excitatory and inhibitory neural circuits, are not fully understood.
A recent study investigated changes in neuronal activity and
local field potentials simultaneously with tissue oxygenation in
anesthetized cats (Allen et al. 2007). This study clearly demonstrated that TMS-induced local neuronal changes, either increases
or decreases of activity, resulted in corresponding hemodynamic
changes, and promised the helpfulness of hemodynamic measurements for monitoring the actions of TMS.
The Author 2009. Published by Oxford University Press. All rights reserved.
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1
Department of Cortical Function Disorders, National Institute
of Neuroscience, National Center of Neurology and Psychiatry,
Kodaira 187-8502, Japan, 2PRESTO, Japan Science and
Technology Agency, Kawaguchi 332-0012, Japan, 3Human
Brain Research Center, Kyoto University Graduate School of
Medicine, Kyoto 606-8507, Japan, 4Department of Neurology,
Kyoto University Graduate School of Medicine, Kyoto 6068507, Japan, 5Musashino Hospital, Ageo 362-0033, Japan and
6
CREST, Japan Science and Technology Agency, Kawaguchi
332-0012, Japan
for artifact-diminished acquisition of EEG during hemodynamic
imaging (Anami et al. 2003). The hypothesis was that singlepulse TMS-induced changes in hemodynamic signals would
show both linear and nonlinear components as suggested by
a previous TMS-EEG study (Komssi et al. 2004). The present
TMS-fMRI study was expected to identify the sources of these
TMS-induced linear and nonlinear stimulus--response profiles in
a spatially segregated manner. A preliminary result of this study
has been published only in abstract form.
Materials and Methods
Subjects
Nineteen healthy adults (mean age = 31.4 years; range 24--39 years)
were initially recruited. None of the subjects reported any history of
neuropsychiatric disorders, especially epilepsy. All subjects were right
handed as judged by Edinburgh handedness inventory. The study
protocol was approved by the Kyoto University Graduate School and
Faculty of Medicine, Ethics Committee. The subjects were fully
informed about the experimental procedure, and all of them
participated in the experiment after giving written informed consent.
TMS and EMG Monitoring
The optimal site at which TMS evoked a maximal motor response in the
right abductor pollicis brevis (APB) muscle (‘‘motor hot-spot’’) was
identified for each subject while sitting comfortably on a chair outside
the scanner. The scalp position corresponding to the motor hot spot
was marked with a felt-tip pen. We used the APB in this experiment
because the cortical representation of the thumb is larger than that of
the other fingers (Penfield and Boldrey 1937). We thought that this fact
should help us to stimulate the cortical representation of the same
finger consistently and thereby allow us to measure reliable fMRI
signals during the whole fMRI session.
The subject then lay supine on the bed of a 3-Tesla whole-body MRI
scanner equipped with a circular polarization head coil (Siemens
Magnetom Trio, Erlangen, Germany). An MRI-compatible figure-of-8
TMS coil with an outer-wing diameter of 70 mm (MR coil, Magstim,
Witland, Wales, UK) was positioned tangentially to the scalp at the
marked site. The orientation of the TMS coil was approximately 45
away from the medial--lateral axis. The TMS coil was connected to
a stimulator (SuperRapid, Magstim, Witland, UK) via a 10-m cable
running through a wave guide tube appropriate for radiofrequency
wave filtering. The stimulator produced biphasic electrical pulses of
approximately 250-ls duration and a rise time of 50 ls.
For EMG recording, we employed a method originally developed for
EEG recording during fMRI scanning (Anami et al. 2003). MEPs were
recorded from the right APB. Silver/silver chloride surface electrodes
with shielded plates and cables were placed over the right thenar
eminence with an interelectrode distance of 3 cm. A ground electrode
was placed on the dorsal surface of the right wrist. EMG signals were
fed to a digital amplifier (SynAmps; Neuroscan, Sterling, VA) through
a radiofrequency filter. EMG data were sampled at a digitization rate of
1 kHz with amplitude resolution of 0.336 lV/bit and a dynamic range of
22 mV. As the SSS method requires precise temporal consistency
between the timing of EMG sampling and that of gradient pulses for
MRI acquisition, the SynAmps amplifier was externally driven by the
clock of the MRI scanner. For this purpose, the clock frequency was
downsampled from the original 10 MHz to 10 kHz by a custom-made
clock divider (CD5; Physio-Tech, Tokyo, Japan). Furthermore, a trigger
pulse from the scanner was sent to the clock divider to synchronize the
onset of EMG measurement and MRI acquisition. The EMG data were
monitored and recorded with a low-pass filter of 2 kHz throughout the
experiment (Fig. 1A).
In the MRI environment, the position of the TMS coil was adjusted
while stimulation was delivered every 5 s to elicit abduction of the right
thumb. After stable production of MEPs was ascertained with EMG
monitoring, the TMS coil was fixed immobile to the scanner bed with
a custom-made coil holder made of polyetheretherketone plastic. To
minimize head motion during the scanning, foam pads or vacuum
2606 Hemodynamic Responses during Single-Pulse TM
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Hanakawa et al.
Figure 1. (A) An example EMG recording during concurrent TMS-fMRI using the
‘‘SSS’’ method. Imaging artifacts are overlain onto the EMG record during fMRI
scanning, as subtraction of imaging artifacts was not performed. Even without artifact
subtraction, MEPs are much larger than scanning artifacts. (B) An example of the
functional imaging volume acquired with the SSS imaging sequence just after a single
TMS pulse.
cushions were utilized. After the subject’s head was positioned at the
gantry center, the resting motor threshold (rMT) was defined
individually as the percentage of stimulator output that elicited MEPs
of >50 lV peak-to-peak amplitude in the APB at rest in more than 5 of
10 successive trials (Rossini et al. 1994).
Experimental Paradigm
During scanning, subjects were instructed to relax and not to fall
asleep. Vision was not constrained. In each fMRI run, 20 TMS pulses
were delivered at a mean frequency of ~0.15 Hz. Stimulus onset
asynchrony was semirandomized (5.4 or 8.1 s). The stimulation timing
was controlled by Presentation software (Neurobehavioral systems,
Albany, CA) on a personal computer synchronized with the MRI
scanner via transistor--transistor logic pulses converted from the default
optic signals of the scanner. To avoid image degradation, TMS pulses
were delivered in the middle of the 200-ms scan delay periods, during
which no gradient magnetic fields or radiofrequency pulses were
generated for MRI acquisition. Twelve out of 19 subjects received TMS
stimulation from 30% to 95% of the machine output at 5% steps. The
stimulus intensity remained the same in each run; one to 2 fMRI runs
were prescribed per TMS intensity. With this protocol, however,
suprathreshold intensity was not sufficiently covered in some subjects
because of technical reasons discussed later. In the remaining 7
subjects, therefore, stimulation intensity up to 110% of the original
machine output was used. By using a special controller provided by the
manufacturer, the maximum machine output of the TMS stimulator was
temporarily reset to 110% of the default machine output (enhanced
mode). For consistency, the physical intensity of TMS stimulation is
always defined as the percentage of the default machine output (in the
range 30--110%) in this article. In the latter group of subjects, stimulus
intensity was varied from 30% of the machine output to <80% of the
rMT in 10% steps and from 80% of the rMT to 110% of the machine
output in 5% steps. The stimulus schedule was either an increasing-decreasing sequence or a decreasing--increasing sequence, and was
counterbalanced across subjects.
Image Acquisition
The SSS scheme was utilized to measure hemodynamic signals with
a blip-type echo planar imaging (EPI) sequence with following
parameters: repetition time (TR) = 2.7 s, intervolume acquisition
delay = 200 ms, echo time (TE) = 30 ms, flip angle (FA) = 90, 64 3 64
matrix, 30 slices, field of view (FOV) = 192 mm, 3 3 3 3 3.75-mm voxel
size, bandwidth = 1086 Hz). In brief, the timing of gradient pulses was
carefully designed so that electrophysiological signals could be sampled
every 1 ms (for a digitization rate at 1 kHz), in the designated periods,
whereas the induced electric currents due to magnetic-field switching
stayed around the baseline level (Anami et al. 2003). The scanner and
the EMG amplifier were perfectly synchronized as described above. In
addition, the intervolume acquisition delay allowed us to acquire EPI
data without interference from induced electromagnetic fields or
vibration of the TMS coil following pulse delivery (Fig. 1B). Each subject
underwent 16--21 fMRI runs, and each run consisted of 70 functional
volumes (total scanning time = 3 min, 9 s).
For anatomical registration, T2-weighted turbo spin echo images
were obtained in the same space with the functional images (TR = 7080
ms, TE = 73 ms, FA = 122, FOV = 192 mm, matrix = 256 3 256, voxel
size = 0.75 3 0.75 3 3.75 mm). T1-weighted 3-dimensional structural
images were also acquired with a magnetization-prepared, rapidgradient echo sequence (TR = 2,000 ms, TE = 4.38 ms, FA = 8,
FOV = 240 mm, matrix = 256 3 256, voxel size = 1 3 1 3 1 mm).
EMG and Image Data Analysis
To assess the cortico-motoneuronal output, the peak-to-peak amplitude
of MEP for each stimulation was measured and the data were averaged
for each session (Scan 4, Neuroscan, Sterling, VA). The imaging data were
preprocessed and analyzed with SPM5 (Wellcome Department of
Imaging Neuroscience, UCL, London, UK) implemented on Matlab7
(MathWorks, Inc., Natick, MA). The first 4 volumes in each experimental
run were discarded to allow for T1 equilibrium effects. The remaining
functional images were corrected for differences in slice acquisition
timing and spatially realigned to the first image of the first run to adjust
for head motion. The realigned images were spatially normalized to fit
into a Montreal Neurological Institute template based on the standard
stereotaxic coordinate system. Subsequently, all images were smoothed
with an isotropic Gaussian kernel of 6-mm full-width at half-maximum.
The events representing onsets of TMS were modeled as a main
regressor for the first-level multiregression analysis. This analysis was
performed for each subject to test the correlation between hemodynamic signal changes and a train of delta functions (representing the
onsets of TMS) convolved with the canonical hemodynamic response
function and its temporal derivative. Six parameters representing the
head motion calculated in the realignment step were included in the
design matrix as covariates of no interest. Global signal normalization
was performed between runs. Low frequency noise was removed using
a high-pass filter with a cut-off of 128 s, and serial correlations were
adjusted using an autoregression model. By applying linear contrasts to
the parameter estimates, mean effect images reflecting the magnitude
of correlations between the hemodynamic signals and the behavioral
model of interest were computed. The summary images were used for
the subsequent second-level, random-effect model analysis.
Group-level statistical parametric maps (SPM) were produced by
performing one-sample t-tests for the contrast of the strongest,
suprathreshold stimulation (95--110% of machine output depending
on the availability) and the weakest stimulation (30% of machine
output in all subjects). In the group-level SPM, the threshold was
initially set at a voxel-wise height-level P < 0.001, and activity with
a cluster size of P < 0.05 corrected for multiple comparisons was
regarded significant. The cytoarchitectonic nomenclature of significant
brain activity was identified according to the SPM anatomy toolbox
(Eickhoff et al. 2005) when applicable.
To assess intensity-dependent modulation of hemodynamic signals,
brain activity was calculated from representative brain regions of
interest determined on an a priori basis. The percent signal changes in
hemodynamic signals was estimated in each region in each subject by
setting up 5-mm radius spherical VOIs with the Marseille region of
interest toolbox (http://marsbar.sourceforge.net/). The VOI-based
method was chosen to assess both linear and nonlinear aspects of
intensity-dependent modulation of brain responses. The VOIs were set
up according to the individual’s SPM from the contrast between the
maximum and the minimum intensity conditions. Hence, subjects who
did not reveal M1 activity in this contrast, known as ‘‘nonresponders’’
(Fox et al. 2006), were excluded from the group analysis. The VOIbased hemodynamic signal changes were then sampled from 9
representative areas, including the directly stimulated area (left M1),
remote motor areas (SMA, cingulate motor areas, and bilateral dorsal
lateral premotor cortex), somatosensory areas (left primary somatosensory cortex and bilateral second somatosensory cortices), bilateral
primary auditory cortices, left thalamus, and the right cerebellum.
Considering the size of the VOIs and the spatial resolution of the
experiment, the midline structures (SMA and cingulate zones) should
include data from both hemispheres. The left dorsal lateral premotor
cortex (PMd) in the precentral gyrus and primary somatosensory
cortex (S1) in the postcentral gyrus are very close to the left M1 and
likely to be under the influence of direct TMS stimulation to some
extent. Additionally, the left PMd and S1 have direct anatomical
connections with the left M1, and the left S1 should also receive sensory
afferents in the suprathreshold conditions. Therefore, interpretation of
the VOI-based data sampled from the left PMd and S1 requires caution
as the data may reflect complex interactions among these factors.
The signal changes were first evaluated as a function of the physical
intensity (% of default machine output) of TMS. A repeated-measures
analysis of variance (rmANOVA) was performed with a nonsphericity
correction (Greenhouse--Geisser) having the stimulus intensity (bin
width = 10% of machine output) as a within-subject variable. Pair-wise
comparisons were performed to test if activity for each bin of
the stimulus intensity was significantly greater than the activity for the
minimum stimulation (30% machine-output bin). In this analysis, the
100% machine-output bin was assessed with a separate rmANOVA,
because data were available from only 7 subjects.
Furthermore, TMS intensity was recalculated for each run for each
individual by taking individual’s rMT values into account. Percent
changes in hemodynamic signals were assessed with regard to this rMTadjusted, physiological intensity of TMS. These stimulus--response
profiles were analyzed at 2 levels: one included both sub- and
suprathreshold intensities (global-level analysis), whereas the other
only included subthreshold intensity (subthreshold-level analysis). At
the global level, curve fitting was performed with a sigmoid function
(Boltzmann) to capture the nonlinear stimulus--response relationship
between all levels of physiological TMS intensity and the hemodynamic
signals (Origin7.5, OriginLab, Northampton, MA). For this purpose, the
data were first pooled across all subjects. Next, data from each
individual were fitted with both sigmoid and linear functions. To avoid
irregular fitting, the point of inflection of the sigmoid fitting was
constrained to fall within ±10 of the value obtained in the pooled data
analysis. Each of these fitting analyses yielded the coefficient of
determination as a rough measure of goodness of fit. To find which
fitting could better explain the stimulus--response relationship in each
area, the coefficient of determination was statistically compared across
the 2 fitting analyses (Wilcoxon signed-rank test). At the subthreshold
level, hemodynamic responses to TMS with subthreshold intensity
(operationally defined as <80% rMT) were separately analyzed in each
area. At this level, only linear fitting was applied as informed by the
results from the global-level analysis.
Results
None of the subjects reported significant adverse side effects.
One subject was excluded because EMG analyses failed to
Cerebral Cortex November 2009, V 19 N 11 2607
detect MEPs, even in the supposedly suprathreshold TMS
conditions, possibly because of head motion after the fixation
of the TMS coil. Two more subjects were excluded from the
group analysis because they were ‘‘nonresponders’’ in whom
M1 activity was not detected during suprathreshold TMS in the
individual analysis at a liberal threshold (voxel-level P < 0.01
uncorrected). Hence, the results were based on data from 16
subjects. The range of stimulus intensities was between 30%
and 95% of the machine output for 9 subjects and between 30%
and 110% for 7 subjects.
The SSS combined with TMS yielded functional images of
satisfactory quality even in scans performed just after TMS
delivery (Fig. 1B). The image distortion and signal drop around
the TMS coil were minimal.
Motor-Evoked Potentials
Consistent with previous literature (Ridding and Rothwell
1997), the size of EMG responses became larger as the intensity
of TMS was increased during simultaneous TMS-fMRI measurement (Fig. 2A). Figure 2B illustrates the relationship between
the physical intensity, expressed as a percentage of machine
output, and the physiological intensity, expressed as percentage of rMT determined by standard MEP measurement within
the scanner. The mean rMT across all subjects was 85.4% (SD =
13.5) of the default machine output.
Group-Level Statistical Parametric Mapping
The overall effects of the suprathreshold M1 stimulation on
brain activity are summarized as group-level SPM reflecting the
contrast between stimulation with the maximum intensity (95/
110% of the default machine output depending on availability)
and that with the minimal intensity (30% of the default
machine output) (Table 1 and Fig. 3). The regions showing
significant activity included the left M1 (stimulated site), the
left S1, bilateral dorsal lateral premotor areas (PMd), the ventral
part of the SMA (SMAv) extending into the caudal cingulate
zone (CCZ), the rostral cingulate zone (RCZ), second
somatosensory area (S2), supplementary somatosensory areas
(SSA), the middle temporal gyrus, insula, thalamus, putamen,
and right anteromedial cerebellum. The left-lateralized activity
of the M1 and S1 centering on the ‘‘hand-knob’’ of the
precentral gyrus and the right-lateralized anteromedial cerebellar activity were consistent with activation of the somatotopic motor/somatosensory representation of the right hand.
The spatial localization of the present SMAv/CCZ regions also
corresponded to the hand representations of the SMAv and
CCZ (Hanakawa et al. 2008). Motor and somatosensory areas
with poorer somatotopy, such as PMd and S2, were activated
bilaterally. Additionally, there was activity in the auditory and
cognitive/affective regions, which included the bilateral
auditory cortices, hippocampus, prefrontal cortex, posterior
cingulate cortex, and middle temporal cortex. The right M1
contralateral to the stimulated side did not show significant
activity, but revealed a non-negligible tendency toward
increases in hemodynamic responses (x = 34, y = –32, z = 54;
T = 3.99) time-locked to the suprathreshold TMS.
In comparisons between the maximum and the minimum
intensity conditions, there was no activity significantly greater
during the minimum stimulation than during the maximum
stimulation. This meant that there was no significant deactivation associated with single TMS pulses during the suprathreshold
condition.
2608 Hemodynamic Responses during Single-Pulse TM
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Hanakawa et al.
Figure 2. (A) Intensity-dependent changes in MEPs recorded from a representative
subject in the MRI environment. (B) The relationship between physical intensity of
stimulation relative to the default maximum machine output (MO) and physiological
intensity of stimulation relative to the rMT is shown. The data are averaged across 16
subjects while the data for 100% MO are from 7 subjects only.
Evoked Hemodynamic Responses as a Function of
Physical TMS Intensity
The directly stimulated site, the left M1, showed monotonous
increases in brain activity (relative to the baseline) as a function
of the physical TMS intensity, represented as a percentage of
the default machine output (Fig. 4). When the physical
intensity of TMS was treated as a within-subject variable for
rmANOVA, significant effects of TMS intensity were evident in
the left M1 (P < 0.001). In the pair-wise comparison of brain
activity across different levels of stimulus intensity, M1 activity
was significantly increased only in the suprathreshold conditions (90% and 100% of the default machine output) as
compared with the 30% machine-output bin.
Table 1
Results from the group-level statistical parametric mapping analysis: activity associated with
suprathreshold TMS to the left primary motor cortex
Activity clusters
(functional anatomy)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
R inferior frontal gyrus
(Area 44/45)
R parietal operculum
(OP1/OP4)
R auditory cortex
R postcentral gyrus
(S1, Area 2)
R postcentral gyrus
(S1, Area 1)
L auditory cortex
L parietal operculum
(OP1/OP4))
L insula
L putamen
L middle temporal gyrus
R insula
R putamen
L postcentral gyrus
(S1, Area 2)
L precentral gyrus
(M1, Area 4)
L posterior cingulate cortex
R anteromedial cerebellum
R middle cingulate cortex (RCZ)
L superior parietal lobule
(S1, Area 1)
L precentral gyrus (M1/PMd,
Area4/6)
R precuneus
R thalamus
Cerebellar vermis
R hippocampus
Superior frontal gyrus
(SMAv, Area 6)
L middle cingulate cortex (SSA)
R paracentral lobule (SSA,
Area 3)
R middle temporal gyrus
R superior frontal gyrus
(SMAd, Area 6)
L superior frontal gyrus
(PMd, Area 6)
R middle frontal gyrus (PMd)
L thalamus
R precentral gyrus
(PMd, Area 6)
Volume (mm3)
Coordinates
x
T-value
y
Z
784
60
20
26
10.96
11 176
60
20
16
10.05
60
62
10
18
6
42
6.48
5.57
44
36
62
4.80
48
58
20
24
6
16
8.81
8.62
38
30
60
40
24
44
14
10
62
52
18
36
0
2
8
58
8
50
7.54
4.97
8.79
7.65
6.34
8.50
36
24
52
7.60
4
16
2
24
40
52
22
40
26
28
34
72
7.47
7.28
7.00
7.47
40
24
68
5.63
18
12
4
18
0
72
8
46
24
12
44
6
24
10
50
6.42
6.38
6.09
6.82
5.80
14
16
38
32
50
52
5.60
5.22
1096
168
60
2
54
18
2
70
5.23
5.05
280
26
6
66
4.91
536
200
184
38
10
28
6
14
22
58
8
72
4.69
4.72
4.60
16 584
3808
8960
3168
3608
6176
5128
4712
416
472
776
1040
1304
The effects of stimulus intensity on brain activity were
significant in all sampled regions of a priori interest (left PMd
P = 0.001, right PMd P = 0.001, left S1 P < 0.001, SMAv/CCZ P =
0.002, right cerebellum P < 0.001, RCZ P = 0.013, left S2 P =
0.002, right S2 P = 0.007, left thalamus P = 0.012, left auditory
cortex P < 0.001, right auditory cortex P < 0.001; all by rmANOVA
with nonsphericity correction) (Fig. 4). In the right PMd and
SMAv/CCZ, however, brain activity responded to the subthreshold stimuli as reported previously with rTMS (Bestmann et al.
2003, 2004; Fox et al. 2006). Activity sampled from the left PMd
also seemed to be increased at the levels below the motor
threshold. However, this activity increase did not reach statistical
significance as compared with activity in the 30% bin because of
large variance of the data. Moreover, the left S1 and right
cerebellum showed an almost linear pattern of intensitydependent modulation of brain activity, which seemed to be
gradually increased in response to the subthreshold stimulation. A
common characteristic of the stimulus--response profile in the
motor network, including both the directly stimulated and remote
areas, was almost no activity in the 30% machine-output bin.
The RCZ showed a stimulus--response profile resembling that
of the motor network in part, but its activity was mildly
increased in response to TMS with the minimal intensity.
Similarly, the nonprimary somatosensory areas (bilateral S2)
showed substantial activity in the 30% bin and prominent
increases in activity in the suprathreshold conditions. It seemed
that activity in the S2 and RCZ, most typically in the right S2,
primarily represented the states of stimulation (suprathreshold
TMS that evoked movement or subthreshold activity that did
not). The left thalamus showed a similar pattern. The auditory
cortices showed robust activity even in the 30% bin. In addition,
activity in the auditory cortices was very clearly modulated by
physical TMS intensity in a parametric fashion.
Evoked Hemodynamic Responses as a Function of
Physiological TMS Intensity
The stimulus--response profile was analyzed by reformatting
the data with regard to the rMT in each individual (Fig. 5). First,
a global pattern of stimulus--response profiles was investigated
Figure 3. Group-level statistical parametric mapping showing the categorical comparison of hemodynamic changes between the maximal stimulation condition at the
suprathreshold level (95--110% of the default machine output) and the control stimulation condition (30% of the default machine output).
Cerebral Cortex November 2009, V 19 N 11 2609
Figure 4. Stimulus--response profiles in the directly stimulated (left M1) and remote areas with regard to the physical intensity (percentage of the default machine output) of
TMS stimulation. An error bar represents the standard error of the mean. All regions showed a significant effect of stimulus intensity as shown by rmANOVA. Activity in each bin
was compared with that in the 30% bin (yP \ 0.05, zP \ 0.01, #P \ 0.001). M1 5 primary motor cortex, S1 5 primary somatosensory cortex, SMAv/CCZ 5 ventral
supplementary motor area/caudal cingulate motor zone, S2 5 second somatosensory area, RCZ 5 rostral cingulate zone.
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Hanakawa et al.
by including all levels of TMS intensity relative to the rMT
(Fig. 5A). In this global-level analysis, many areas showed
a mixture of linear and nonlinear components in the stimulus-response profile. A nonlinear feature was prominent in the left
M1 and S2, as evident in the curve fitting with a sigmoid function
(Boltzmann function). In these areas, the brain responses
showed a sharp increase around the rMT. Linearity of the
stimulus--response profile was rather pronounced in the SMAv/
CCZ and the right cerebellum, but fair fitting with a sigmoid
function, suggesting that a nonlinear component around the
rMT also existed in these areas. Notably, however, the
hemodynamic responses in the SMAv/CCZ and cerebellum
appeared to be almost linearly increased below the subthreshold level of intensity. Fitting with a sigmoid function
apparently failed to capture these changes occurring at the
subthreshold stimulation level. Therefore, these subthresholdlevel linear components were separately assessed, as described
later in the subthreshold-level analysis. In contrast to the above
motor/somatosensory areas, the nonlinear component was less
evident in the bilateral auditory cortices. To verify the
adequacy of applying sigmoid fitting to the global-level analysis,
the proportion of data variance explained by fitting was
compared between sigmoid fitting and linear fitting. For this
purpose, each fitting was performed by using all of the
stimulation conditions in each individual. The resultant coefficient of determination was used as a summary variable of
goodness of fitting and fed into the group-level nonparametric
statistics (Wilcoxon signed-rank test). It was shown that the
sigmoid fitting better explained the data than the linear fitting
in the M1 (P = 0.017, 46.4% of data variance explained by
sigmoid fitting and 32.2% by linear fitting), SMA/CCZ (P =
0.002, 36.9% by sigmoid fitting and 25.1% by linear fitting),
and S2 (P = 0.002, 35.9% by sigmoid fitting and 18.8% by linear
fitting). In the right cerebellum, however, no difference was
found (P = 0.88) between sigmoid (26.4%) and linear fittings
(25.3%). In the left auditory cortex, although data variance
tended to be better explained by linear fitting (35.5%) than
sigmoid fitting (25.0%), the difference did not reach statistical
significance (P = 0.08).
Finally in the subthreshold-level analysis, the evaluation of
the stimulus--response profile was limited to the subthreshold
condition (intensity < 80% of rMT). Because this analysis was
meant to assess linear increases in the hemodynamic signals at
the subthreshold level, fitting was performed only with a linear
function. In response to subthreshold stimulation, many areas
showed a linear increase in brain activity as a function of
physiological intensity (Fig. 5B). This linear increase in
hemodynamic signals at subthreshold-level stimulation was
statistically significant in the SMA/CCZ, right cerebellum,
auditory cortex, and, importantly, also in the directly stimulated
left M1. The only exception was the right S2.
Discussion
The present results have revealed both linear and nonlinear
aspects in the stimulus--response relationship between the
intensity of single TMS pulses and evoked hemodynamic
responses in the directly stimulated and remote motor/
somatosensory network. These results not only replicated
previous findings from a TMS-EEG study (Komssi et al. 2004),
but also identified multiple sources of linear and nonlinear
neural responses in the motor/somatosensory network.
A couple of imaging studies have addressed the issue of a TMS
intensity-hemodynamic response profile, using rTMS (1--4 Hz)
with a train of at least 10 pulses (Bestmann et al. 2003; Speer
et al. 2003; Fox et al. 2006). It should be remembered that rTMS
modulates cortical excitability in a complicated manner as an
interaction among stimulus frequency, intensity, and length of
pulse trains. Indeed, a few TMS-fMRI/PET studies examining the
effects of the length of pulse trains or stimulus frequency have
produced conflicting results. When brain activity was assessed as
a function of the length of pulse trains, a TMS-fMRI study
reported a linear increase in hemodynamic signals (frequency
1 Hz, intensity 120% rMT) (Bohning et al. 2003), whereas a TMSPET study found a linear decrease in blood flow (frequency 1 Hz,
subthreshold intensity) (Paus et al. 1998). Another TMS-PET
study found a linear increase in blood flow as a function of the
stimulus frequency (1--5 Hz) of a continuous rTMS with
subthreshold intensity (Siebner et al. 2001). The discrepancy
can be partly explained by differential effects of rTMS on cortical excitability, depending on whether they are delivered
continuously or intermittently (Huang et al. 2005).
The present study employed single TMS pulses at
a frequency <0.2 Hz, which less likely had carry-over effects
on cortical excitability (Chen et al. 1997). Our study covered
the widest range of intensities ever studied using the
concurrent TMS-fMRI/PET method, as it seemed possible that
the range of intensities used in previous studies might not be
sufficiently wide to delineate the full picture of the stimulus-response profile. The present study should thus reveal one of
the most fundamental forms of the stimulus--response profile,
perhaps along with a study examining EEG responses during
single-pulse TMS (Komssi et al. 2004). A common finding
between that study and the present one was that of both linear
and nonlinear components in the relationship between the
intensities of single TMS pulses and evoked brain responses.
The present study indicates for the first time that this effect can
be approximated by a linear function of stimulus intensity at
the subthreshold level, but nonlinear components emerge at
the levels of stimulus intensity around the motor threshold.
These findings implicate that even single TMS pulses may
influence neural activity in the remote motor/somatosensory
areas in both linear and nonlinear fashions, depending on the
stimulus intensity. These lines of evidence should help refine
interpretation of the effects of single TMS pulses on behavior
and MEP.
Stimulus--Response Profile in the Motor and Sensory
Networks
The cortical motor areas, including the left M1, SMAv/CCZ, and
bilateral PMd, commonly demonstrated an almost monotonous
increase in activity as a function of physical TMS intensity. Also
in common, these directly stimulated and remote motor areas
showed almost no activity during TMS with the lowest intensity
studied here (30% of the default machine output). The directly
stimulated M1 revealed significant activity only in the suprathreshold conditions relative to the minimal intensity condition.
However, remote motor areas except for the left PMd showed
significant activity, even during subthreshold stimulation, relative to the minimal intensity condition. Previous TMS-fMRI/PET
studies with M1 stimulation have already pointed out that
subthreshold TMS activates remote motor regions, but not the
directly stimulated M1 (Bestmann et al. 2003, 2004; Fox et al.
Cerebral Cortex November 2009, V 19 N 11 2611
Figure 5. (A) Global-level analysis of stimulus--response profiles as fitted with a sigmoid function. Stimulus intensity is expressed as the physiological intensity (% of
rMT) of TMS stimulation. All the sub- and suprathreshold stimulus conditions were taken into account. Nonlinearity is evident at around 100% of the rMT in the
directly stimulated left primary motor cortex (M1) as well as in the SMAv/CCZ, and the right second somatosensory area (S2). The left auditory cortex showed an
2612 Hemodynamic Responses during Single-Pulse TM
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Hanakawa et al.
2006). Activity in the M1 was only detected during suprathreshold TMS (Baudewig et al. 2001; Bestmann et al. 2003,
2004; Fox et al. 2006). These observations have led the
researchers to hypothesize that activity in the stimulated M1
mainly reflects afferent sensory information from the twitched
muscles. However, the sensory afferent theory may not be the
sole explanation for the behavior of the directly stimulated M1
activity. A parametric-design PET study with 1-Hz rTMS showed
increases in M1 activity during subthreshold stimulation (80% or
90% rMT), although the activities were clearly smaller than those
during suprathreshold stimulation (Speer et al. 2003). During
median nerve stimulation inducing clear twitching of hand
muscles, many imaging studies only reported activity in the
contralateral S1 (see e.g., Del Gratta et al. 2000; Ferretti et al.
2007), although a limited number of studies reported M1 activity
in addition to much larger S1 activity (Spiegel et al. 1999).
Finally, a similar phenomenon (activity in the directly stimulated
region only during suprathreshold stimulation) is also observed
in the prefrontal cortex (Nahas et al. 2001) and the PMd
(Bestmann et al. 2005), where TMS induces no movement.
With rTMS protocols, an increase in cerebellar activity
contralateral to the stimulated M1 was previously reported in
response to suprathreshold- and threshold-level stimulation
(Speer et al. 2003; Bestmann et al. 2004), whereas a recent
study found linear decreases in cerebellar activity as a function
of stimulus intensity (Fox et al. 2006). This discrepancy might
result from a complex interaction among the stimulus parameters of rTMS. In the present single-pulse TMS-fMRI study, the
stimulus--response profile of the right anteromedial cerebellum
resembled that of the M1. It is tempting to assume that
the cerebellar activity reflects not only the afferents from the
muscles, but also remote effects of M1 stimulation, because
there was a parametric increase in activity even in the
subthreshold condition. The cerebellar remote activity in
the suprathreshold condition could partly be ascribed to the
‘‘efference copy’’ of the motor commands from the M1 to the
spinal cord.
The S2 in either hemisphere revealed mild activity during
subthreshold stimulation, including stimulation with 30% of the
machine output and much enhanced activity during suprathreshold stimulation. The enhanced suprathreshold activity
was consistent with the roles of the S2 in analyzing sensory
afferents. The similar pattern of stimulus--response profile was
observed in the RCZ and the left thalamus, which could
partially reflect cognitive/affective components resulting from
TMS stimulation. This interpretation is consistent with the
widespread activity in the cognitive/affective regions including
the prefrontal cortex and the hippocampi. Meanwhile, whereas
most of the sampled areas showed parametric activity increases
in the subthreshold stimulation, the right S2 did not (Fig. 5B). It
appeared that the right S2 coded the state of stimulation:
stimulation without muscle twitches or stimulation with
muscle twitches.
Previous concurrent TMS-fMRI/PET studies often reported
activity in the auditory cortex (Bestmann et al. 2004, 2005;
Bohning et al. 1998, 2000; Siebner et al. 1998). Click sounds
associated with TMS pulses were especially pronounced because
of the much stronger force exerted on the TMS coil in MRI
environments compared with non-MRI environments. The
vibration of the coil and the loudness of click sounds should
be a function of TMS intensity, and activity in the auditory
cortices was almost linearly increased in both the physical and
physiological intensity analyses. Activity in the middle temporal
gyrus is consistent with previous findings during suprathreshold
TMS to the M1 (Bestmann et al. 2004) or to the PMd (Bestmann
et al. 2005), but its significance is not clear.
Because of the reasons explained in the method section,
interpretation of activity sampled from the left PMd and S1 is
only speculative. The interaction between the remote and
direct effects of TMS may partly explain the variability of the
data in the left PMd. Although the left S1, which should process
somatosensory information caused by muscle twitch, was
highly activated in the suprathreshold conditions as expected,
it also demonstrated significant activation in the subthreshold
conditions. Subthreshold-level activity in the left S1 could
primarily reflect remote effects as it closely resembled the
pattern observed in the SMA/CCZ and the cerebellum. The
stimulus--response profile in the right M1, which may show
remote activity through the transcallosal connection with the
stimulated M1, also seems interesting. This analysis was not
reported as the right M1 activity did not reach significance in
the group-level SPM analysis, although it was moderately
increased during suprathreshold single TMS pulses with the
present stimulus protocol. This finding can be contrasted to
previous reports of decreased contralateral M1 activity with
rTMS protocols (Baudewig et al. 2001; Bestmann et al. 2003,
2004; Fox et al. 2006), suggesting the dependency of
TMS-induced hemodynamic changes on stimulus protocols.
Possible Sources of Linear and Nonlinear Aspects of
Stimulus--Response Property
The dose--response profile of the M1 activity clearly exhibited
a nonlinear component, which was a sharp rise in activity
starting around the rMT. As a similar activity rise was observed
in the S2, it is likely that the nonlinear component at least
partly reflected sensory afferents. However, a milder degree of
nonlinearity was also observed in the SMAv/CCZ, in which
activity started to rise gradually from the subthreshold level.
This difference in the stimulus--response profile between the
directly stimulated and remote motor areas is consistent with
previous observations that the remote areas revealed activity
with weaker stimulation than did the directly stimulated M1
(Bestmann et al. 2003, 2004).
Now, the question is what the sources of the nonlinearity in
the directly stimulated and remote areas might be. Another
point requiring attention is that both the directly stimulated
and remote areas revealed a mild increase in activity as a linear
function of subthreshold-level intensity (see Fig. 5B). The
profile in the right S2 (that is, no parametric changes during
subthreshold stimulation) does not support the idea that such
stimulus--response profiles during subthreshold stimulation can
solely be explained by changes in attention levels related to
larger clicks. It is hence probable that at least some of the
almost linear stimulus--response profile. The gray dots represent a single data point from each stimulus-intensity condition from each subject. (B) Subthreshold-level
analysis of physiological intensity-response profiles as fitted with a linear function. All areas except the right S2 showed a mild yet significant increase in activity as
a linear function of stimulus intensity. The gray dots represent a single data point from each stimulus-intensity condition from each subject.
Cerebral Cortex November 2009, V 19 N 11 2613
aforementioned linear activity increases during subthreshold
stimulation truly reflect direct and remote effects of M1. This
idea is consistent with recent findings from an invasive corticocortical evoked potential study in which subthreshold electrical stimulation to the M1 induced responses in remote motor
areas, including the SMA (Matsumoto et al. 2007).
A following idea could explain the observed behavior of
brain activity in the directly stimulated and remote motor areas
in the present study. Single TMS pulses induce a sequence of
excitatory and inhibitory neuronal processes locally in the
stimulated region in response to a wide range of stimulus
intensities, including subthreshold levels (Moliadze et al. 2003).
It may be that, below the threshold, the excitatory activity does
not surpass the inhibitory activity to activate long projecting
neurons to the spinal cord. Around the threshold, the
excitatory processes would become predominant and start to
depolarize a larger number of long projecting neurons. This
recruitment process is conceivably nonlinear, provided that the
depolarizing threshold of each long projecting neuron is
distributed normally around the rMT. This hypothesis would
expect induction of both the direct and remote activities in
a nonlinear fashion. Furthermore, with hemodynamic measurement, activity can be detected more easily in the remote areas
than the directly stimulated area because 1) hemodynamic
signals largely reflect neural inputs to a particular region in
addition to local spiking activity (Logothetis et al. 2001), and 2)
remote activity, perhaps induced by release of neurotransmitter of transcortical neurons, may consume more metabolic
resources than direct activity because energy for depolarizing
neurons is provided externally in the direct area, at least in part.
These considerations may account for the nonlinear component in the remote and directly stimulated areas from the
viewpoint of not only sensory afferents but also TMS-induced
neuronal changes.
Methodological Consideration
The present study has, for the first time, applied the SSS scheme
(Anami et al. 2003) to a concurrent TMS-fMRI study for
monitoring and recording of MEPs. Because the feasibility of
concurrent TMS-fMRI was first demonstrated by Bohning and
colleagues (Bohning et al. 1998), this innovative multidisciplinary mapping technique has provided new insight into direct and
remote actions of TMS. Online measurement of EMGs may
enable further technical advances in combined TMS-fMRI studies
(Bestmann et al. 2004, 2005). First, it is ideal to determine formal
rMT in a real experimental environment. The fact that rMT was
relatively high in the present setup can largely be explained by
the long cable between the TMS coil and the stimulator plus
difficulty in positioning the TMS coil within the MRI head coil. In
this regard, it is obvious that applying an rMT determined
outside the MRI is not ideal. Second, constant MEPs should
guarantee stable positioning of the TMS coil relative to the head
during the experiment. Finally, unintended movement or muscle
activity, which would influence both MEP and hemodynamic
signals, can be monitored.
It could be a matter for debate whether we can apply the
same hemodynamic response function to directly stimulated
and remote regions. A previous concurrent TMS-fMRI study
addressed this question and found a standard hemodynamic
response to a single TMS pulse consistently across the
stimulated M1 and auditory cortices (Bohning et al. 2000). In
2614 Hemodynamic Responses during Single-Pulse TM
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Hanakawa et al.
accordance with this finding, we used the standard hemodynamic response function for the SPM analysis and were able to
capture reasonable activity from all regions of interest. Then,
a VOI analysis, rather than a voxel-wise parametric approach,
was employed as both linear and nonlinear components of the
stimulus--response profile were of a priori interest.
In conclusion, the present study demonstrated for the first
time a detailed stimulus--response profile in the neural network
consisting of directly stimulated and remote activations induced during single TMS pulses, by combining MEP and
hemodynamic measurements at 3 Tesla. Single TMS pulses
evoked activity in the motor/somatosensory network and other
areas related to detection of TMS delivery. The stimulusintensity profiles revealed both linear and nonlinear components. The nonlinear increase in brain activity in the directly
stimulated M1 may be induced by the nonlinear recruitment of
neurons in addition to sensory afferents.
Funding
Grant-in-Aid for Scientific Research on Priority Areas (Integrative Brain Research 20019041) to T.H.; (20019023) to
T.M.; (20020013) to H.F.; Emergence of Adaptive Motor
Function through Interaction among the Body, Brain and
Environment (20033030) to T.H.; Strategic Research Program
for Brain Sciences (SRPBS) to T.M. from the Ministry of
Education, Science, Sports, Culture, and Technology of Japan;
Grant-in-Aid for Scientific Research (C) (18500239) to T.M.
from the Japan Society for the Promotion of Science; a Grant-inAid from the Takeda Science Foundation (2007) to T.H.; and
a research grant (2007) from Neurocreative Lab to T.M.
Notes
Conflict of Interest : None declared.
Address correspondence to Takashi Hanakawa, MD, PhD, Department of Cortical Function Disorders, National Institute of Neuroscience, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi,
Kodaira, Tokyo 187-8502, Japan. Email: [email protected].
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