1Department of Neuroscience, Division of Human Brain Research, The Karolinska Institute, 171 77 Stockholm, Sweden; 2Institute of Equilibrium Research, Gifu University School of Medicine, Gifu 500; 3Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980, Japan; 4Department of Neuroanatomy and C. and O. Vogt Institute for Brain Research, University of Düsseldorf, D-40001 Düsseldorf; and 5Institute of Medicine, Research Center Jülich, D-52425 Jülich, Germany
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ABSTRACT |
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Naito, Eiichi, Shigeo Kinomura, Stefan Geyer, Ryuta Kawashima, Per E. Roland, and Karl Zilles. Fast Reaction to Different Sensory Modalities Activates Common Fields in the Motor Areas, but the Anterior Cingulate Cortex is Involved in the Speed of Reaction. J. Neurophysiol. 83: 1701-1709, 2000. We examined which motor areas would participate in the coding of a simple opposition of the thumb triggered by auditory, somatosensory and visual signals. We tested which motor areas might be active in response to all three modalities, which motor structures would be activated specifically in response to each modality, and which neural populations would be involved in the speed of the reaction. The subjects were required to press a button with their right thumb as soon as they detected a change in the sensory signal. The regional cerebral blood flow (rCBF) was measured quantitatively with 15O-butanol and positron emission tomography (PET) in nine normal male subjects. Cytoarchitectural areas were delimited in 10 post mortem brains by objective and quantitative methods. The images of the post mortem brains subsequently were transformed into standard anatomic format. One PET scanning for each of the sensory modalities was done. The control condition was rest with the subjects having their eyes closed. The rCBF images were anatomically standardized, and clusters of significant changes in rCBF were identified. These were localized to motor areas delimited on a preliminary basis, such as supplementary motor area (SMA), dorsal premotor zone (PMD), rostral cingulate motor area (CMAr), and within areas delimited by using microstructural i.e., cytoarchitectonic criteria, such as areas 4a, 4p, 3a, 3b, and 1. Fields of activation observed as a main effect for all three modalities were located bilaterally in the SMA, CMAr, contralateral PMD, primary motor (M1), and primary somatosensory cortex (SI). The activation in M1 engaged areas 4a and 4p and expanded into area 6. The activation in SI engaged areas 3b, 1, and extended into somatosensory association areas and the supramarginal gyrus posteriorly. We identified significant activations that were specific for each modality in the respective sensory association cortices, though no modality specific regions were found in the motor areas. Fields in the anterior cingulate cortex, rostral to the CMAr, consistently showed significant negative correlation with mean reaction time (RT) in all three tasks. These results show that simple reaction time tasks activate many subdivisions of the motor cortices. The information from different sensory modalities converge onto the common structures: the contralateral areas 4a, 4p, 3b, 1, the PMD, and bilaterally on the SMA and the CMAr. The anterior cingulate cortex might be a key structure which determine the speed of reaction in simple RT tasks.
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INTRODUCTION |
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Primates have three major motor zones: the primary motor zone, the
supplementary motor zone, and the premotor zone. Further subdivisions
of these zones have been prompted by recent anatomic and physiological
studies in monkeys and man (Roland and Zilles 1996). The
premotor zone (PM) is now subdivided into at least two areas, a dorsal
PMD and a ventral PMV (Barbas and Pandya 1987
; Crammond and Kalaska 1994
; Kurata and Hoffman
1994
; Matelli and Luppino 1992
; Matelli
et al. 1985
). Similarly a subdivision of the supplementary
motor zone into a pre-SMA and SMA proper has been proposed
(Luppino et al. 1991
; Matsuzaka et al.
1992
; Zilles et al. 1995
). In addition to the
three classic motor zones, a cingulate motor zone was described that
now is subdivided into a rostral cingulate motor area (CMAr), a caudal
cingulate motor area (CMAc) (Dum and Strick 1991
;
Matelli et al. 1991
; Shima et al. 1991
).
Many of these motor areas have neurons that fire when voluntary
movements are triggered by sensory stimuli. In the classical primary
motor zone MI, the same neurons can be triggered by somatosensory, visual and auditory stimuli (Lamarre et al. 1983
;
Salinas and Romo 1998
). In the SMA, some neurons fire to
all three modalities but with clear preferences for one sensory
modality (Tanji 1994
; Tanji and Kurata
1982
). In the PMV and PMD, the majority of neurons fire
nondifferentially with respect to sensory modality (Kurata and
Tanji 1986
). Little is known about the sensory preference of
neurons in the remaining motor areas. These studies raise the question
of how sensory information from different modalities address the motor
areas and which motor areas are active when a movement is triggered by
signals from different sensory modalities.
In humans, activations of what has been hypothesized to be MI, SMA, and
PM have been described during various types of voluntary movements,
although there have been no systematic studies of the activation of
various motor areas when simple voluntary movements are triggered by
different sensory signals. As far as subdivision of motor zones in
human is concerned, Dettmers et al. (1995), Jenkins et al. (1994)
, Kawashima et al. (1993)
,
Paus et al. (1993)
, and Stephan et al.
(1995)
have described activation of the cortex in or near the
cingulate sulcus. However, the human counterparts of the primate CMAr
and CMAc have not yet been identified due to lack of anatomic evidence.
Similarly the human counterparts of PMV, PMD, and pre-SMA are also
unidentified. First delineations of these areas based on combined
architectonic and transmitter receptor studies were reported recently
(Zilles et al. 1995
, 1996
). The human primary motor area
has been subdivided into two regions, areas 4a and 4p (Geyer et
al. 1996
). The present study was undertaken to examine which of
these many motor areas would be activated in coding a simple motor
output triggered by sensory signals from somatosensory, auditory and
visual modalities and which motor areas would be specifically active in
reaction to a signal from each sensory modality.
It is not clear yet which neural substrates determine the speed of reaction to stimuli. The length of the reaction time (RT) is determined by many factors, such as attention, complexity of stimuli, conduction time of the signal, and so on. For example, the RT is shorter when the subject pays attention to a stimulus and a choice RT is longer than a simple RT. The differences in RT between the sensory modalities set aside, it is uncertain whether further prolongation of the RT would be caused by the neuronal modulations in the sensory processing stage or in the motor output stage. We therefore also examined which neural structures would be involved in the speed of reaction in a simple reaction time task and whether these structures are engaged in the sensory processing stage or the motor output stage.
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METHODS |
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Subjects and physiological procedures
The study was approved by the Ethics Committee of the Karolinska
Hospital and the Radiation Safety Committee of the Karolinska Institute
and Hospital, and carried out following the principles and guidelines
of the Declaration of Helsinki 1975. Nine healthy male volunteers (aged
20-32 yr) participated in the study. They were all right-handed except
for one ambidextrous person. The subjects rested comfortably in a
supine position and had their heads fixed to the scanner by a
stereotaxic helmet (Bergström et al. 1981), which
also was used for fixation during the magnetic resonance imaging (MRI)
scan. Each subject had a catheter placed into the right brachial vein
for tracer administration and another inserted, under local anesthesia,
into the left radial artery for the measurement of arterial
radioisotope activity and partial pressure of arterial
CO2 (PaCO2). All subjects
had an electroencephalogram (EEG) recorded with four needle electrodes
located at the F3, F4, P3, and P4 positions according to the
international 10/20 system (reference at Cz). The degree of
-blockade in the EEG, indicating increased alertness, was assessed
as the time period of the PET measurement having faster activity than
14 Hz in the EEG channels from the posterior leads. All subjects had
predominant
rhythm in the rest state. Eye movements were recorded
with four silver-disk electrodes, placed at the outer orbital canthuses (reference at Cz). The arterial PaCO2 was
measured twice during each PET scan. The background illumination in all
conditions was 0.27 cd/m2. The subjects were
adapted by a 9-min exposure to this level before each PET scan. The
order of the rest and test conditions was randomized after a balanced
randomized schedule.
Activation tasks
Four PET measurements were made on each subject. These were rest, auditory reaction time (Aud-RT), somatosensory reaction time (Som-RT), and visual reaction time (Vis-RT).
In rest, as defined by Roland and Larsen (1976), each
subject was instructed to keep his eyes closed and not to move. The subject held a combined response key and somatosensory stimulator in
his right hand. The tip of the right index finger rested on a polyvinyl
plate in which a 11-mm-diam hole was drilled. The thumb in an opponent
position relative to the other fingers was resting on a mouse button
attached to the stimulator. The subjects received a warning 30 s
before the start of the injection of tracer that "the measurement
would start in 30 s." Before the actual measurement, sham
injections (no tracer) were made and all measurement procedures were
performed to habituate the subjects to the scanning conditions. In the
reaction time tasks, the subjects got a similar warning. Thirty seconds
later, 15O-butanol was injected and the reaction
time task started. This continued for 200 s.
In the auditory reaction time task, (Aud-RT), the subjects listened to a pure tone of 530 Hz (baseline) at 80 dB (sound pressure level) through earphones attached bilaterally inserted into the fixation helmet. The tone frequency changed abruptly to 1,530 Hz for 1,000 ms, after which the frequency returned to baseline for a time period of 1,000-3,000 ms. The subjects had their eyes open and fixated a 3° visual angle yellow monochrome circle 0.8 cd/m2 displayed on a video monitor. The task was to press the response key held in the right hand with the thumb as soon as possible. The movement was a simple thumb opposition.
In the visual reaction time task (Vis-RT), the subjects kept their eyes open and fixated the yellow circle described in the preceding paragraph. At random intervals ranging from 1,000 to 3,000 ms, the luminance of the circle suddenly increased to 14.5 cd/m2 for 1,000 ms. The task was to press the response key held in the right hand with the thumb as soon as possible.
In the somatosensory reaction time task (Som-RT), a 2-mm-diam stylus suddenly protruded through the 11-mm-diam hole and indented the tip of the right index finger. The rise time to maximal amplitude was 15 ms in free air. At interstimulus intervals ranging from 1,000 to 3,000 ms in a random manner, the stylus was not in contact with the skin, but suddenly, controlled by a solenoid, the stylus indented the tip of the index finger by 2.8 mm for 1,000 ms. During the somatosensory reaction time task, the subjects had their eyes open and fixated on the yellow circle. The task was to press the key as soon as possible when the subject felt the indentation on his right index finger.
In all reaction-time tasks, reaction times between 121 and 500 ms were
included in the analysis, reaction times >500 ms were discarded
(misses). The reason was that human subjects usually easily respond to
an external stimulus within 500 ms. The 500 ms was far longer than each
mean RT +3 SD (see Table 1). Because reaction times of <120 ms occur only as rare exceptions in adults (Woodworth and Schlosberg 1951), responses <120 ms were
classified as false alarms. The mean RT was calculated for 200 s
of the RT recording. In the three reaction time measurements, none of
the subjects broke fixation. The percent correct responses defined as
[total stimuli
(false alarms + misses)] × 100/total stimuli, are shown in Table 1. Thus the differences between the rest and the
reaction time conditions were open eyes, fixation on the yellow circle,
and the increased vigilance and attention.
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PET scanning, MRI scanning, and data processing
The methods for rCBF measurement were as described in a recent
study (Hadjikhani and Roland 1998). Each subject,
equipped with a stereotaxic helmet, had a magnetic resonance tomogram
and PET. The magnetic resonance tomogram was a spoiled gradient echo (SPGR) sequence obtained with a 1.5 T General Electric Signa scanner, TE = 5 ms, TR = 21 ms, flip angle = 50°, giving rise
to a three-dimensional (3D) volume of 128 × 256 × 256 isotropic voxels of 1 mm3 (field of view 256 mm).
The rCBF was measured with an eight-ring, 15-slice PET camera
(PC2048-15B Scanditronix) in plane spatial resolution of 4.5 mm and an
interslice distance of 6.5 mm. 15O-butanol (70 mCi) was injected intravenously as a bolus. The arterial input function
was monitored continuously, and the rCBF was calculated on the basis of
the data sampled from 20 to 80 s after injection (Roland et
al. 1993
). The sinograms were reconstructed with a 4-mm Hanning
filter. The reconstructed images were subsequently filtered with a 5-mm
3D isotropic Gaussian filter to yield a final full-width half-maximum
of 6 mm for the images.
The images were anatomically standardized with the Human Brain Atlas
(HBA) (Roland et al. 1994). Each individual's MRI of the brain was transformed to the standard anatomic format of the HBA,
and subsequently the PET images were transformed with the HBA to
standard brain format. The anatomically standardized images had a voxel
size of 2 × 2 × 2 mm3. Statistical
analysis was done with a general linear model (GLM) (Ledberg et
al. 1998
). The design matrix had subjects and tasks as factors.
The main effect of reaction time was contrasted to rest. Subsequently
the RT of one modality was contrasted to the two other modalities. Both
z threshold and cluster size for significant activations in
the whole brain (P < 0.05) were determined by 3,000 Monte Carlo simulations (Ledberg et al. 1998
). This
simulation provided the thresholds z = 2.58, and
cluster size = 712 mm3 in the whole brain.
Correlation coefficients were calculated between mean RT and rCBF voxel
by voxel in each task. A t-test was done according to the
null hypothesis that the correlation coefficients were equal to 0. The
t-image had lower degrees of freedom, hence only clusters
>800 mm3 having t >2.5 were significant.
The activations covering the sensory-motor cortices were examined for
localization within the objectively cytoarchitecturally defined
areas 4a, 4p, 3a, 3b, and 1 (Geyer et al. 1996;
Roland et al. 1997
; Schleicher et al.
1999
). The cytoarchitectural regions were delineated with
observer-independent techniques in 10 post mortem brains by the method
described in detail by Schleicher et al. (1999)
. The
areas were delineated in cell-body-stained coronal sections of the post
mortem brains. The brains were fixed in 4% formalin or Bodian's
solution, embedded in paraffin, serially cut into coronal sections 20 µm thick, and stained for cell bodies (Merker 1983
).
Before the histological procedures, high-resolution 3D FLASH MR images
with a voxel size of 1 × 1 × 1.17 mm were obtained from
each brain.
The borders of areas 4a, 4p, 3a, 3b, and 1 were determined on each 60th
section. The gray level index (GLI) was measured as an expression of
the volume density of cell bodies with a computer-controlled image
analyzer (Schleicher et al. 1999). Profiles of the GLI
were measured from the border between layers I and II to the
cortex/white matter boundary. These profiles covered the whole cortical
area (for example area 4a) tightly spaced (200 µm) and define the
cytoarchitecture in quantitative measures. The measured profiles at one
cross-laminar sampling line are compared statistically with the
neighboring profiles by the Mahalanobis distance measure
(Schleicher et al. 1999
). The Mahalanobis measure is a
distance measure for multivariate vectors (Mahalanobis et al.
1949
). Maximal distances occur between profiles that lie on
opposite sites of an areal border (Schleicher et al.
1999
). Borders between areas are defined at cross laminar planes where the Mahalanobis measure is significant (Hotelling's T2 test, P < 0.05)
(Schleicher et al. 1999
) (For other applications and
documentation of this method, see Amunts et al. 1996
;
Geyer et al. 1996
, 1997
; Larsson et al.
1999
).
In addition to defining the borders between areas from neuronal density
profiles, borders also were determined on the basis of densities of
muscarinic M2 receptors and serotonin-2 (5-HT-2) receptors with an
similar approach as described in detail in Geyer et al. (1996,
1997
). The T2 measure showed
statistically significance in exactly those places where significant
differences were found in the multivariate (Mahalanobis) measures of
neuronal densities (Geyer et al. 1996
, 1997
). In this way, areas 4a, 4p, 3a, 3b, and 1 were defined by objective statistical measures in 10 brains. The images of the histological sections of each
brain were corrected for distortions and shrinking during the cutting
and fixation by the software of Schormann et al. (1995)
and subsequently matched with the 3D FLASH MR images of the same brain.
Each cytoarchitectural brain image then was transformed into the
standard anatomic format of the HBA (Shormann et al. 1995
). Subsequently the functional (PET) images were
transformed into the standard anatomic format of the HBA. The accuracy
of the HBA software was described in Roland et al.
(1994)
. In this way, the cytoarchitectural brain images and the
cluster images showing the statistically significant activations were
transferred to the same 3D standard anatomic space.
The cytoarchitectural areas were filtered with a 5-mm Gaussian 3D
filter to have approximately the same spatial resolution as the cluster
images. The activated fields were then compared with the spatial extent
of each cytoarchitectural area defined as the 30% population map of
that area, i.e., the voxels in which that area can be found in 30% of
the postmortem brains (Roland and Zilles 1998). We
analyzed which population threshold would maintain the criterion that
adjacent cytoarchitectural areas which abut in individual brains should
also abut in the map of cytoarchitectural areas made from the
population maps. A 30% threshold was found to fulfil this criterion
without producing overlaps between adjacent areas. Thus each
cytoarchitectural area was represented as the volume corresponding to
the volume occupied by the 30% population map. Then the volumes of
intersection between clusters and cytoarchitectural areas were
calculated (Tables 2-4). The PMD, SMA, and CMAr were defined
preliminarily by Roland and Zilles (1996)
.
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RESULTS |
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Psychophysiological measurements
The degree of -blockade in the EEG was increased only during
the visual RT task, although the subjects had their eyes open in all
three tasks (Table 1; P > 0.2). The subjects fixated
the yellow monochrome circular spot in all three reaction time tasks. The electrooculogram (EOG) showed only 0.2-Hz eye blinks in all tasks.
There was no significant correlation between the percentage of
-blockade and the global cerebral blood flow (gcbf;
r =
0.06 for Aud-RT, r =
0.51 for
Som-RT, r =
0.39 for Vis-RT, respectively). Neither
was the global blood flow correlated with the percentage of correct
responses nor the RTs. The RTs in individuals followed the same pattern
as the mean RTs. One-factorial ANOVA was done. The ANOVA showed
significant differences between three RTs [F(2,12) = 4.14, P < 0.05]. A test by Ryan's method for
multiple comparisons among means showed the visual reaction times were
significantly longer than the auditory and somatosensory RTs
(t = 2.73, df = 12, P < 0.05 for
Vis-RT vs. Aud-RT; t = 2.15, df = 12, P = 0.053 for Vis-RT vs. Som-RT, respectively; Table
1). The distribution of reaction times of each of the three modalities
was normal (Gaussian) or slightly log-normal. In the calculation of
means and SD, we have assumed normal distributions. The longer RTs and
occasional misses occurred predominantly in the 10-s interval during
which the tracer was injected. In this case, we excluded all RT data within this time interval from the analysis.
Main effects of RT tasks
We examined the main effect of doing a reaction time task by
contrasting the Aud-RT, Vis-RT, and Som-RT relative blood flow measurements with the REST condition. Table
2 shows the two large active clusters
observed in all three RT modalities. One cluster covered the SMAs and
part of the CMAs bilaterally (Fig.
1B). The center of gravity was
at y = 0, meaning that both the caudal and rostral CMA
were presumably active according to the parcellation of Roland
and Zilles (1996). The other cluster covered the contralateral sensory-motor cortices (Fig. 1A). The large field in the
contralateral sensory-motor cortex engaged cytoarchitectural areas 4a,
4p, 3b, and 1. Rostrally it extended into the adjacent area 6 (Fig.
2). Caudally the field extended into the
adjacent cortex lining the postcentral sulcus and into the rostral and
superior part of the supramarginal gyrus. The somatosensory and visual
RT tasks also provided significant active fields in the same locations
when each RT was contrasted to the rest condition (Table
3).
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Activation patterns specific to each RT task
We also tested the hypothesis that there might be active fields in the motor areas that are associated specifically with only one RT modality. We compared the rCBF of a given RT modality with the rCBF of the other two RT modalities. Table 3 shows that auditory RT task bilaterally activated the auditory cortices and that the visual RT task activated the right visual association cortex; however, no specific regions were active in the somatosensory RT task. We could not find any modality specific significant activation in the motor areas.
Correlation between rCBF and RT
We tested the hypothesis whether the rCBF of some cortical areas
might be correlated with the RTs. For all RT modalities strong negative
correlations appeared as fields located in the anterior cingulate
cortex (ACC) (r = 0.95, df = 6, P < 0.01 for Aud-RT; r =
0.97,
df = 6, P < 0.01 for Som-RT; r =
0.93, df = 5, P < 0.01 for Vis-RT,
respectively; Figs. 3 and
4, Table 4).
The fields demonstrating the negative correlation in somatosensory RT
did not overlap with the fields associated with visual RT and auditory RT, neither did the fields of visual RT and auditory RT overlap. In
addition, there were some fields presumably specifically correlated with the Aud-RT, Som-RT, and Vis-RT in different parts of the prefrontal cortex. Table 4 shows the sizes and locations of these fields. Surprisingly mean rCBFs of the SMA cluster and the mean rCBF of
the SI-M1 cluster didn't show any strong correlation between the mean
RT in any of the RT tasks (Table 4).
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DISCUSSION |
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We have shown that simple RT tasks with reactions to somatosensory, visual, and auditory stimuli activated the contralateral (left) PMD, M1, SI, SMA, and CMA bilaterally. The large activation in the contralateral M1 and S1 engaged the hand regions of the cytoarchitectural areas 4a, 4p, 3b, and 1. Specific activations associated with each RT task appeared only in sensory association cortices and not in the motor areas. The rCBF in the anterior cingulate cortex showed significant negative correlation with the RT, but no such correlation was found in the motor areas.
In all RT tasks, the subjects viewed a yellow circle on a video monitor. In contrast, during the rest condition, the subjects had their eyes closed. This fundamental difference did seem to affect the cortical activation pattern because there was a small signal in visual area V1 (maximum Z value of 2.84 for Som-RT contrasted to REST and 3.65 for Aud-RT contrasted to the REST condition). This V1 signal was, however, not statistically significant with the cluster-size method. No visual association cortices were significantly active in the Aud-RT and Som-RT tasks. Because we had only four conditions per subject, but no repetitions, this could have reduced the sensitivity.
Because the subjects in all RT tasks held the response key in their
right hand, both in rest and during the RT tasks, the somatosensory and
motor activities associated with holding the response key should have
been cancelled out in the contrasts. However, because the subjects
responded to the stimuli by pressing the button with their right thumb,
the sensory-motor cortices should be activated somatotopically. The
active fields in the motor areas (SMA, PMD, M1, CMA) might be due to
the preparation for movement, motor set, and movement execution. The
present data do not permit one to distinguish among these possible
causes. The active fields in the primary somatosensory cortex (SI)
might be mainly due to the somatic feedback by pressing the response button. Widener and Cheney (1997) showed that
microstimulation of areas 3b and 1 did not produce significant
postspike facilitation in spike-triggered averages of EMG activity
during voluntary movement. This result suggested that motor output
effects from SI frequently were absent or very weak compared with those
of the primary motor cortex. Neurons in area 3b and 1 showed a
directionally tuned activity during active digit and arm movements
(Cohen et al. 1994
; Inase et al. 1989
;
Prud'homme et al. 1994
). We found activation in the
finger-hand representation (Roland 1987a
,b
) of
cytoarchitectural areas 4a, 4p (small), 3b, and 1. Areas 4a and 4p have
somatotopical representations of thumb (Geyer et al.
1996
) as have areas 3b and 1.
Activations in PMD and SMA
The activation in the premotor cortex can be classified as
belonging to PMD (Roland and Zilles 1996). The
activation of PMD as a main effect and the lack of any modality
specific RT activation in PMD is in accordance with a previous
single-unit study showing that the majority of neurons in the PMD fire
nondifferentially with respect to sensory modality (Kurata and
Tanji 1986
). Neurons of the PMD discharged more when a stimulus
instructs a limb movement than when the same stimulus instructs a shift
in spatial attention or memory (Wise et al. 1992
).
Set-related neurons, showing sustained activity during the delay period
after presentation of instruction signals, are predominantly located in
the PMD (Kurata 1993
; Kurata and Hoffman
1994
). Still other neurons in the PMD showed movement-related activity, which changed immediately before and during a movement, after
a trigger signal (Kurata 1993
; Kurata and Hoffman
1994
). From this one may speculate that the PMD activation was
related to the set- and/or movement-related neuronal activity but not by the attention to the stimuli.
The activation in the SMA is located in the SMA-proper (Roland
and Zilles 1996). Recently the human SMA-proper was subdivided into two regions: rostral part of the SMA (SMAr) and caudal part of the
SMA (SMAc) (Vorobiev et al. 1998
). The activation of SMA in the present study was located in the mid (y = 0)
part of the SMA (Roland and Zilles 1996
). However, this
location was suggested by Picard and Strick (1996)
on
the basis of a meta study of Talairach coordinates from different
imaging studies to be the "face" representation of SMA. Obviously
the claim of three medial motor areas above the cingulate sulcus,
pre-SMA, SMAr, and SMAc (Vorobiev et al. 1998
) must be
supported by other results such as differences in neuron or receptor
densities and by a complete (somatotopical) representation of the motor
apparatus in single subjects. Differences in the procedures for
bringing data into Talairach space may produce rather large variations
in centers of gravities or points of maximum activation (Roland
et al. 1997
). Direct stimulation of the SMA produce movements
of the hand and arm if the stimulation site is close to
y = 0 (Buser and Bancaud 1967
;
Chauvel 1976
).
The SMA activation extended into the cingulate sulcus in which several
cingulate motor areas presumably exist in humans (Picard and
Strick 1996) that are similar to the cingulate motor areas described in monkeys (Dum and Strick 1991
; Galea
and Darian-Smith 1994
; Luppino et al. 1991
;
Roland and Zilles 1996
; Shima et al. 1991
). The present activation was located at a site
predominantly activated by simple movements of the hand
(Dettmers et al. 1995
; Kawashima et al.
1996
; Larsson et al. 1996
; Schlaug et al.
1994
; Stephan et al. 1995
) or arm in the meta
study of Picard and Strick (1996)
. According to the
localization of the main effect cluster (Fig. 1B), the
activation was located mainly in the caudal part of the cingulate motor
zone, but a more definite parcellation of the human cingulate motor
zone is not yet available due to lack of anatomic and uniformly treated
high quality functional data.
Some neurons in the SMA in monkeys fire to all three modalities but
with a clear preference for one sensory modality (Matsuzaka et
al. 1992; Tanji and Kurata 1982
). SMA neurons
are more sensitive to the stimulus modality compared with PM neurons.
The present findings illustrate that in the SMA proper and the PMD, the
synaptic and neuronal activity associated with responses to sensory
signals is distributed roughly over the same part of the cortex, making it impossible to distinguish preferences in neuronal responses with
respect to sensory modality within these areas with PET (and fMRI).
The large main effect activation in the sensory-motor region
posteriorly extended into the uppermost and rostral part of the supramarginal gyrus. This part, laterally to the IPA functional area
(Roland et al. 1998) and posterior to the cortex lining
the postcentral sulcus (Bodegard et al. 1998
) has been
active in previous studies in which subjects were in somatosensory
contact with objects and made a manual response (Bodegard et al.
1998
; Hadjikhani and Roland 1998
; Ledberg
and Roland 1998
; Roland et al. 1998
;
Seitz et al. 1991
).
Activations in all three tasks
Our findings suggested that sensory information is processed in
each modality specific sensory association cortex and subsequently converges on the motor areas; SMA, CMA, PMD, 4a, and 4p. Neurons in the
M1, SMA, and PMD of other primates show set- and/or movement-related activities during limb movements. Zhang et al. (1997)
suggested that M1 belongs to a distributed network such that its neural activity reflects the underlying network dynamics that translate a
stimulus representation into a response representation via the activation and application of appropriate S-R mapping rule. It therefore seems reasonable to describe the activation of these fields
as due to input from other cortical areas and subcortical sectors
processing the sensory stimuli which are relevant in a motor context.
The auditory, somatosensory, and visual RT tasks activated nearly all
known subdivisions of the motor cortices despite the simplicity of the
motor task. This finding can be interpreted in two ways. 1)
All motor areas are being addressed by afferent synaptic input from
cortical and subcortical structures processing the sensory information.
And 2) active fields in the motor cortices arise as a
consequence of synaptic activity originating from the interconnections
between the motor areas themselves and the afferent input from
subcortical motor sectors. This explanation is to some extent favored
by current knowledge about the cortico-cortical connections of the
motor cortices for which only the somatosensory modality has direct
access to the primary motor cortex (areas 4a and 4p)
(Darian-Smith et al. 1993; Stepniewska et al.
1993
), whereas the premotor cortical zone has connections with
prefrontal, parietal and cingulate areas that might process sensory
information (Barbas and Pandya 1987
; Jones and
Powell 1969
; Jones et al. 1978
; Jürgens 1984
; Lu et al. 1994
;
Muakkassa and Strick 1979
; Pandya and Vignolo
1971
).
Correlation between rCBF in anterior cingulate and RT
We found active fields in the anterior cingulate cortex (ACC), the
superior frontal cortex, the orbitofrontal cortex, and the frontal pole
the rCBF of which showed significant negative correlation with the RTs.
The rCBF of the ACC was correlated particularly strongly with the RTs.
The greater the increase of the rCBF in the ACC, the faster the
response. Surprisingly, there was no such strong correlation between RT
and rCBF in the motor cortices nor in the sensory areas. The cortical
fields correlated with Vis-RT, Som-RT, and Aud-RT did not overlap,
indicating parallel access to this sector of the ACC for the three
senses. The three ACC fields of correlation did not appear as
significantly activated in the main effect contrast probably because of
the range of rCBF in these regions (Fig. 4). The three fields partly
overlapped the position of the field intersection reported in
Klingberg and Roland (1997). In that study, the same
part of the ACC was engaged in a simple auditory working memory tasks
and a simple visual working memory task. When the two tasks were
performed simultaneously, the RTs increased considerably
(Klingberg and Roland 1997
). The three fields were also
very close to the part of the ACC (1, 24, 24) in which the rCBF was
positively correlated with the rCBF in the medial thalamus and midbrain
tegmentum in a vigilance task (Paus et al. 1997
). Taken
together, this indicates a role of this particular sector of the ACC
(y = 15-26) in the speed of reaction. This sector
seems functionally associated with the midbrain reticular intralaminar
thalamic system, known to be modulating alertness and general attention
in awake subjects (Kinomura et al. 1996
).
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ACKNOWLEDGMENTS |
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The technical help of J. Pedersen and W. Pulka was greatly appreciated.
This study was supported by the Volvo Foundation, the Swedish Medical Research Council, and German Sonderforschungsbereich 194/Project A6. The correlations between cytoarchitectures and functional fields were funded by Biotech Grant Bio 96-0177 from the European Union. E. Naito was supported by the Brain Science Foundation and the Naito Foundation in 1997.
Present address of E. Naito: Faculty of Human Studies, Kyoto University, Sakyo-ku, Kyoto 606 8501, Japan.
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FOOTNOTES |
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Address for reprint requests: P. E. Roland, Department of Neuroscience, Division of Human Brain Research, The Karolinska Institute, Berzelius vaeg 3, 171 77 Stockholm, Sweden.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 15 January 1999; accepted in final form 28 September 1999.
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REFERENCES |
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