1Motor Control Laboratory, Department of Woman and Child Health and 2Division of Human Brain Research, Department of Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
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ABSTRACT |
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Ehrsson, H. Henrik, Ers Fagergren, and Hans Forssberg. Differential Fronto-Parietal Activation Depending on Force Used in a Precision Grip Task: An fMRI Study. J. Neurophysiol. 85: 2613-2623, 2001. Recent functional magnetic resonance imaging (fMRI) studies suggest that the control of fingertip forces between the index finger and the thumb (precision grips) is dependent on bilateral frontal and parietal regions in addition to the primary motor cortex contralateral to the grasping hand. Here we use fMRI to examine the hypothesis that some of the areas of the brain associated with precision grips are more strongly engaged when subjects generate small grip forces than when they employ large grip forces. Subjects grasped a stationary object using a precision grip and employed a small force (3.8 N) that was representative of the forces that are typically used when manipulating small objects with precision grips in everyday situations or a large force (16.6 N) that represents a somewhat excessive force compared with normal everyday usage. Both force conditions involved the generation of time-variant static and dynamic grip forces under isometric conditions guided by auditory and tactile cues. The main finding was that we observed stronger activity in the bilateral cortex lining the inferior part of the precentral sulcus (area 44/ventral premotor cortex), the rostral cingulate motor area, and the right intraparietal cortex when subjects applied a small force in comparison to when they generated a larger force. This observation suggests that secondary sensorimotor related areas in the frontal and parietal lobes play an important role in the control of fine precision grip forces in the range typically used for the manipulation of small objects.
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INTRODUCTION |
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The precision grip
between the tips of the thumb and the index finger has developed in
primates for the manipulation of small and delicate objects
(Napier 1961). It requires independent finger movements
(Lawrence and Kuypers 1968
; Passingham et al.
1983
; Porter and Lemon 1993
) and a sophisticated
control of the small fingertip forces applied to the surface of the
object (Johansson 1996
; Johansson and Westling
1984
). An illustrative example of this control is when picking
a raspberry
too much force will crush the raspberry, too little
and it will slip away.
The precision grip configuration is highly dependent on cortical
control (Passingham 1993; Porter and Lemon
1993
). In a recent functional magnetic resonance imaging (fMRI)
study, we examined the cortical areas activated when healthy subjects
used a precision grip to apply well-controlled time-variant grip forces
to a fixed object under isometric conditions (Ehrsson et al.
2000
). This precision grip task was associated with bilateral
activity in a set of frontal and parietal areas in addition to the
primary motor cortex (M1). Several of these areas, i.e., the bilateral ventral premotor cortex (PMV, also engaging area 44), the rostral cingulate motor area (CMAr), the supramarginal cortex, the ventral lateral prefrontal cortex, and the right intraparietal cortex, were
either recruited exclusively or showed augmented activity when the
subjects used the precision grip as opposed to when they used a palmar
power grasp to perform a similar manipulative task. These differences
could reflect differences in the hand posture or higher demands imposed
when controlling small forces at the fingertip-object interface.
In the present study, we examined whether the cortical control of small
precision grip forces differs from the control of large forces when the
same grasp is used. In particular, we test the hypothesis that some of
the cortical regions associated with precision grips would be more
active during the employment of small fingertip forces than when
generating large grip forces. This hypothesis is grounded on
single-cell recordings in non-human primates that have demonstrated
that a larger number of corticospinal neurons modulate their discharge
rate for forces in the small force range than for larger forces
(Evarts et al. 1983; Hepp-Reymond et al.
1978
) and that some populations of neurons in frontal motor areas [M1, PMV, and primary somatosensory cortex (S1)] increase their
rate of firing as the precision grip force is decreased (i.e., there is
a negative correlation with force) (Hepp-Reymond 1988
;
Hepp-Reymond et al. 1994
; Maier et al.
1993
; Wannier et al. 1991
). There are also
studies in humans that indicate that the control of fine precision grip
forces is dependent on cortical mechanisms that can be impaired during
various neurological conditions (e.g., cerebral palsy, focal dystonia,
stroke, attention deficit/hyperactivity disorder) (Eliasson et
al. 1992
; Hermsdörfer and Mai 1996
;
Odergren et al. 1996
; Pereira et al.
2000
).
We used fMRI to measure the cortical activity when healthy subjects performed a precision grip task fulfilling one of two force conditions: a small grip force (3.8 N), representative of the forces that are typically used when manipulating small objects with precision grips in everyday situations (comparable to lifting a cup of coffee), or a large grip force (16.6 N) that represents a somewhat excessive force in this respect (comparable to lifting a 1.5-l soda bottle).
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METHODS |
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Subjects
Six healthy male subjects (21-28 yr) participated in the study.
They were all naive with regard to the specific purposes of the
experiments. All subjects were right-handed (Oldfield
1971) and all had given their informed consent. The Ethical
Committee of the Karolinska Hospital had approved the study.
General procedure and task
The subjects performed a precision grip task with two force conditions. A baseline condition in which the hand was relaxed was also included. The subjects rested comfortably in a supine position on the bed in the magnetic resonance (MR) scanner. The room was dark, and the subjects were instructed to keep their eyes closed. All subjects wore headphones to reduce noise and to present auditory cues. The extended right arm was oriented parallel to the trunk and supported up to the radial side of the hand to minimize movement (Fig. 1B). The subjects grasped a nonmagnetic immovable test object between the pulps of the thumb and the index finger (Fig. 1A). The test object had flat parallel contact surfaces 30 mm apart (covered with sandpaper; grit size, 180). Optometric transducers in the object allowed measurements of the grip forces normal (perpendicular) to the contact surfaces. The grip force was represented as the mean of the normal forces measured at the two grasp surfaces (400 samples/s). The data were stored and analyzed using the SC/ZOOM data-acquisition system (Physiology Section, IMB, University of Umeå, Sweden).
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To perform the precision-grip task, the subjects applied forces normal to the contact surfaces (grip force) cyclically, following the pace of a metronome that generated click sounds at 0.67 Hz. They increased the force, then maintained the grip force until the next click of the metronome (this interval is referred to as the static plateau period), at which point they first released the grip force completely and then immediately started to increase it again (thereby performing a complete force cycle). When they reached the force of 2 N (small force condition) or 16 N (large force condition), they received a brief weak vibrotactile pulse delivered tangentially to the contact surfaces (of 10-ms duration and with a force of less than 0.5 N). The subjects then applied a self-selected static grip force slightly above this force threshold. They were asked to reproduce the same force across the force cycles and not to generate forces that greatly exceeded the force threshold. Figure 1, C and D, illustrates the grip force profiles together with the auditory and tactile cues for the grip task for the two forces. During the baseline condition (baseline), the subjects held the thumb and index finger in weak contact with the contact surfaces almost without applying any grip force. They received the tactile pulses and heard the metronome sound (0.67 Hz) through the headphones exactly as they had in the grip task.
We selected the lower force level so that it would be representative of the small forces that are typically used when manipulating small objects with precision grips in everyday situations. The level of the larger force was chosen to represent a somewhat excessive precision grip force in this respect. A constraint for the large force level was that it had to be employed without muscular fatigue, general effort, or impaired performance. Pilot experiments showed that a target force of 16 N was appropriate.
Before the scanning commenced, the subjects practiced the grip task at both force levels for 15 min until they produced the requested grip force profiles. After the training, the subjects were able to keep up a conversation while performing the task, which suggests that it had been well learned.
After the scanning, we measured the grip-force during maximal voluntary
contraction (MVC) as the subjects grasped a standard dynamometer
(cylindrical handle, 30-mm diam) with a precision-grip (Nordenskiöld and Grimby 1993). A surface EMG
(Myo115-electodes with in-built 2000X preamplifiers, Liberty
Technology, Hopkinton, MA) was recorded in four subjects while they
performed the precision-grip task at the two force levels outside the
MR scanner. We recorded from the right biceps-brachii and deltoideus to
check for possible recruitment of proximal muscles of the arm, and the
left 1DI and AbPB to check for nonvoluntary synergistic movements of
the nonparticipating hand.
Kinetic analysis
The force data were analyzed using the ZOOM software (Department of Physiology, University of Umeå). Force cycles in which the subjects did not generate the requested time course for the forces were defined as incorrect. We analyzed the mean grip force and the variability of the grip force during the static plateaus of each grip cycle (mean ± SD for data pooled across subjects; see Fig. 1, C and D). The static plateau was defined as the period between the peak grip force after the dynamic force increase to the beginning of the force relaxation (defined as the local minima of the 2nd derivative of the grip force).
To measure the accuracy of the force generation, we analyzed the variability of the plateau grip force across force cycles (SD of the grip force for data pooled across subjects). To compare variability of the grip force in the two force conditions, we determined the coefficient of variation (i.e., the ratio SD/mean).
Brain imaging
fMRI was conducted on a 1.5 T scanner (Signa Horizon Echospeed,
General Electric Medical Systems) equipped with a head-coil. We
collected gradient-echo, echo-planar (EPI) T2*-weighted image volumes
with blood oxygenation level-dependent (BOLD) contrast (Kwong et
al. 1992; Ogawa et al. 1992
). The scanning
parameters were: echo time (TE) = 50 ms; field of view (FOV) = 22 cm; matrix size = 64 × 64; pixel size = 3.4 × 3.4 mm, and flip angle = 90°. Twenty contiguous axial slices of
3.4-mm thickness were collected in each volume. We selected slices from
the dorsal surface of the brain to cover the frontal and parietal
lobes. The cerebellum, brain stem, and part of the basal ganglia were
outside the field of view. A plastic bite bar restricted head
movements. A high resolution, three-dimensional gradient echo
T1-weighted anatomical image volume of the whole brain was collected
(3D-SPGR).
Functional-image volumes were collected in six separate runs, and for each run, a total of 104 volumes was collected. During each run, volumes were acquired continuously every 5000 ms (TR = 5 s) while the subjects performed the grip task or relaxed with the hand (baseline condition). The grip task was performed in periods of 25 s (5 volumes being collected in this time) alternated with baseline periods of 25 s. During each grip period, the subjects performed one force condition, and across periods, the two force conditions alternated. During each force condition an equal number of volumes was collected. To allow for T1 equilibration effects, four volumes were recorded immediately before each run; these were neither stored nor analyzed.
Data analysis and image processing
We used the publicly available software SPM-96 to analyze the
functional images (Welcome Dept. Cognitive Neurology, London, http://www.fil.ion.ucl.ac.uk/spm). The volumes were realigned, co-registered to each individual anatomical T1-weighted image (3D-SPGR)
and normalized to the stereotactic coordinate system of
Talaraich and Tournoux (1988) using the Montreal
Neurological Institute (MNI) template brain (Friston et al.
1995a
). Then the images were spatially smoothed with an
isotropic Gaussian filter of 8 mm full width at half-maximum (FWHM) and
temporally smoothed with a Gaussian kernel with a FWHM of 2.83 s.
To increase the sensitivity of the analysis and detect activity that
was present across the subjects, we analyzed the functional images from
the six subjects as a group (fixed effect model). We estimated the task
specific effects using the general linear model (GLM) with a delayed
boxcar wave form at each voxel (Friston et al. 1995b
,c
; Worsley and Friston 1995
). The fMRI data corresponding
to each run were modeled with regressors for the conditions and the
mean value using the standard model implemented in SPM-96. A high-pass filter (cutoff frequency, 0.005 Hz) was used to remove low-frequency drifts and fluctuations of the signal, and proportional scaling was
applied to eliminate the effects of global changes in the signal
(Holms et al. 1997
). The significance of the condition specific effects was assessed using Z statistics for every
voxel from the brain, and these sets of Z values were used
to create statistical images. Linear contrasts between the different
conditions were used to create these statistical images; these were
arbitrarily thresholded at a Z value of 3.09. From these
statistical images (known as activation maps), we report peaks (or
local maxima) of activity that, when corrected for multiple comparisons
for the whole brain volume, corresponded to P < 0.05 on the basis on a test of peak height (Friston et al.
1995c
). All clusters that are shown in the figures and
described in the text were also significant on the basis of a test for
the extent of the cluster (Poline et al. 1997
). To
localize activity that reflected the generation of the precision grip
task at both force levels we defined the contrast (small
baseline + large - baseline). This tests the main effect of the
precision grip task. We also examined the contrasts (small - baseline)
and (large - baseline). To localize changes in activity that
specifically reflected whether a small or large force was applied, we
used the contrasts (small - large) and (large - small), respectively.
For the brain regions that showed a force specific activation (i.e.,
activity detected when we contrasted the 2 force conditions), we only
report voxels that were active when the force condition was compared
with the baseline condition (at Z > 3.09 at each
voxel). By this mean, we focused on brain areas that showed stronger
activity while the hand was grasping than when it was relaxed. This
excluded the possibility that differences between the tasks merely
reflected different degrees of deactivation.
To exclude the possibility that the results obtained in the group
analysis (fixed effects model) were biased by one or two subjects only
exhibiting very strong effects (Friston et al. 1999), we
examined the activation patterns of each individual subject in a
descriptive analysis (reported in Table 2). We probed for increases in
BOLD contrast signals close to (within a sphere of 12-mm radius;
corresponding to the FWHM of the smoothness of the statistical images
as determined using SPM96) or at the location of the most relevant peak
activations from the group analysis. We concluded that the results
obtained in the group analysis were representative of the observations
made for individual subjects (see RESULTS).
Anatomical definitions and localizations
The anatomical localizations of the activations were related to the major gyri and sulci that were identifiable from an average image generated from normalized T2*-weighted images from each of the six subjects.
We used the terminology of Roland and Zilles (1996b) for
the functional areas of the cortical motor system, and we used the European Computerized Human Brain Data Base (ECHBD; Div. Human Brain
Research, Stockholm) (Roland and Zilles 1996a
) to define the location and extent of M1, S1, area 45, and area 44 in the standard
anatomical space. Arbitrary criterions were used for PMV, dorsal
premotor cortex (PMD), supplementary motor area (SMA), and the
cingulate motor areas (CMAs). The ECHBD is a digital three-dimensional brain atlas in which representations of microstructurally defined cytoarchitectural areas from 10 postmortem brains are available in the
standard anatomical format. The methods used for the anatomical delineation (Amunts et al. 1999
; Geyer et al.
1996
, 1999
), spatial transformations (Geyer et al.
2000
; Schormann and Zilles 1998
), and generation
of population maps of these cytoarchitectural areas have been described
in detail elsewhere (Roland and Zilles 1998
; Roland et al. 1997
) (SPM was used to match the ECHBD to
the MNI space). M1 was defined as the voxels where at least 3 of 10 post mortem brains (30% population map) had their area 4a or 4p; S1 was defined as the 30% population maps of areas 3a, 3b or 1 (we do not
differentiate between different cytoarchitectural areas within M1 or S1
because of the limited effective resolution of the statistical images
from the group analysis). Areas 44 and 45 were also defined as the 30%
population maps of these areas. By the SMA, we mean the cortex rostral
to area 4a on the medial side of the hemisphere above the cingulate
sulcus. The rostral border of the SMA was defined to be in the vertical
plane at y = +16 (Buser and Bancaud
1967
; Roland and Zilles 1996b
). Activations located in the SMA posterior to y = 0 probably
correspond to the classical SMA (or SMA-proper) (Picard and
Strick 1996
; Roland and Zilles 1996b
). The
lateral premotor cortex, divided into a dorsal (PMD) and a ventral
(PMV) portion, is located rostral to lateral area 4a (Geyer et
al. 1996
; Roland and Zilles 1996b
). The rostral
border of the PMD is not known. The PMV was defined as the cortex
posterior to area 44 and anterior to area 4a, i.e., the tentative
location of the ventral part of area 6. The border between the PMD and
the PMV was defined as a horizontal plane at z = +45.
The CMAs refer to the cortex lining the cingulate sulcus. Their
preliminary parcellation into a rostral part (CMAr) and a caudal part
(CMAc) were described in Roland and Zilles (1996b)
.
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RESULTS |
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Behavioral performance
In more than 99% of the force cycles, all subjects performed the precision-grip task according to the instructions at both force levels (small and large). There was no difference in the number of correct force cycles between the force conditions.
In the small force condition, the mean grip force during the plateau phase was 3.81 ± 0.28 N (mean ± SD for data pooled across subjects). In the large force condition, it was 16.6 ± 1.21 N.
For both conditions of the grip task, the variability of the grip force during the static plateau period across force cycles was relatively low, which indicates regular and consistent performance of both tasks. There was no difference in the coefficient of variation (SD/mean) of the plateau grip force across force cycles in the two conditions (7.3% in both force conditions). Thus the accuracy of the force production was similar for the two force levels.
The mean of the maximal voluntary contraction (total grip force MVC) was 73 N (range: 58-96 N) for the precision grip. Thus the force production was performed in the lower 40% range of the MVC. The surface EMG showed no consistent activity in the proximal muscles of the right arm (biceps and deltoideus) or in the first dorsal interosseous muscle (1DI) or abductor pollicis brevis muscle (AbPB) muscles of the left hand during any of the tasks.
Brain activations
PRECISION GRIP TASK VERSUS BASELINE CONDITION.
The regions of the brain with stronger activity when the subjects
performed the precision grip task at both force levels (main effect of
the precision grip task) compared with the baseline condition
(large baseline + small - baseline) are shown in Table 1 and Fig.
2. The cerebellum, the brain stem,
and the lower parts of the basal ganglia and thalamus were outside the
field of view.
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SMALL FORCE VERSUS LARGE FORCE. The regions that displayed significantly stronger BOLD contrast signals when the subjects used the small precision grip force in comparison with when they generated the large force (small - large) are shown in Table 2 and Fig. 4 (P < 0.05 corrected for multiple comparisons).
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LARGE VERSUS SMALL.
The regions of the brain that exhibited significantly stronger BOLD
contrast signals when subjects applied the large force in comparison
with when they employed the small force are indicated in Table 2
and Fig. 5 (large - small)
(P < 0.05 corrected for multiple comparisons). The
left M1 and S1 showed such force specific activations with a maximum of
activity in the depth of the central sulcus. The active voxels of this
cluster extended rostrally into the PMD and posteriorly into the
anterior part of the intraparietal sulcus (the cluster extended from
y = 44 to y =
4 in the standard anatomical space). We also recorded positive force-related effects bilaterally into the PO. In addition, there were two areas with weaker
increases in activity located on the medial wall of the frontal lobe:
one in the most ventral part of the superior frontal gyrus (SMA;
x =
16, y =
8, z = 48; Z = 3.89, P < 0.25 after correcting for multiple comparisons) and one in the cingulate sulcus
(CMAc; x =
8, y =
24,
z = 40; Z = 3.94, P < 0.25 after a correction for multiple comparisons). The difference in
the activity in these areas did not attain the statistical criterion of
P < 0.05 after a correction for multiple comparison in
the whole brain space (P < 0.25 corrected).
Nevertheless we report this finding to show the correspondence with a
previous study (Dettmers et al. 1995
).
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DISCUSSION |
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The most important finding of the present study is that several sensory and motor related fronto-parietal areas were more strongly activated when a small precision grip force was applied to a stationary object than when a larger force was used. This result suggests that the bilateral cortex lining the inferior part of the precentral sulcus (area 44/PMV), CMAr, and the cortex lining the right intraparietal sulcus are involved in the control of small fingertip forces in the range typically used in manipulation.
Precision grip task
All subjects produced accurate force trajectories in the grip task at both force levels. The subjects had their eyes closed and did not move the digits. Thus the task used in the present study tests isometric fingertip force control guided by somatosensory feedback. The subjects had to control both the amplitude of the fingertip forces and the temporal sequence to produce proper cycles. The rhythm was paced by the metronome, and tactile signals from a brief vibration of the object provided feed back when the requested minimum force was reached. The same sensory cues were presented to the subjects at both force levels and in the baseline condition. Thus putative neuronal responses associated with these sensory signals were probably eliminated by comparing the two force conditions. Another possible confounding factor could have been increased recruitment of proximal muscles (shoulder, neck) when the larger force was applied. However, there was no consistent muscle activity of proximal muscles. Another issue relates to whether one of the force conditions was more difficult to perform and thus required more attention. We find no support for this concern because the grip task was well trained before the scanning (both force conditions), the subjects produced the requested force-trajectories at both force levels, and the variability of the grip forces in relation to the mean grip force (the coefficient of variation of the static plateau force) was similar during the two force conditions (7.3%).
Brain regions with stronger activity when generating the small precision grip force
Our results showing increased cortical activity in fronto-parietal
areas suggest that the control of small precision grip forces is
dependent on distributed cortical areas that are more active during
small than large grip forces. Support for this finding in humans comes
from recordings of neurons in the monkey motor cortex. These studies
showed that several M1 neurons tend to code for low forces in a limited
range, while relatively few neurons are found to be recruited
specifically at high force levels (Cheney and Fetz 1980;
Evarts et al. 1983
; Hepp-Reymond et al.
1978
). Furthermore Hepp-Reymond et al. (1978)
showed that during precision grips a larger number of cortical motor
neurons had a positive correlation between discharge rate and grip
force at low forces, than the forces were larger. Finally, during
precision grips, some populations of neurons in M1, S1, and PMV show
activity that is negatively correlated with force (Hepp-Reymond
et al. 1994
; Maier et al. 1993
; Wannier
et al. 1991
). Hence, our fMRI results obtained in human
subjects together with the single-cell recordings in monkeys suggest
that the cortical representation of small precision grip forces
involves strong activity of distributed populations of neurons in the
frontal and parietal lobes.
Another argument supporting increased neural activity when small forces
are applied can be raised from an ecological approach. The small force
(3.8 N) used in the present experiments is within the normal range of
the precision grip, while the large force (16.6 N) (comparable to
lifting a 1.5-l soda bottle) exceeds this range. Thus a speculative
possibility is that frequent use of finger forces within this smaller
force range will exert an "ecological pressure" to develop a rich
neural representation in this range (Nudo et al. 1996;
Sanes and Donoghue 2000
).
The increases in activity while generating small grip forces could also
reflect an additional recruitment of sensorimotor control mechanisms
due to a more sophisticated control of small forces during hand-object
interaction. When humans grasp objects with a fine precision grip, both
the direction and amplitude of the force vectors applied to the surface
of the object have to be well controlled (Johansson and Westling
1984), while the grasp automatically becomes more stable when
large forces are applied (the friction increases). The somatosensory
signals from the fingertips may also play a more important role when
applying fine forces than large forces. Indeed if the fingertips are
anesthetized, subjects lose their ability to conduct fine manipulation
and start to use excessive grip forces (Johansson and Westling
1984
; Roland and Ladegaard-Pedersen 1977
).
Furthermore neurons in the monkey primary motor cortex responded more
strongly when a somatosensory stimulus was applied during the
performance of fine finger movements than when the same stimulus was
applied during a more forceful movement (Fromm and Evarts
1977
). This indicates increased processing (central
gain control) of the somatosensory signals in sensorimotor areas during
fine force control.
Brain areas
PMV/AREA 44.
Previous positron emission tomography (PET) and fMRI studies suggest
that the cortex on the inferior part of the precentral gyrus and the
cortex lining the inferior precentral sulcus (PMV/area 44 region) are
active when healthy subjects use their right hand to manipulate objects
(Binkofski et al. 1999; Ehrsson et al.
2000
; Kawashima et al. 1998
; Seitz et al.
1991
). The pattern of activations in these studies could
reflect the movement of the digits, the hand posture, or the fingertip
force control. Therefore it is interesting that we could show here that
the bilateral cortex lining the inferior part of the precentral sulcus
was specifically activated in association with the control of small
isometric forces applied between the fingertips. In general terms,
these results are consistent with recent anatomical and
electrophysiological studies in non-human primates (Gentilucci
et al. 1988
; Kurata 1989
; Preuss et al.
1996
), which show multiple representations of the distal
forelimb in the PMV region (parts of which might be homologous with
human area 44 according to some researchers) (e.g., Rizzolatti and
Arbib 1998
), and that neurons in the rostral PMV region (area
F5) are active during specific grip tasks, e.g., while grasping small
objects with a precision grip (Rizzolatti et al. 1988
).
ROSTRAL CINGULATE MOTOR AREA (CMAr).
Electrophysiological and anatomical studies in non-human primates
(Dum and Strick 1991; He et al. 1995
;
Shima et al. 1991
) and functional imaging studies in
humans (Grafton et al. 1993
; Jahanshahi et al.
1995
; Kawashima et al. 1996
; Larsson et
al. 1996
; Picard and Strick 1996
) suggest the
existence of motor representations of the hand in the cortex lining the
cingulate sulcus rostral to the anterior commissure line in standard
anatomical space (Talaraich and Tournoux 1988
). The
present CMAr activation specific for the small grip forces seemed to
engage this "hand section" of this area (the cluster of active
voxels extended from y = +4 to y = +18
in the standard anatomical space). Thus this observation suggests that
the CMAr could be especially involved in force control during fine-skilled precision grip actions. More speculatively, the activity could also reflect a suppression of the motor output to keep the low
force level (Krams et al. 1998
).
INTRAPARIETAL CORTEX.
The human posterior parietal cortex (PPC) has been regarded as
a multimodal association area involved in a variety of cognitive functions. However, experiments in primates suggested that the PPC is
involved in higher-order sensorimotor integration during the planning
and execution of goal-directed actions (Andersen et al.
1997; Mountcastle et al. 1975
). Multiple
parallel parietofrontal circuits connect the posterior parietal lobe
with the frontal motor areas (Rizzolatti et al. 1998
).
The present study demonstrates that the activity increased in an
anterior section of the cortex lining the right IPS when subjects
employed a small precision grip force to the object. The same section
of the right intraparietal cortex (as determined from the Talaraich
coordinates) was also more active during isometric force production
with a precision grip (right hand), than during a power grasp
(Ehrsson et al. 2000
). It also showed stronger activity
when objects with complex rather than simple shapes were explored by
hand (using either hand) (Binkofski et al. 1999
). Thus
the present study adds to these previous observations in that it
indicates that the right anterior intraparietal cortex is involved in
somatosensorimotor integration required for the control of fine
fingertip forces during object manipulation.
Brain regions with stronger activity when generating the large precision grip force
We expected that contralateral M1 and S1 would show stronger
activation when the subjects applied the large precision grip force in
comparison to when they employed the small force (Dettmers et
al. 1995, 1996
; Kinoshita et al. 2000
;
Thickbroom et al. 1998
; Wexler et al.
1997
). And indeed, the contralateral M1 and S1 and the
bilateral PO did show such positive force related effects. The
increased BOLD signals in the M1 presumably reflect an increased overall synaptic activity in this area caused by increased firing of
corticospinal neurons and other neuronal elements. In man, the S1 and
PO is activated by tactile stimuli applied to the contralateral hand
(Burton et al. 1997
; Disbrow et al. 2000
;
Ledberg et al. 1995
). Thus the activation of these areas
could reflect increased somatosensory feedback arising from increased
compression of the densely innervated pulp of the fingertips in
conjunction with increased tension of the tendons.
Conclusions
There are several implications for the novel finding of increased
fronto-parietal activity when subjects employ small precision grip
forces. First, it demonstrates that the sensorimotor control mechanisms
associated with the generation of small fingertip forces is dependent
on distributed cortical regions in both hemispheres in addition to the
contralateral M1. Second, it suggests that the relationship between
muscular force and the general pattern of human brain activity is more
complex than has previously been described (Dettmers et al.
1995, 1996
; Kinoshita et al. 2000
; Thickbroom et al. 1998
; Wexler et al.
1997
). Finally, it suggests that the brain activity during
object manipulation does not merely reflect the grasp configuration
used (e.g., precision or power grasp), but that the activation in some
areas is increased when small forces are applied at the
fingertip-object interface.
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ACKNOWLEDGMENTS |
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The authors especially thank Dr. Göran Westling (Dept. Physiology, Umeå University) for technical development of the MR-grip instrument and the optical transducers. We are also grateful for the cytoarchitectural data provided by Dr. Stefen Geyer, Dr. Katrin Amunts, and Prof. Karl Zilles (Dept. of Neuroanatomy and C. and O. Vogt Institute for Brain Research, University of Düsseldorf, Düsseldorf, Germany). We thank T. Jonsson (MR Center, Karolinska Institute) and G. Ehrsson for technical assistance. Finally, we appreciate valuable discussions with Prof. Per Roland (Dept. Neuroscience, Karolinska Institutet) and Prof. Roland Johansson (Dept. Physiology, Umeå University).
This work was supported by Axel and Margaret Ax:son Johnsson's foundation and the Swedish Medical Research Council (Project 5925). H. H. Ehrsson was supported by Stiftelsen Sunnerdahls Handikapp Fond, Stiftelsen Frimurarna Barnhuset, and Sällskapet Barnavård.
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FOOTNOTES |
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Present address and address for reprint requests: H. H. Ehrsson, Neuropediatrics Unit, Dept. of Women and Child Health, Astrid Lindgren Hospital, 171 76 Stockholm, Sweden (E-mail: Henrik.Ehrsson{at}neuro.ki.se).
Received 13 October 2000; accepted in final form 9 February 2001.
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REFERENCES |
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