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Volume 16, Number 23,
Issue of December 1, 1996
pp. 7688-7698
Copyright ©1996 Society for Neuroscience
Primary Motor and Sensory Cortex Activation during Motor
Performance and Motor Imagery: A Functional Magnetic Resonance Imaging
Study
Carlo A. Porro1,
Maria
Pia Francescato1,
Valentina Cettolo2,
Mathew E. Diamond1,
Patrizia Baraldi3,
Chiara Zuiani2,
Massimo Bazzocchi2, and
Pietro E. di
Prampero1
1 Dipartimento di Scienze Tecnologie Biomediche e
2 Scienze Mediche Morfologiche, Università di Udine,
I-33100 Udine, Italy, and 3 Dipartimento di Scienze
Biomediche, Università di Modena, I-41100 Modena, Italy
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
FOOTNOTES
REFERENCES
ABSTRACT
The intensity and spatial distribution of functional
activation in the left precentral and postcentral gyri during actual motor performance (MP) and mental representation [motor imagery (MI)]
of self-paced finger-to-thumb opposition movements of the dominant hand
were investigated in fourteen right-handed volunteers by functional
magnetic resonance imaging (fMRI) techniques. Significant increases in
mean normalized fMRI signal intensities over values obtained during the
control (visual imagery) tasks were found in a region including the
anterior bank and crown of the central sulcus, the presumed site of the
primary motor cortex, during both MP (mean percentage increase, 2.1%)
and MI (0.8%). In the anterior portion of the precentral gyrus and the
postcentral gyrus, mean functional activity levels were also increased
during both conditions (MP, 1.7 and 1.2%; MI, 0.6 and 0.4%,
respectively).
To locate activated foci during MI, MP, or both conditions, the time
course of the signal intensities of pixels lying in the precentral or
postcentral gyrus was plotted against single-step or double-step
waveforms, where the steps of the waveform corresponded to different
tasks. Pixels significantly (r > 0.7) activated
during both MP and MI were identified in each region in the majority of
subjects; percentage increases in signal intensity during MI were on
average 30% as great as increases during MP. The pixels activated
during both MP and MI appear to represent a large fraction of the whole
population activated during MP. These results support the hypothesis
that MI and MP involve overlapping neural networks in perirolandic
cortical areas.
Key words:
primary motor cortex;
primary somatosensory cortex;
motor
performance;
motor imagery;
functional magnetic resonance imaging;
brain mapping
INTRODUCTION
Motor imagery (MI) may be defined as the mental
rehearsal of simple or complex motor acts that is not accompanied by
overt body movements. Two kinds of mental representations of motor acts can be generated by normal subjects: an "internal" or first-person process in which subjects feel themselves executing movements, and an
"external" or third-person process involving a visual
representation of actions (see Mahoney and Avener, 1987 ). Unlike visual
imagery (VI), internal (or kinesthetic) MI is difficult to describe
verbally. Nevertheless, it is usually characterized by vivid mental
representations and by changes in heart and respiration rates that are
related to the degree of mental effort (Decety et al., 1991 ; Wang and Morgan, 1992 ).
It is currently debated to what extent brain networks activated during
internal MI overlap those involved in the preparation and execution of
real motor acts (Jeannerod, 1994 ). This issue has been addressed using
a variety of brain mapping techniques. Early studies investigating
regional cerebral blood flow levels by single photon emission or
positron emission tomography (PET) techniques demonstrated the
activation during MI of different motor-related regions, such as the
supplementary motor area, lateral frontal (premotor) areas, and
cerebellum, but they did not provide evidence for increased activity in
the primary sensorimotor cortex (Ingvar and Philipson, 1977 ; Roland et
al., 1980 ; Fox et al., 1987 ; Decety et al., 1990 ).
Conflicting results have been obtained by more recent PET or functional
magnetic resonance imaging (fMRI) mapping studies. Activated foci in or
around the primary motor area have been described in PET studies by
Lang et al. (1994) during oculomotor imagery, and by Stephan et al.
(1995) during mental representation of upper extremity movements, but
not during imagery of grasping movements (Decety et al., 1994 ) or
implicit imagery of hand rotations (Parsons et al., 1995 ). Moreover, in
the study by Stephan et al., only two of six subjects showed activated
foci in or near the anterior bank of the central sulcus, the likely
site of primary motor cortex (Brodmann area 4) in humans (Roland and
Zilles, 1994 ; Geyer et al., 1995 ). Primary sensorimotor cortex
activation during MI has been denied by two early fMRI works (Rao et
al., 1993 ; Sanes et al., 1993 ), whereas it was found by other groups,
at least in some subjects (Leonardo et al., 1995 ; Sabbah et al., 1995 ).
These studies, however, did not provide a quantitative assessment of the relative contribution of precentral and postcentral areas.
The present study was designed to assess by high-resolution fMRI
techniques whether perirolandic areas show increased functional activity levels during mental representation of sequential finger movements and to investigate the spatial distribution and intensity of
activated foci during MI and overt motor behavior. The results suggest
that overlapping neural networks in the primary motor and somatosensory
areas are activated during mental representation and actual performance
of motor acts.
MATERIALS AND METHODS
Fourteen right-handed volunteers (4 males, 10 females; 20-39
years of age, mean, 24.6) were studied. All gave their informed consent
for the procedure, and none had a history, symptoms, or signs of
neurological or psychiatric disease. Handedness was assessed using a
short questionnaire based on the Edinburgh scale (Oldfield, 1971 ).
Data acquisition. The experiments were performed using a
Magnetom SP 4000 (Siemens, Erlangen, Germany) superconducting 1.5 T
whole-body magnetic resonance (MR) system equipped with a standard circularly polarized head coil. Head motion was minimized by an adjustable padded head holder. Field homogeneity was adjusted by a
global shimming procedure for each subject, with line widths being
~20 Hz. To locate the precentral and postcentral gyri, multislice T1-weighted spin-echo sagittal, axial, and
coronal images [repetition time (TR)/echo time
(TE) = 600/15 msec] were acquired. Two adjacent oblique
(axial to sagittal) planes were then defined along the central sulcus
of the left hemisphere, including the putative hand representation area
of the primary sensorimotor cortex (Talairach and Tournoux, 1988 ;
Colebatch et al., 1991 ; Grafton et al., 1991 , 1993 ; Rumeau et al.,
1994 ). The anatomy of these oblique planes was shown on
T1-weighted images [field of view (FOV) = 220 mm; 256 × 256 matrix; slice thickness = 4 mm]. The more
superficial plane covered the gray matter at the convexity of the
precentral and postcentral gyri, whereas the deeper one included the
anterior and posterior banks of the central sulcus. For the activation studies, images from the same planes were acquired using a
gradient-echo fast low-angle shot (FLASH) sequence
(TR/TE = 91/60 msec, flip angle = 40°; 128 × 128 matrix; FOV = 220 mm; slice thickness = 4 mm). The FLASH images were interpolated to and displayed as a
256 × 256 matrix, thus yielding a pixel size of 0.86 × 0.86 × 4.0 mm. Total scan time for one slice was 14 sec.
Each subject was asked to perform three different tasks sequentially
during the experiments: mental representation of a stationary visual
scene (VI), mental representation of self-paced, sequential finger-to-thumb opposition movements of the right hand at a frequency of ~2 Hz (MI), and actual execution of the same motor performance (MP). VI was taken as a reference state to control for possible aspecific effects related to imagery. Subjects were instructed to
perform the motor sequence at a constant rate, exerting a light pressure at each finger contact with the thumb. The order of
finger-tapping was simply 2-3-4-5-2-3-4-5. The instructions for MI were
"to imagine using the right hand to perform movements and feeling the
sensations associated with finger-tapping, while keeping the hand
still." For VI, subjects were asked to mentally represent a familiar
landscape (typically, a natural setting). They were requested to scan
the mental scene and to focus on particular objects but not to imagine themselves moving any part of the body. It was emphasized that during
the MI and VI tasks, the arms had to remain still with the right hand
resting on the chest and the fingers in a midflexion position.
Subjects were allowed to practice each of the three tasks during the
time (~40 min) they were lying in the magnet, before the acquisition
of functional images. All of them reported being able to execute the
tasks, although some judged it quite difficult to maintain the same
vividness of mental representations (MI or VI) over the whole
experimental period. Hand movements were monitored throughout the
experiments using a video camera. Dynamic data sets were acquired in
blocks of four images, each lasting 14 × 4 = 56 sec, while
subjects performed one of the tasks. Subjects started the execution of
the next task immediately after the end of each block. The functional
sequence, however, started 12 sec later; this delay was chosen to avoid
the acquisition of data during the transition periods (Kwong et al.,
1992 ; Bandettini et al., 1993 ; Friston et al., 1994 ).
In a first group of experiments (experiment 1), performed in 12 subjects, the task sequence was VI-MI-MP. In a second group of
experiments (experiment 2), performed in eight volunteers (six of whom
had already participated in experiment 1), the order of tasks was
reversed, and rest periods of the same duration as the other conditions
were added, during which subjects were asked to relax, keeping the arms
and fingers in the same posture as during the VI and MI tasks. The task
order was MP-Rest-MI-VI. In each experiment, the task sequence was
repeated three times during the acquisition of functional images from
each plane of interest. A total of 36 (48 for experiment 2) images was
thus acquired for each plane over a total period of 20 (27 for
experiment 2) min.
Data analyses. Image analyses were performed using a Silicon
Graphics Indy workstation. For each study and each anatomical image,
three regions of interest (ROIs) were identified and manually outlined
by one investigator and independently confirmed by another: the
postcentral gyrus (PostCG) and the anterior (PreCGAnt) and posterior
(PreCGPost) portions of the precentral gyrus. In the superficial plane,
the boundary between PreCGAnt and PreCGPost was traced at approximately
1/3 the distance between the central sulcus and the precentral sulcus,
which was identifiable in all subjects. In the deeper plane, the same
boundary corresponded typically to the white matter underlying the
precentral gyrus. Thus, PreCGPost included the anterior bank and crown
of the central sulcus. PostCG was defined as the region lying posterior
to the central sulcus; it was limited posteriorly by another sulcus, the shape of which, however, was quite different from one subject to
another. As a first approximation, PostCG corresponds to the "hand
area" of the primary somatosensory cortex (Brodmann areas 3, 1, 2),
PreCGPost to the "hand region" of the primary motor cortex (area
4), and PreCGAnt to the adjacent portion of the lateral premotor cortex
(area 6). The number of pixels, including both planes, in the three
ROIs (mean ± SEM of 20 studies) was 782 ± 50 for PreCGAnt,
632 ± 33 for PreCGPost, and 1478 ± 81 for PostCG. Care was
taken to exclude pixels associated with structures other than nerve
tissue, such as visible blood vessels or the inside of sulci.
To correct for possible movement artifacts, functional images were
aligned by a software procedure implemented by Robert Cox (AFNI
software package) and based on a previously described algorithm (see
Irani and Peleg, 1991 ). Briefly, registration was accomplished by
minimizing the error functional
E(u,v,h) = x,y [I(x,y) J(T(u,v,h)(x,y))]2,
where J(x,y) is the "base"
image, I(x,y) is the image to
be aligned to it,
T(u,v,h) is the
transformation with shift parameters (u,v) and
with rotation angle h. After finding the
(u,v,h) that minimizes the
error functional, I(x,y) was
transformed with
T( u, v, h) using
bicubic interpolation for resampling I. Then the
minimization was repeated; that is, simple descent gradient was used to
minimize E. The procedure was first performed with a
J(x,y) that has been smoothed
with a Gaussian filter with full-width at half-maximum (FWHM) equal to
4 pixels. After minimizing the error, the procedure was repeated with
J(x,y) smoothed with an
FWHM = 1 pixel. Mean ± SEM u and v
values from the 20 studies, expressed in pixel fractions (unsigned),
were 0.297 ± 0.008 (range for individual images, 0-1.846) and
0.336 ± 0.009 (range, 0-2.222), respectively; h value
was 0.232 ± 0.006° (range, 0-1 771°). Even if subtle
artifacts caused by head motion during single-image acquisition cannot
be excluded, no obvious false-positive results (e.g., activated pixels at the borders between the gray matter and surrounding tissue) were
found. A preliminary analysis performed on the same set of images
showed that the number of activated pixels during actual MP was not
significantly different using the present registration algorithm or
that described by Woods et al. (1992) . In each case, the "base"
functional image was acquired immediately after the T1-weighted anatomical image of the same plane.
The boundaries of the three ROIs identified on anatomical images were
automatically projected onto the aligned functional images, and
subsequent analyses were performed only on pixels lying inside the
three ROIs.
To analyze the intensity and time profile of fMRI signal changes, data
were normalized in every study and for each pixel by dividing the
actual value in each image by the mean signal intensity of the same
pixel in the 12 images acquired during the control (VI) condition. Mean
values of signal intensity of all pixels (in the superficial and deep
planes) lying within the three ROIs, or of pixel populations selected
by correlation analyses (see below), were then calculated and analyzed
by repeated-measures ANOVA, using the SPSS for Windows software
package. To ascertain potential variations of task-related neural
activation over time, the block order (possible levels, 1-3) and image
order within a block (1-4) were added to region (PreCGAnt, PreCGPost,
PostCG) and task (MP, MI, VI and rest in experiment 2) as
within-subject factors. The Mauchly test of sphericity was used to test
the hypothesis that the covariance matrix of the transformed variables
has a constant variance on the diagonal and zeroes off the diagonal. If
the sphericity assumption appeared to be violated
(p < 0.05), the Greenhouse-Geisser was
used to adjust degrees of freedom for the averaged results. Whenever
first-level tests were significant, difference (reverse Helmert)
contrasts were applied to assess differences between variable levels. A
value of p < 0.05 was assumed as the significance
level.
To locate activated foci during MI and MP in individual subjects, the
signal time courses in each pixel were compared with predefined,
task-related waveforms, thus creating statistical maps based on
correlation coefficients (r), with a possible range of 1
to 1 (Bandettini et al., 1993 ). A correlation coefficient of 0.7 was
assumed as the threshold for significance, corresponding to an
approximate p value of 2 × 10 6
(two-tailed) for analyses performed on 36 images. Because the highest
number of statistical comparisons in the subject displaying the largest
ROIs was 11,496 (3832 pixels in the 3 ROIs × 3 correlation analyses, see below), the adopted significance threshold yielded a
Bonferroni-corrected level of <0.05. Preliminary analyses, done on
36 images acquired from phantoms (n = 9; mean extent of the ROI 5300 pixels) or from the perirolandic cortex of healthy volunteers (n = 5; mean extent of the ROI 1400 pixels) during 9 min of a resting, relaxed state or repeated 3 min
periods of finger-tapping at a frequency of 2 Hz, gave no
"false-positive" pixel, using any of the waveforms used for
data analysis and a threshold of r = 0.7.
Negative correlations were found for a small number of pixels in a few
subjects; only positive results are reported here. Statistical maps
were overlaid on the T1-weighted anatomical
images obtained at the same planes. For each subject and each ROI, the occurrence of at least 4 pixels significantly correlated with a given
waveform was assumed to be a threshold of activation. To identify sites
of activation using standard coordinates, the MRI scans were resized
into the anatomical space of the atlas of Talairach and Tournoux
(1988) . The Talairach coordinates of the centers of mass of the
activated pixels within each ROI were then calculated using software
procedures (AFNI) developed by Robert Cox.
Electromyographic (EMG) recording. EMG recordings were not
performed during the fMRI study because of technical limitations. In a
separate experimental session, performed outside the MR equipment, EMG
activity was recorded in each volunteer from surface electrodes overlaying the thenar eminence or flexor digitorum superficialis on the
medial aspect of the forearm. Subjects performed the three tasks (VI,
MI, and MP) in the same order as during the fMRI experiment 1, and each
recording session lasted ~10 min. After conventional rectification
and filtering of the digitized EMG data, integral values of EMG
activity over successive 4 sec periods were calculated in each subject
and later analyzed by ANOVA. Although no subject made overt movements
of the right arm during MI, a mild increase of EMG activity during MI
relative to the control condition (VI) was observed in 4 of 14 subjects
for recordings from the thenar eminence, in 1 subject from both
recording sites, and in 3 of 14 subjects from the medial forearm.
However, the integrated EMG data were not significantly affected by MI
in the whole population at thenar (F = 0.96, p > 0.4) or forearm (F = 0.05, p > 0.8) sites.
RESULTS
None of the subjects displayed overt hand motion during the two
imagery conditions. The rate and amplitude of hand movements during the
MP task showed little intraindividual and interindividual variations,
as judged independently by two investigators.
Experiment 1
Mean signal intensity changes in the precentral and
postcentral regions
Mean values of normalized signal intensity for individual subjects
were obtained for each image from all pixels lying within each ROI: the
PreCGAnt and PreCGPost parts of the precentral gyrus and the PostCG. A
four-way, repeated-measures ANOVA (region × task × block × image: 3 × 3 × 3 × 4) showed that mean
fMRI signals were differently modulated in the three regions according
to task (region, F = 6.19, p < 0.01;
task, F = 23.61, p < 0.001; task × region, F = 4.24, p < 0.05). MI was
associated with significantly higher values (t = 2.69, p < 0.05) than VI. Moreover, images obtained during MP
were characterized by higher values than both of the other conditions
(t = 6.13, p < 0.001). No significant
difference was found for data obtained in different blocks or for
different images within a block. Therefore, for each subject, data from different blocks and time points were grouped and additional one-way, repeated-measures ANOVAs were performed for each region on values representing the mean normalized fMRI signal of all images obtained during the execution of each task (VI, MI, or MP). In all regions, fMRI
signals were significantly modulated by task (PreCGAnt:
F = 17.13, p < 0.001; PreCGPost:
F = 19.14, p < 0.001; PostCG:
F = 7.66, p < 0.01). In PreCGPost,
mean signal intensity values were significantly higher during the
execution of the finger-tapping task (t = 5.03, p < 0.001) than during the other two conditions, and
they were higher during mental representation of the same motor
sequence (t = 2.91, p < 0.05) than
during the VI task (Fig. 1). In PreCGAnt and PostCG,
significant signal increases were found only during MP (PreCGAnt:
t = 5.56, p < 0.001; PostCG:
t = 3.35, p < 0.01), although in the
PreCGAnt, a tendency toward an increase (t = 2.07, p < 0.062) was present during MI.
Fig. 1.
Histograms represent mean ± SEM percentage
fMRI signal changes in the anterior (PreCGAnt) and
posterior (PreCGPost) portions of the precentral gyrus
and in the postcentral gyrus (PostCG) during actual or
imagined MP relative to mean values of the control (VI) condition.
Significant differences from control values are *p < 0.05, **p < 0.01, and ***p < 0.001, respectively.
[View Larger Version of this Image (26K GIF file)]
Time profile of functional activation in different
pixel populations
The observed differences in mean fMRI signal intensities during MP
and MI might be related to the presence of spatially segregated neuronal populations selectively activated during one task, to a
differential involvement of overlapping neural networks during the two
tasks, or to a combination of the two. In a preliminary analysis,
pixels significantly (r > 0.7) activated during actual MP (population "MP") were identified by correlating the time course of their signal intensities over the 24 images acquired during VI or MP
with a square-wave function. For each subject, the mean normalized
signal intensities of the selected group of "MP" pixels lying in
PreCGPost were then calculated for each of the 36 images (Fig.
2). A three-way, repeated-measures ANOVA (task × block × image) confirmed that values were significantly affected
by task (F = 100.8, p < 0.001).
Moreover, they were higher during MI (t = 7.72, p < 0.001) than during VI and still higher during MP
(t = 10.3, p < 0.001), suggesting that at least
some movement-related pixels were also engaged during mental
representation of the same motor sequence.
Fig. 2.
Time profile of mean normalized signal intensity
in the population of pixels, located in the posterior portion of the
precentral gyrus, displaying significant (r > 0.7)
increases during actual MP (population MP). Each point represents
mean ± SEM values of one image in the series. The task sequence
is shown at the bottom of the graph. A repeated-measures
ANOVA performed on values of the 36 images showed that this pixel
population was also significantly activated during MI (see
Results).
[View Larger Version of this Image (29K GIF file)]
To further test this hypothesis, activated pixels during MP, MI, or
both conditions were identified by correlating their time profile of
signal intensity over the 36 images with square-wave or double-step
waveforms (Fig. 3). Clusters of pixels, the signal time
course of which was significantly (r > 0.7) correlated
with a double-step function (Fig. 3A), were identified in
the three ROIs in the majority of subjects (9/12 in PreCGAnt, 10/12 in
PreCGPost, and 8/12 in PostCG). To confirm that these pixel populations
were indeed activated during both MP and MI, the mean normalized signal intensities of all identified "double-step" pixels (population "A") lying within each ROI were calculated for each subject and for
each image, and data entered a four-way, repeated-measures ANOVA
(region × task × block × image). Values were
significantly different during the three tasks (F = 130.1, p < 0.001), being higher during MI than VI
(t = 8.09, p < 0.001) and during MP
relative to the other two conditions (t = 12.01, p < 0.001). No significant difference was found in the
time profile of signal intensity between the pixel populations of the
three areas; mean percentage increases over control values during MI
were ~26% as great as the increases during MP in the PreCGPost (Fig.
4A), 32% in PreCGAnt, and 33% in
PostCG.
Fig. 3.
To identify pixels in the three ROIs significantly
activated during MP, MI, or both conditions, their time profile of
signal intensity was correlated with single-step (B,
C) or double-step (A) waveforms.
Based on data shown in Figures 1 and 2, the height of the first step in
waveform A was set to ~30% that of the second one.
[View Larger Version of this Image (21K GIF file)]
Fig. 4.
Time profile of normalized fMRI signal intensity
in the pixel populations located in the posterior portion of the
precentral gyrus, significantly activated during both actual MP and MI
(A) or MP alone (B). Each point
represents mean ± SEM values of one image in the series. The task
sequence is shown at the bottom of the graph.
[View Larger Version of this Image (24K GIF file)]
To assess whether other pixel populations were activated exclusively
during MI or MP, two additional analyses were performed by comparing
the time profile of signal intensity of each pixel in the three ROIs
with waveforms B or C of Figure 3. Only one subject showed some pixels
in the PreCGAnt and PreCGPost, the signal time course of which was
selectively correlated with function C (that is, which displayed
increased levels only during MI). In approximately half of the subjects
(6/12 in the PreCGAnt, 7/12 in PreCGPost, and 6/12 in PostCG), clusters
of pixels were identified, the signal time course of which was
selectively correlated with the waveform B in Figure 3 (population
"B"). A 4-way, repeated-measures ANOVA showed that signal
intensities of these pixels were affected by task (F = 37, p < 0.001), whereas they did not differ
significantly among the three ROIs. Values acquired during MI were
indistinguishable from the control (VI) condition (t = 0.17, p > 0.85). By contrast, MP induced a clear-cut
activation (t = 6.13, p < 0.01). Thus, these pixels were indeed activated only during actual MP. The mean
signal time course of population B pixels lying in the PreCGPost is
shown in Figure 4B. It should be mentioned that some
pixels were identified by (that is, the time course of their signal
intensity was significantly correlated with) both waveforms A and B in
Figure 3. Because repeated-measures ANOVA showed that their values
acquired during MI were significantly higher than during VI, they were considered to belong to population A.
Spatial distribution and extent of functional activation during MI
and MP
Representative statistical maps obtained in two subjects,
depicting the location and extent of populations A and B, are shown in
Figure 5. There was considerable intersubject
variability, both in the anatomical conformation of the precentral and
postcentral gyri and the extent and spatial distribution of the
activated areas. Pixels activated by movement alone (population B) were intermingled with, or more often at the periphery of, clusters of
pixels activated both during movement performance and imagery (population A). In the precentral gyrus, these populations could be
found both in the depth of the banks of central and precentral sulci
and in the gray matter at the convexity of the gyrus. More sparse
activation was detectable in the postcentral gyrus (Fig. 5). No
significant difference was found between the number of activated pixels
or mean signal intensity changes in the deep (anterior bank of the
central sulcus) and superficial (crown) portions of PreCGPost.
Fig. 5.
Statistical maps, overlaid on
T1-weighted anatomical images of oblique
planes along the left central sulcus, showing the location of activated
points in the perirolandic cortex (left) and of the three identified ROIs (right) in two representative
subjects. For each subject, two planes were studied, one covering the
convexity of precentral and postcentral gyri (top) and
the other the depth of central sulcus (bottom). In each
image, top is anterior and right is
lateral. Left, Pixels showing by correlation analysis significant fMRI signal increases during both actual MP and MI (population A) are indicated in red; pixels
activated during MP alone (population B) in
white-yellow. Right, Boundaries of the ROIs located in the postcentral gyrus (red), the
posterior portion of the precentral gyrus
(yellow), and the anterior portion of the
precentral gyrus (green). The central sulcus
corresponds to the limit between the red and yellow areas. The boundary
between the two precentral areas is shown in yellow.
Both areas in the precentral gyrus display clusters of pixels activated
during both MP and MI and more sparse pixels activated only during
actual MP. Discrete activated foci are also present in the postcentral gyrus, particularly in the subject displayed on
top.
[View Larger Version of this Image (80K GIF file)]
Mean activated volumes for population A and B were 131 and 15 mm3 in PreCGAnt, 164 and 36 mm3 in PreCGPost,
and 117 and 36 mm3 in PostCG, respectively. If values are
expressed as percentage fractions of the total (anatomical) volume of
each ROI, it appears that the spatial extent of activation during MI
and MP was much wider in the two precentral areas than in the
postcentral area (Fig. 6). No significant correlation
was found between the spatial extent or intensity of activation in any
of the three ROIs and the degree of EMG activity displayed by the same
subjects during MI (Fig. 7).
Fig. 6.
Histograms are mean ± SEM of the activated
volumes during both MP and MI (population A), expressed as percentage
of the anatomical extent of the three ROIs. Significant differences at
*p < 0.05, **p < 0.01, ***p < 0.001.
[View Larger Version of this Image (23K GIF file)]
Fig. 7.
Integrated EMG activity recorded from surface
electrodes overlying the right thenar eminence (open
circles) or medial forearm (triangles) plotted
against the number of pixels in the PreCGPost showing a significant
activation during both MI and MP; that is, the extent of population A
(left) or the percentage changes of signal intensity
during MI in the same pixel population (right). Multiple
linear regression analyses yielded no significant correlation between
the EMG values and neural activity (number of activated pixels:
r = 0.41; F = 0.92;
p > 0.4; intensity of activation: r = 0.15; F = 0.10;
p > 0.9). Similarly, no significant correlation was found between the EMG activity during MI and the spatial extent or
intensity of activation of population A in the PreCGAnt (number of
pixels: r = 0.46; F = 1.24;
p > 0.3; intensity of activation: r = 0.22; F = 0.23;
p > 0.75), and the PostCG (number of pixels: r = 0.51; F = 1.58;
p > 0.25; intensity of activation:
r = 0.22; F = 0.19;
p > 0.8).
[View Larger Version of this Image (18K GIF file)]
A final analysis was made to estimate whether the spatial distribution
of pixels activated during both MI and MP (population A) was different
from the whole population presumably activated by movement (population
MP). All pixels belonging to population A in the three ROIs were also
identified by the correlation analyses performed on the 24 images
acquired during VI or MP (that is, population A corresponded to a
fraction of population MP). Talairach coordinates (Table
1) of the centers of mass of populations A and of
populations MP were calculated for each subject and compared by
repeated-measures ANOVA. No significant difference was found between
the two sets of values.
Experiment 2
In the previous group of experiments, the periods of mental
representation of movement immediately preceded real motor acts. To
test whether the observed signal increases during MI were attributable to, at least in part, an unintentional preparation to move, an additional series of experiments was performed in which the task order
was MP-Rest-MI-VI. In this way, any increase of neural activity during MI attributable to a "preparatory" phenomenon should be cancelled, because it should conceivably be present also during the
control task. The rest condition should also exclude possible after
effects of MP on data acquired during MI.
Mean percentage changes of normalized signal intensities of all pixels
lying in PreCGPost during MP, MI, or rest compared with the VI task are
shown in Figure 8. A four-way, repeated-measures ANOVA
(region × task × block × image) performed on values
from the 48 images in the three ROIs revealed a significant effect of
task (F = 44.03, p < 0.001); mean
signal intensities during MI were higher than during both VI and rest
(t = 4.5, p < 0.01), and values during
MP were higher than during the other three conditions (t = 7.98, p < 0.001).
Fig. 8.
Mean ± SEM percentage fMRI signal changes in
the PreCGPost during actual or imagined MP or rest, relative to mean
values of the control (VI) condition, in the eight subjects
participating in experiment 2. Significant differences from values of
the VI task at **p < 0.01 and
***p < 0.001, respectively; n.s.,
not significant. Significant differences at
##p < 0.01 and
###p < 0.001, respectively.
[View Larger Version of this Image (19K GIF file)]
To identify activated pixels during MP, MI, or both, cross-correlation
analyses were performed using the same single- or double-step reference
waveforms used in the previous experiment (Fig. 3), adapted to the new
task order. Population A pixels (Fig. 9A)
meeting the statistical criterion were identified in eight of eight
subjects in PreCGAnt and PreCGPost and in six of eight subjects in
PostCG. Repeated-measures ANOVA showed that the time profile of their signal intensity was similar in the three ROIs, whereas it was significantly affected by task (F = 114.17;
p < 0.001). Signal intensities during MI were higher
than both VI and rest (t = 6.96, p < 0.001), and still higher values were obtained during MP
(t = 13.9, p < 0.001). Mean percentage
increases of signal intensities over the control (VI) values during MI
were ~28% as great as during MP in PreCGPost, 29% in PostCG, and
34% in PreCGAnt. The mean extent of the activated areas was 215 mm3 in PreCGPost, 208 mm3 in PostCG, and 140 mm3 in PreCGAnt.
Fig. 9.
Time profile of normalized fMRI signal intensity
in the pixel populations located in the posterior portion of the
precentral gyrus, significantly activated during both actual MP and MI
(A) or MP alone (B), in experiments in
which MI preceded the control (VI) task. Each point represents
mean ± SEM (n = 8) values of one image in the
series. The reference waveforms and the task sequence are shown at the
bottom of the graphs.
[View Larger Version of this Image (24K GIF file)]
Population B pixels (Fig. 9B) were found in three of eight
volunteers in PreCGAnt, five of eight in PreCGPost, and six of eight in
PostCG. Their signal time course was also affected by task
(F = 20.32, p < 0.01), with
significant signal increases only during MP relative to the other three
conditions (t = 8.89, p < 0.01);
similar values were found in the three ROIs. No pixel in any region was
significantly activated only during MI.
In the six subjects who participated in both experiments, there were no
significant differences between the two studies in mean changes of
signal intensity in the three ROIs during MI and MP (experiment:
F = 1.58, p > 0.25; experiment × task: F = 2.55, p > 0.15;
experiment × task × region: F = 0.04, p > 0.85). The extent of population A in the three
ROIs (experiment: F = 0.11, p > 0.75;
experiment × region: F = 0.97, p > 0.40) and the intensity of activation of the same population during
MI and MP (experiment: F = 2.88, p > 0.15; experiment × task: F = 2.39, p > 0.15; experiment × task × region:
F = 1.84, p > 0.20) were also similar
in the two experiments. Accordingly, no significant difference in the extent and intensity of activation was found when comparing the results
of the 12 studies of experiment 1 with those of the 8 studies of
experiment 2.
In comparing mean normalized signal intensity values obtained
during VI, MI, and MP in the 20 experimental sessions, significant increases were found during MI (as well as during MP) in all three ROIs
(PreCGAnt: t = 3.47, p < 0.01;
PreCGPost: t = 4.67, p < 0.001; PostCG: t = 3.16, p < 0.01). Mean
percentage increases during MI and MP were ~0.6 and 1.7% in
PreCGAnt, 0.8 and 2.1% in PreCGPost, and 0.4 and 1.2% in PostCG,
respectively.
DISCUSSION
The results of this study indicate that functional
activity levels in the posterior portion of the precentral gyrus, the
presumed site of the primary motor cortex, are increased during mental representation of a simple sequence of finger movements, although the
intensity of activation is lower than during real movements. Moreover,
foci displaying significant activation during both MP and MI are present in the majority of subjects in the precentral and
postcentral gyri, where they appear to represent a large fraction of
the whole neural population activated by movement.
Gradient-echo fMRI mapping techniques: advantages
and limitations
fMRI provides a noninvasive tool for mapping human brain function
(LeBihan and Karni, 1995). Specifically, T2*
tissue relaxation-dependent proton signal increases can be detected by
gradient-echo sequences on activation in specific brain regions, which
are likely to reflect the interplay among local changes in blood flow,
volume, and oxygenation (see Prichard and Rosen, 1994 ; Kwong, 1995 ).
These fMRI signal changes are expected to be small, and the observed
percentage increases in the three anatomically defined regions fit well
with previous results on visual and motor cortex activation using
similar fMRI techniques (Kwong et al., 1992 ; Frahm et al., 1993 ; Mattay et al., 1995 ).
The spatial resolution affordable by fMRI appears well suited to detect
signal changes in discrete units of the human cortical gray matter
(Frahm et al., 1993 ). However, because gradient-echo fMRI sequences are
sensitive to inflow and large vessel effects, the effective spatial
resolving power may be hampered if the observed signals are related
predominantly to flow changes in large veins, draining blood from wide
and potentially distant sites, rather than from the parenchimal
capillary bed (Lai et al., 1993 ; Frahm et al., 1994 ; Segebarth et al.,
1994 ). In the present study, pixels associated with visible blood
vessels were excluded from the three ROIs. Moreover, the signal
increases found in activated foci, on the order of 10%, are likely
to be induced by hemodynamic changes at the venule (vessel diameter,
50-200 µm) (Haacke et al., 1994 ) and capillary levels and therefore
to reflect local neural activity (see also Rostrup et al., 1995 ). Clear
differences were indeed observed between the mean intensity and spatial
extent of motor-related activation in contiguous structures such as the anterior and posterior banks of the central sulcus, with higher values
in motor areas.
Experimental design
To exclude potential effects of mental imagery per se, such as an
aspecific arousal, in the present study, a VI task was adopted as the
control condition. To the authors' knowledge, no study has so far
described significant changes in functional activity levels in the
primary sensorimotor area (SM1) during VI. Because subjects were asked
to mentally scan the visual scene, some degree of neural activation
related to actual or imagined eye movements otherwise might have been
present (see Lang et al., 1994 ). The results of our second group of
experiments show that fMRI signal intensity values during MI were
higher than those during either VI or rest. Therefore, the observed
increases during MI and MP are unlikely to be related to a downward
shift of hemodynamic parameters during the control (VI) state.
Given the poor temporal resolution achieved in the present study (14 sec) compared with other fMRI techniques, fast hemodynamic changes
could not be detected. It is well known that at the onset (or offset)
of stimulation, fMRI signal intensities rise (decay) with a time
constant of some seconds (Kwong et al., 1992 ; Bandettini et al., 1993 ;
Friston et al., 1994 ). The adopted delay between the beginning of each
task and image acquisition should exclude major after effects. In any
case, because MI was never immediately preceded by actual MP, the
observed signal changes during mental representation of motor acts
cannot be attributed to residual effects of the latter condition. On
the other hand, similar results were obtained when MI immediately
preceded actual MP (experiment 1) or the control condition (experiment
2). Therefore, fMRI signal changes during MI were not simply
attributable to an unintentional preparation to move.
Movement-related functional activation in the
perirolandic area
The cortical primary motor area has long been associated with the
control of distal arm movements (for review, see Porter and Lemon,
1993 ), and motor tasks involving repetitive finger flexion have been
consistently shown to increase functional activity levels in the
contralateral SM1 cortex in humans (Roland et al., 1980 ; Fox et al.,
1987 ; Colebatch et al., 1991 ; Kim et al., 1993 ; Matelli et al., 1993 ;
Rao et al., 1993 , 1995 ; Shibasaki et al., 1993 ; Dettmers et al., 1995 ).
The present results showed that during a self-paced finger-tapping
task, the spatial extent and mean intensity of functional activity
changes within the sampled portion of SM1 were significantly higher in
the two precentral regions, including the primary motor cortex and the
adjacent portion of the lateral premotor cortex, than in the
postcentral gyrus. These findings are likely to reflect the more direct
involvement of precentral areas in motor control. In all subjects,
multiple activated foci were identified in the precentral gyrus,
probably representing overlapping areas controlling distal movements
(Rao et al., 1995 ; Sanes et al., 1995 ) .
MP and MI: common neural substrates?
In the present study, significant increases in functional activity
levels at the presumed site of the primary motor cortex were found
during MI, which were not evident or could be detected only in a few
subjects, in previous functional imaging mapping investigations (see
introductory remarks). It is likely that several factors contribute to
this apparent discrepancy. Levels of activation during imagery were
relatively low compared with actual MP; therefore, they may have been
undetected by imaging techniques characterized by lesser spatial
resolution, particularly when activity levels from the precentral and
postcentral areas could not be clearly separated. Moreover, given the
complexity of motor subsystems, quantitative differences in the pattern
of activation of motor and premotor areas are to be expected when
different kinds of motor acts are executed or imagined (see Passingham,
1993 ; Ashe and Ugurbil, 1994 ; Jeannerod et al., 1995 ). For instance,
mental rehearsal of visually guided grasping movements increases blood flow rates in inferior lateral premotor regions (Decety et al., 1994 ),
whereas the supplementary motor area appears to be more active during
mental representation of other kinds of motor tasks (Roland et al.,
1980 ; Rao et al., 1993 ; Stephan et al., 1995 ). In the present study, a
simple and predictable self-paced sequence of finger movements was
used, which can be easily implemented, even without a training period.
It can be speculated that the neural networks organizing simple,
"unlearned" sequences of finger movements are also distributed in
the precentral areas, which have been recently suggested to participate
in the organization of complex motor acts in humans (Shibasaki et al.,
1993 ). There is indeed evidence that neuronal assemblies in the
primate motor cortex are related to complex, cognitive processes
(Georgopoulos et al., 1993 ). For instance, directionally tuned
cells in the primary motor area discharge during the delay period
(without concomitant changes in EMG activity) in delayed (Tanji and
Evarts, 1976 ; Georgopoulos et al., 1989a ; Alexander and Crutcher, 1990 ) or memorized (Smyrnis et al., 1992 ) motor tasks. Moreover, time-related changes in the activity of directionally selective neurons may encode
mental rotation of the direction of intended movement (Georgopoulos et
al., 1989b ). It may be hypothesized that the activity of similar networks, lying in the precentral gyrus, might be accessible to conscious inspection in humans, and thus be involved in MI. When more
complex, learned sequences of motor acts must be retrieved, the
supplementary motor area is more likely to be involved (Roland et al.,
1980 ; Rao et al., 1993 ).
Local hemodynamic changes during brain activation are thought to
reflect primarily alterations in synaptic activity, which may in turn
be attributable to increased firing in local interneurons (either
excitatory or inhibitory) and/or in afferent fibers (Raichle, 1987 ;
Roland, 1993 ). In the investigated regions, foci activated during MI
were always active (and displayed higher signal increases) during MP as
well, suggesting that imagery involves at least a subset of neurons
that are engaged during actual MP. It cannot be fully established
whether the observed fMRI signal increases during mental representation
of motor acts are attributable entirely to the activity of
intracortical networks or whether they are related in part to motor or
sensory feedback signals attributable to increased descending volleys.
A related issue concerns the mechanisms and sites (cortical or spinal)
of motor inhibition during MI (see Jeannerod, 1994 ; Berthoz, 1996 ; Lang
et al., 1996 ). There are several reports of an increase of EMG activity
in muscles involved in the imagined motor act (Jacobson, 1930 ; Wehner
et al., 1984 ; Harris and Robinson, 1986 ), although this is not a generalized finding (Yue and Cole, 1992 ) (for discussion, see Jeannerod, 1994 ). In the present study, no subject displayed overt motor behavior during MI, and only some showed a small increase of EMG
activity during MI compared with the control condition. Although it is,
of course, possible that the activity of muscles other than that
recorded could have been changed, regression analyses showed that
cortical activation was not related to the degree of EMG activity.
Thus, it is conceivable that the observed fMRI changes during MI are
attributable primarily to the activity of intracortical circuits.
It is intriguing that in the majority of subjects, an increase in
functional activity levels was found not only during MP but also during
MI in discrete neural units lying in the postcentral gyrus. Recent
results suggest that the primary somatosensory area displays higher
levels of neural activity during imagery of tactile stimuli (Hodge et
al., 1996 ). In the present study, subjects were asked to recall during
MI the sensations associated with finger-tapping, which are both
exteroceptive and proprioceptive in nature. Thus, it might be
speculated that the observed fMRI changes in the postcentral gyrus
during MI are related, at least in part, to somatosensory imagery.
The present fMRI results are in line with recent studies
suggesting an involvement of the primary motor area during MI.
Imagination of hand movements induced specific changes in the pattern
of DC potentials recorded from sites overlying the primary sensorimotor cortex (Beisteiner et al., 1995 ) and in the pattern of magnetic fields
related to activity of the primary motor cortex (Lang et al., 1996 ),
although in both studies, changes were less pronounced than those
induced by actual MP. In a transcranial magnetic stimulation study,
Pascual-Leone et al. (1995) showed that after 5 d of mental practice of a five-finger piano exercise, the cortical motor output maps targeting finger flexors and extensors enlarged, and their activation threshold decreased. Sirigu et al. (1995) described a
patient with a focal lesion of the right motor cortex, who displayed congruent and selective unilateral impairments of motor behavior and MI
of the contralateral hand, as judged by the actual and perceived time
required to perform overt or covert movements, respectively.
Altogether, these observations suggest that primary motor cortex plays
a role in the mental representation of motor acts. Furthermore, the
present results show that conscious representation of movement induces
changes in activity of neural networks in the perirolandic cortical
area, largely overlapping the changes involved in motor execution.
FOOTNOTES
Received March 25, 1996; revised Sept. 4, 1996; accepted Sept. 9, 1996.
This work was supported by funds of Consiglio Nazionale delle Ricerche
and Ministero Università Ricerca Scientifica e Tecnologica, a
grant from Siemens Italia SpA to V.C., and Telethon Grant 779 to P.E.P.
We thank R. Cox, Biophysics Research Institute, Medical College of
Wisconsin, for providing the software package for image registration
and analyses.
Correspondence should be addressed to Prof. Carlo A. Porro,
Dipartimento di Scienze Tecnologie Biomediche, Universitá di Udine, Via Gervasutta 48, I-33100 Udine, Italy.
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