Human Walking Along a Curved Path,II,Gait Features and EMG Patterns
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Transcript of Human Walking Along a Curved Path,II,Gait Features and EMG Patterns
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Human walking along a curved path. II. Gait features andEMG patterns
Gregoire Courtine1,2 and Marco Schieppati2
1INSERM Motricite & Plasticite, University of Burgundy, Dijon, France2Section of Physiology, Department of Experimental Medicine, University of Pavia, and Human Movement Laboratory (CSAM),
Fondazione Salvatore Maugeri (IRCCS), Scientific Institute of Pavia, Italy
Abstract
We recorded basic gait features and associated patterns of leg muscle activity, occurring during continuous body progression when
humanswalked along a curved trajectory, in order to gain insight into the nervous mechanisms underlying the control of the asymmetric
movements of the two legs. The same rhythm was propagated to both legs, in spite of inner and outer strides diverging in
length(P
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the intrinsic features of spinal networks and the force acting during the
turn. In this paper, we attempted to examine whether locomotor
patterns are fundamentally changed or only finely tuned in order to
exploit a basic functioning of the spinal locomotor system. To this aim,
we investigated basic gait features involved in the production of a
continuous body trajectory along a curve as well as associated patterns
of leg muscle activity. We provide the evidence that commands to walk
along a curved path may exploit the basic mechanisms of the spinal
locomotor generator, thereby limiting the computational cost of
turning.
Materials and methods
Participants
Six healthy male adults volunteered for this experiment (see compa-
nion paper for further subjectsdescription).
Locomotor task
The locomotor task has been described in the companion paper.
Briefly, subjects executed walking trials along two locomotor paths:
straight and curved. The curved path shared the initial 3 m of the
straight path, then followed a 4.6-m curve to the right, ending with a
further 2 m of straight walking. The radius of curvature was constant
(120 cm), thus resulting in an overall change of direction of 2208(see
Fig. 3). Subjects walked barefoot with the arms folded across the chest.
They made 10 repetitions with eyes open (EO) and 10 repetitions
blindfolded (BF) in each walking condition.
Data acquisition
General procedures have also been described in detail in the compa-
nion paper. Both kinematic and electromyographic (EMG) data were
obtained using the integrated ELITE (BTS, Italy) system. Bipolar
surface electrodes (1 cm diameter, electrode separation of 1 cm) were
placed over three muscular groups of each leg: tibialis anterior (belly),
soleus (2 cm below the insertion of the gastrocnemii) and rectus
femoris (belly). A ground electrode was placed on the wrist. In
addition, for three of the six participants, the activity of the peroneuslongus muscle was recorded from both legs. Signals were preamplified
(100), digitized, and transmitted to the remote amplifier via tele-metry. Signals were sampled at 1000 Hz, band-pass filtered (10
500Hz) and full-wave rectified. The resulting EMG signal was
normalized with respect to mean EMG activity measured during a
window of 500 ms selected in the middle of 3 s of maximum voluntary
contraction. Normalized waveforms were smoothed by applying a
moving average of 50 ms width.
Data processing
Kinematic sampling and EMG data recordings were synchronized at
rates of 100 and 1000 Hz, respectively. Data from each trial were
ensemble-averaged after time interpolation over individual gait cycles
to fit a normalized 1000-point time base.
Elaboration of kinematics data
Co-ordinate frames
Co-ordinate frames that describe body motion while moving through
space were defined in a hierarchical manner as described by Imai et al.
(2001). The primary co-ordinate frame was the space-fixed reference
frame of the video system (XS, YS, ZS). Instantaneous heading direction
was defined as theangle of theinstantaneouslinear velocity vector of the
body mid-point (see the companion paper for details) in the horizontal
plane with respect to the space-fixed reference frame. The amplitude of
the locomotor direction change during one gait cycle was calculated as
the difference in heading between two successive heel strikes of one leg.
Subsequently, the co-ordinates of the different markers were converted
in the body-centred reference frame, whose Xaxis matched the heading
direction, through co-ordinate transformation. Following this, angles of
trunk, foot and limb axis segments were computed.
Determination of gait events
The stride cycle was considered the interval between two successive
heel strikes of one leg. In this paper we considered for further analysisonly gait cycles whose heading change was >408. Indeed, whensubjects walked along curved paths, heading change was generally
>408, whereas smaller angles corresponded to the transition fromstraight to curved trajectories. Selected cycles were then expected to
provide more consistent information concerning turn-related gait
organization (in some figures, cycles associated with intermediate
heading changes arealso included, and additions areindicated). Onsets
of swing phases were based on rates of change of foot vertical
translations. A threshold of foot clearance was set at 10% of maximal
peak velocity of foot vertical displacement during the swing phase.
Gait parameters
Gait cycle duration was taken as the time interval between twosuccessive heel strikes of one leg. Stance and swing duration was
computed and converted to percentages of total cycle duration. For
each leg, stride length was measured as the linear translation of the
malleolus between two successive heel strikes. The body displacement
was also computed as the length of the body mid-point path during the
entire time-interval of the cycle:
Body path=cycle Xn1i1
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffiffiffiffiffiffixi1 xi
2 yi1 yi2 zi1 zi
2
q
wheren is the number of acquired frames during the gait cycle. The
average velocity of body displacement was computed as the body path
length divided by the duration of the gait cycle. As turning affected the
walking speed (see companion paper), a speed-independent index(Sekiya & Nagasaki, 1998) was used in order to assess the relationship
between gait parameters across the two walking directions and left and
right legs. Awalking ratio was computed as the stride length divided by
the step frequency.
Limb displacements
Inter-limb coordination was calculated as the phase difference (DF)
between angular displacements of left and right limb axes:
DF 360
Dt=T
where T is the duration of the inner (right) limb cycle and Dtis the
difference between the time at which the outer (left) limb reaches its
angular peak (heel strike) and the time halfway between the two
successive angular peaks (heel strikes) of the inner limb (see inset of
Fig. 4). Given this definition, if the left and right limbs move 1808out
of phase, DF would be equal to zero. In turn, when DF is positive,
contralateral heel strike occurred beyond half of the cycle, thus
indicating a phase lag of the outer with respect to the inner limb.
Mean velocity of limb endpoint displacements were evaluated as
average velocities of malleolus displacements during the swing phase.
Elaboration of EMG data
Temporal EMG features
Onsets and ends of EMG burst activity were established at the points at
which muscle activity was, respectively, greater or less than mean
192 G. Courtine and M. Schieppati
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activity plus 1.5 SD recorded during a period when the muscles were
least active(swing phase for the soleus and from 25 to 50% of cycle for
tibialis anterior and 3070% of cycle for rectus femoris). Soleus and
rectus femoris muscles presented a single burst during the gait cycle,
whereas tibialis anterior showed a well-identified double burst. The
latter was divided into two distinct bursts whose separation was set as
the trough occurring around the centre of the double burst. The burst
determination was made automatically (see above) but noise-induced
errors were corrected when necessary by means of interactive custom-
made software. This was done by redefining a temporal window forcomputing EMG background during which noise was absent. The
activity of each muscle during stance and swing phases as well as
during the time interval of the burst was calculated as the integral of the
muscle envelope.
Inter-limb EMG timing
The timing of EMG activation between homonymous muscles of the
two legs during turning was assessed by means of cross-correlation of
averaged EMG waveforms. Averaged waveforms were first normal-
ized by expressing the mean waveform during the entire cycle (T) with
respect to the mean value of the EMG activity during SA, for each
muscle, side and subject individually. Then, the grand averages of
EMG waveforms were computed for each leg and muscle. Finally, thecross-correlation algorithm was applied to the waveform profiles.
Statistical analysis
Means and SD, for each subject in each walking condition (straight or
curved) and for all parameters described above, were calculated. All
the mean values computed during gait cycles were submitted to a
2 (straight-ahead or turning) 2 (limb side) 2 (vision) analysis ofvariance for repeated measures (within-subject ANOVA). Differences
between variables related to the whole trajectory were evaluated using
a 2 (straight or curved path) 2 (normal vision or blindfolded) ANOVAfor repeated measures.Post hocdifferences were assessed by means of
the NewmanKeuls test. In addition, Students t-test and ANOVA/
ANCOVA were, respectively, used to assess the differences between
slopes or intercepts of linear regressions. The software packageStatistica1 was used.
Results
The analysis of the results has been deliberately focused here on the
spatio-temporal gait and muscular events occurring after the comple-
tion of the transition between straight-ahead and turning, i.e. when the
turning behaviour had reached a plateau (see Materials and methods).
A total of 337 and 428 gait cycles where analysed during straight-
ahead and turning, respectively. Subjects were similarly represented,
because each contributed a mean of 56 7 and 71 17 cycles for thestraight and curved paths, respectively, to the analysis.
Gait features
Spatial and temporal features of the gait pattern of all subjects across
all trials during both straight-ahead walking (SA) and turning (TU),
both with eyes open (EO) and blindfolded (BF), are detailed in
Fig. 1AC.
During straight-ahead locomotion, cycle duration and stride length
were unchanged between left and right limbs (ANOVA, side effect,
P> 0.8 for all parameters) regardless of visual condition (vision effect,P> 0.7). Duration of cycles was close to 1 s (on the average1.11 0.02 s). Stride length slightly decreased (5.5%) when walkingblindfolded (vision effect, F1,5 9.9, P< 0.05). A significant effectwas found in the walking ratio (length/frequency) (see Materials and
methods) between EO and BF (vision effect, F1,5 13.2, P< 0.05),mainly connected to the decrease in stride length.
During turning, gait cycle duration was predictably unchanged
between left and right limbs (P> 0.3) but also when comparedto straight-ahead (P> 0.01). There was a decrease (18.5%) in thelength of the internal (right) stride compared to the left stride
(direction side-effect,F1,5 204, P < 0.0001; post hoc comparisonP< 0.001). The latter did not change its length with respect to straight-ahead (post hoccomparison,P> 0.2). When turning was executed BF,
stride length was decreased to a similar extent for both limbs (5.6%).This effect has the same size as that observed under the straight-ahead
condition. As a consequence of the limb-specific change in stride
length but not in stride duration, the walking ratio was markedly
diminished (18.3%) for the right leg cycles (side direction,F1,5 286, P< 0.0001; post hoc, P< 0.0005). The walking ratioof the left leg cycles was unaffected during turning compared
to the straight-ahead conditions (post hoc comparison, P> 0.4).Without vision, the walking ratio slightly diminished (4.9%) for both
trajectories of walking and for both limbs (directionvision ordirectionvision side showed no significant effect; P > 0.4).
The histograms in Fig. 1C summarize spatio-temporal features of
body displacements during both straight-ahead and turning conditions.
Mean body velocity significantly decreased when walking alongcurved as compared to straight paths (by 15.4% on average; see also
companion paper) (direction effect,F1,5 15,P 0.01). Blindfoldingresulted in a decrease (5.7%) in mean body velocity during both
straight-ahead and curved walking. The distance of body displacement
along its own trajectory during one cycle (body path) was calculated as
the total length travelled by the body mid-point during the time-
interval of the cycle. The body paths calculated during the left and right
cycles were averaged together for each walking condition because the
duration of left and right cycles was similar within each condition. The
result was that walking along the curved path induced a moderate but
significant decrease in the distance covered by the body during one
cycle (16.3%) (direction effect, F1,5 26, P < 0.005).
Stride length to body velocity relationshipDuring normal walking, a well-known monotonic relationship exists
between stride length and body velocity. This was reproduced in all
subjects, for straight-ahead walking, as shown in the plot of Fig. 2A.
No differences were found between left and right sides. However, for
turning, the two scatter plots for left and right leg were separated from
each other (plot of Fig. 2B) despite there being no significant changes
in the slopes of the lines of best fit. This is also indicated by the equal
slope values (grand means from each subject) reported in Fig. 2C
(side or direction effect, P> 0.2). Figure2D shows that the meanintercept of the line fitting the data points for the right limb during
turning diverged significantly from the other intercepts (ANOVA,
direction side effect, F1,5 50, P< 0.001; P< 0.001 for all right-turning intercepts vs. other intercepts, post hoc comparison).
Spatial organization
From the typical body displacements along the straight and curved
path depicted in Fig. 3A, one can see that the body mid-point trajectory
lay in between the foot prints during straight-ahead walking, but was
much closer to the inner foot during turning (see companion paper
for further details on foot positioning). Positions of foot prints
illustrate the decrease in the stride length of the inner with respect
to the outer limb. The plot of Fig. 3B details these stride length changes
for all subjects. Differences between stride lengths of left and right
limbs and the length of the body path are plotted against the amplitude
of heading change, which corresponds to the tightness of the curvature
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produced during two successive heel strikes of each limb during the
gait cycle. The cluster located around the zero heading change
corresponds to straight-ahead walking. Here, the difference between
the stride length and the body path length is negative because the
body mid-point covers more distance than the foot during the time
interval of the cycle (the body mid-point moves up and down, and
right and left, during normal straight-ahead walking, while stride
length is the spatial distance between two successive heel strikes).
The data point pertaining to curved walking corresponds to the
upper and lower clusters for left and right limb, respectively. Inter-
mediate points connecting straight- and turning-related clusters
correspond to gait cycles executed during turning but at the initial
part of the curve, when the heading change is less pronounced. The
increase in distance shown for the left limb does not result from a true
increase in stride length but depends upon the decreased distance
travelled by the body mid-point during curved cycles. In turn, the
distance travelled by the body mid-point decreases because of a shift of
the body toward the inner foot. The top right diagram attempts to
provide a graphic explanation of this phenomenon. The two feet cover
imaginary paths, their distance depending on the tightness of the
trajectory curvature; the body path (grey dashed line) tends to approach
the inner foot path, thereby loading and unloading the inner and outer
foot, respectively.
Temporal gait features
Turning not only produced opposite effects in the spatial features of the
gait patterns of left and right limbs but was also accompanied by clear-
cut differences in some temporal features of walking. The duration of
the stance phase is indicated in the histogram of Fig. 4A. Duration
decreased when the supporting foot was the left, outer foot, and
increased when the supporting foot was the right, inner one (side -
direction effect, F1,5 44, P 0.001). Compared to straight-aheadcycles, stance duration of left and right limb significantly decreased
(post hoc, P < 0.01) and increased (post hoc, P 0.01), respectively,during curved walking. As a consequence, the mean double stance
duration was hardly affected during turning (9.9 1.3 and 9.6 1.7%of the cycle for SA and TU, respectively; data pooled for the two
limbs). Without vision, the duration of stance significantly increased
(4.5%) for both left and right legs (vision direction effect, F1,5 9,P< 0.05) (post hoc, P< 0.005 for EOBF comparison during turning).
A slight but significant change in the phase lag between the periodic
oscillations of outer and inner limbs was a regular feature of the
progression along the curved path. This was assessed as the phase lag
between left and right limb angular displacements (limb axis), the
positive peak value of which corresponds to the heel strike. As
expected, the calculation of this phase lag gave a value very close
Fig. 1. (A) Mean duration (upper histogram) and mean stride length (lower histogram) of gait cycles performed when walking along straight or curved paths,with eyes open (EO) or blindfolded (BF). (B) Mean values of the walking ratio (stride length divided by step frequency). The drop in the stride length of theright (inner) leg during turning is responsible for the decrease of its walking ratio. (C) Mean velocity (left) and mean path length (right) of the body mid-point.
Mean values from gait cycles of both legs have been averaged because the body motion features is side-independent. Velocity and length of body displacementswere smaller during curved compared to straight-ahead walking. Horizontal lines with an asterisk join conditions between which significant differences(P
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to zero during straight-ahead walking. The distribution of these lags
during straight-ahead walking, cycle per cycle across all subjects, is
reported in the white bars of the histogram of Fig. 4C. When turning
was analysed (grey bars), the mean phase lag shifted toward a positive
value (corresponding to 57% of the cycle), indicating that the right
limb led with respect to the left (direction effect, F1,5 40,P 0.0001).
The increased duration of the stance phase of the right, inner, foot
was accompanied by leaning of the trunk towards the inner side of the
walking path (trunk roll). The positive correlation between the increase
in right foot stance duration and the extent of mean trunk roll
(producing increased loading of the inner foot) is shown in the plot
of Fig. 4B. Conversely, left foot stance duration was negatively
correlated with trunk inclination to the contralateral side, a sign of
unloading of the outer limb. In addition, the longer step achieved by the
left leg and the limb girdle rotation during turning significantly
(direction side-effect,F1,5 52, P < 0.001) increased the hip anglerange on the left side (3.0 2.08,P < 0.01), whereas the shorter stepof the right leg decreases its range (3.2 1.88; P < 0.005).
The decreased duration of the stance phase of the outer limb was
probably related to the obligatory overall higher velocity of the left
limb, given the longer path to be travelled with respect to the inner
limb. A further aspect of the asymmetry in the characteristics of right
and left limb displacement was the different velocity of their respective
swing phases. This is shown in the plot of Fig. 4D, where velocity of
the foot swing is depicted for right and left feet as a function of the
velocity of body progression along the curve. Indeed, the intercept of
the best-fit line differed (ANOVA/ANCOVA, P< 0.0001) between the twolimbs, whereas the slope did not (t-test, P > 0.2). An example of thelarger velocity of the outer foot is shown in the Fig. 4E, where two
velocity traces are superimposed for the right (black lines) and left foot
(grey lines) during two successive swing phases taken from the centre
part of the adjacent walking trial (in which the positions of the two
malleoli are drawn every 30 ms).
EMG patterns during turning
Spatial and temporal patterns of thigh and leg muscle EMGs were little
changed between straight-ahead and curved walking for both limbs.
Typical averaged traces from one subject during EO are shown in
Fig. 5. Traces have been normalized in duration on the basis of the
cycle duration and in amplitude with respect to the EMG during
sustained maximum voluntary contraction of the corresponding mus-
Fig. 2. Relationship between stride length and mean body velocity during (A) straight-ahead and (B) curved-gait cycles of the left (open circles) and right (filled
circles) leg. Data from all subjects and trials pooled. Mean values of (C) slope and (D) intercept of individual length-to-speed relationships, independently computedaccording to the direction of walking and side of the body. Change in direction did not modify slopes of speed-to-length relationships but affected the intercept(
P
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cle (see Materials and methods). The shape of the muscular activation
pattern during straight-ahead walking is not fundamentally modified
by walking along a curved path. The soleus muscles of both legs
showed a full-blown burst during the stance phase of gait. The tibialis
anterior muscles exhibited a double-peak burst at the onset of swing,
which lasted up to thefirst third of the subsequent stance phase. The
rectus femoris traces were almost superimposed on the second peak of
the tibialis burst. However, small but systematic changes occurred
between inner and outer limbs in both amplitude of EMG bursts and
their relative phases (temporal lag). The first of these changes was an
increase in the amplitude of the soleus burst during the stance phase in
the left leg and a decrease in the same burst in the right leg. Secondly,
during turning, there was an opposite phase shift in the tibialis EMG
burst between left and right legs. The left was anticipated and the right
was delayed with respect to the same burst in the same leg during the
straight-ahead condition. The activity of the peroneus muscle was
recorded in three subjects only. Nonetheless, its turn-related changes
were consistent across individuals and trials. The amplitude of the
peroneus burst generally decreased during curved walking in both legs.
However, such decreases were weak in the outer leg, but a sizeable
drop in the EMG activity was observed in the inner leg. In addition, the
burst of the right peroneus was delayed during the turn with respect to
the same burst observed during straight-ahead walking (see below).The results of the analysis made on all subjects and trials is
summarized in Fig. 6. The histograms of Fig. 6A and B depict mean
values of normalized EMG activity separated by side, visual and
walking conditions. The normalization was made based on the homon-
ymous burst during straight-ahead walking (data from EO and BF
pooled). Mean values for the soleus burst during stance and for the
tibialis anterior burst during swing are reported in Fig. 6A and B,
respectively. The statistical analysis showed a consistent difference in
EMG activity between left (8.1%;post hoctest,P 0.05) and right(11.1%; P< 0.05) soleus muscles during turning with respect tostraight-ahead walking (side direction effect,F1,5 11.5,P < 0.05).Post hoccomparisons also revealed that the activity increased on the
left side but decreased on the right side (P< 0.05 for left vs. right EMGcomparisons). However, there was a general increase in the tibialisanterior burst in both legs during turning with respect to straight-ahead
(on the average, 16.3% and 12.7% for left and right legs, respectively;
direction effect, F1,5 7, P< 0.05). The visual conditions are notfurther detailed in thefigure, because in no walking condition did lack
of vision modify the EMG features compared to walking EO.
The schematic diagram of Fig. 6C summarizes the main temporal
and amplitude characteristics of bursts of rectus femoris, tibialis and
soleus muscles in the two limbs, during both straight-ahead and curved
walking conditions. Onsets and ends of the boxes are the average
onsets ( SD) and ends ( SD) of muscle EMGs computed from allsubjects and EO trials. The height of theboxes corresponds to the mean
EMG amplitude (SD) normalized with respect to straight-ahead. In
thisfigure, the two components of the tibialis anterior burst have beenanalysed and drawn as two separate but adjacent boxes. This segrega-
tion of the two bursts of the tibialis allowed detecting a further feature
of its activity, namely a turn-specific increase (side direction effect,F1,5 9, P< 0.05) of the first component of the right muscle comparedto the activation during straight-ahead progression (SATU post hoc
comparison for the right limb,P < 0.05). The timing characteristics ofthe bursts of the various muscles can be more fully appreciated in this
representation. First, there was littlevariability of burst onsets and ends
for all subjects and trials, as testified by the short horizontal error bars.
Second, there was a strong consistency in the respective timing
between left limb and right limb, except for the tibialis anterior.
Indeed, the onset of the first component of the tibialis anterior burst
was slightly but significantly advanced for the left limb and delayed for
the right limb during turning with respect to the straight-ahead
conditions.
The consistency of this delay is further evident in the distribution
histograms of Fig. 7. These histograms report the distribution of the
soleus end and of the tibialis onset during the straight-ahead and
curved walking tasks, separately for left and right limbs. The interval
distribution of the end latencies of the soleus is centred around the end
of the stance phase (57% of the cycle). The onset of the tibialis is
delayed by a further 7.5% of the cycle. In addition, the width of the
distribution curve appears to be somewhat larger for the tibialis with
respect to the soleus (see range in the abscissas), regardless of the
walking condition. During turning, the soleus burst end was unaffected
Fig. 3. (A) Typical displacement of the body mid-point during the progressionalong straight or curved paths. Foot prints (the segment joining the malleolusand the foot) of the left and right leg during the stance phases are indicated. Onthe right, imaginary paths along which the body and the legs progress arerepresented (see text); the direction of travel is from bottom up and clockwise.(B) Relationship between the heading change and the difference between stridelength and path travelled by the body during one cycle. In this representation,
the displacement of each leg is referred to the body-centred reference frame.The more the body rotates, the larger the discrepancy between the stride lengthof inner and outer legs. The cycles during thestraight-ahead walking correspondtothe datapointsaround08. Those of thetransition from straight to curved pathshave been added to provide clarity to the figure, and roughly correspond to datapoints between 10 and 408 of heading change.
2003 Federation of European Neuroscience Societies, European Journal of Neuroscience, 18, 191205
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whereas the distribution of tibialis onset of left and right limbs shifted
in opposite directions (side direction effect, F1,5 32, P< 0.005).The mean values of these changes are reported in the middle inset of
the same figure. (SATU post hoc comparison, P < 0.01 for left andright legs). An analysis of the temporal coupling of subsequent
activations of the soleus and tibialis anterior was made according to
the trajectory type. However, we found no strong correlation between
the end of the soleus burst and the onset of the tibialis burst, regardless
of the side (r 0.05,ns;r 0.16,P < 0.05 for the left and right limb,respectively), the trajectory followed (r 0.11, P < 0.05; r 0.05, nsfor straight and curved path, respectively), or within left and/or right
limbs during turning (r 0.08, ns; r 0.11, ns for the left and rightlimb, respectively).
A general comparison of the effects of turning across left and right
soleus, tibialis anterior and peroneus longus muscles is given in Fig. 8.
Traces were obtained by averaging all signals from all subjects during
Fig. 4. (A) Mean duration (SD) of the stance phase as a percentage of the gait cycle according to walking direction and body side. During turning, the stanceduration increased and decreased in inner and outer legs, respectively (P< 0.01). (B) Relationship between the relative duration of the stance phase and mean trunkroll, for all gait cycles under all conditions (except for side) pooled. The decrease in stance duration of the left (outer) leg during turning was associated with a
significant leaning of the trunk toward the interior, and vice versa for the right leg. (C) Distribution of the phase lags of the left with respect to the right leg. Thedistribution shifted toward positive values during curved walking, indicating that the inner limb led with respect to the outer. The method of calculation of the phaselag based on limb axis angulardisplacements of both legs is indicatedin the right inset. (D). Therelationship between mean malleolus velocity during theswing phaseand mean body velocity is shown. The velocity of the foot is systematically larger in the outer limb than in the inner limb owing to the larger distance to be covered bythe outer foot during the swing phase. (E) An example of the time course of the velocity of the malleolus of both legs is depicted. A simple illustration of the side-
specific modulation of the limbvelocity during the turn is revealed by the representation at the centre of the panel. The instantaneous position of the malleolus of bothinner and outer leg is displayed every 30 ms. The body mid-point trajectory is also shown. Note the increasing distance between two successive positions of the outerfoot in the central part of the swing phase.
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turning and normalizing them with respect to the mean activation during
straight-ahead walking, each limb individually processed. Figure 8
summarizes EMG changes in timing and amplitude between the corre-
sponding muscles of inner and outer limbs during the progression along
the curved path. The shape of the envelopes, reflecting the activation
profile of muscles, was basically unchanged, as indicated by the very
high value obtained by cross-correlating the two profiles. No phase
shift was observed between right and left soleus muscles. However,
a difference was found in the timing of tibialis and peroneus
muscle bursts. The waveform profiles of the left leg led those of the
right leg by 11 and 40 ms, corresponding to temporal delays of 1.02 and
3.6% of the cycle duration, for the tibialis and peroneus muscles,
respectively.
Discussion
This investigation was an attempt to understand whether and to what
extent the central nervous system modifies its output, or part of it, in
order to produce a continuous curvilinear locomotion. Emphasis has
been put upon the analysis and comparison of straight-ahead with
curved walking.
Gait features
Frequency
Walking along the circular path, either with vision (EO) or blindfolded
(BF), produced no major changes in stepping frequency, thus indicat-
Fig. 5. Representative EMG activity of thigh and leg muscles for left and right limb during straight-ahead and curved walking. Traces were obtained by averagingtime-normalized EMG traces for all trials of one subject walking in the eyes-open condition. EMG amplitude has been normalized in terms of maximal voluntarycontraction, and is expressed as a percentage of that activity. The time course of the ankle angle is traced at the bottom of the figure. Although the general spatial andtemporal patterns of muscle activity were not radically different between the two walking paths, the progression along the curve was accompanied by subtle limb-
specific modifications in muscle activity (see text).
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ing that the transition from a straight to a curved path did not imply a
reorganization of rhythm production, or that the basal rhythm is
adapted to both conditions. There was also no difference in duration
of the right and left cycles during turning. The CNS would indeed
generate a strongly coupled locomotor pattern, during straight-ahead
locomotion as much as during locomotion along a curved path. It
is of interest that crayfish strongly modulate the frequency of each
locomotor limb while they progress along curvedpath (Domenici etal.,
1998), suggesting that temporal coupling across effectors is
not a systematic rule of turning but rather an exception of biped
walking.
The same rhythm was propagated to both legs, in spite of the
obvious but nontrivial consideration that the length of right and left
strides was definitely different when producing the curved trajectory.
With the present radius of curvature, and an average distance between
the feet of some 20cm, the inner foot had to travel along a circle with a
length of15% less than the outer foot. This led to a correspondingdecrease in the length of the right stride (see Fig.3). When the
movement of legs was referenced to body co-ordinates, the length
of left and right strides increasingly diverged with the increase in
heading change. However, the amount of stride length changes with the
increase in velocity obeyed a similar law for both legs. Notably, this
relationship was the same for the left leg during both straight and
curved trajectories, for both slope and intercept. For the right leg the
slope did not change, but the intercept diminished during turning. The
difference between the intercept for the relationships of left and right
Fig. 6. Mean values of EMG activity during straight-ahead and turning gait cycles in the soleus (A, stance phase) and tibialis muscle (B, swing phase) of both legs.Mean valueshave been normalizedwith referenceto themean value of EMGactivity duringthe progression along thestraight path (EOand BF, respectively), foreachlimb and gait phase independently (P
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legs matched the difference in radius of virtual circles along which the
feet moved.
Changes in temporal and spatial features of leg movements were
mirrored in the synthetic measure of gait provided by thewalking ratio,
a velocity-independent index of walking pattern (Sekiya & Nagasaki,1998). This measure confirmed that commands to produce outer leg
forward progression were the same under both straight-ahead and
curved walking. The behaviour of the inner leg was different in
amplitude of progression but not so in cadence. It is easy to conclude
that the CPG distributes its commands to the two legs with the same
frequency, which does not impede the two legs advancing at different
velocities. Others have shown that the two CPGs are normally strongly
entrained (Riek & Carson, 2001) and produce synchronous output to
the two sides of the body (Guadagnoli et al., 2000). Therefore, during
curved walking the CPG would need to distribute a differently
patterned command to the two sides, in a manner appropriate to
perform turning.
Intrinsic temporal features of gait
Not only were spatial features of inner and outer leg movements
different during turning, but also somekey temporal features of thegait
pattern were changed, yet within the cadre of the unchanged frequency.
The duration of the stance phase of gait diminished and increased in
outer and inner legs, respectively. This discrepancy in the temporal
sequences of gait events of the inner and outer legs provoked a
phase lag between the overall limb displacements, which corresponds
to 7% of the total cycle duration. Changes in the phase relationshipof this entity between the two limbs have been observed during
straight-ahead walking in toddlers, and it has been suggested that
they are connected to gait instability (Clark, 1995). Conversely, we
show here that this phase lag is a necessary condition to produce body
rotation.
The longer duration of the swing or transport phase (consequence of
the shorter stance phase) allows more time for the outer leg to travel the
longerdistance imposed by turning. Swing duration during turning waslonger than during straight walking, because the path travelled by the
foot was not linear during turning but bent because of the concomitant
body rotation. This explains the different vertical distance between the
lines bestfitting velocity of foot swing against body progression for the
right and left foot. In other words, the difference in both stance
duration and travelling distance between left and right feet imposed
different swing velocities. In this regard, turning-related gait features
were reminiscent of those associated with the adaptation of walking on
a treadmill with split belts adjusted at different speeds. Indeed, Dietz
and collaborators (Dietz et al., 1994; Prokop et al., 1995; Zijlstra &
Dietz, 1995; Jensen et al., 1998) have shown that, under such condi-
tions, stride length was larger on the fast side (as for the outer leg
during turning, in our case) with respect to the slow side. At the same
time, the stance duration was shortened on the fast leg whereas it
increased on the slow leg, and inversely for swing phase duration.
Concomitant with the increased duration of the stance phase of the
right, inner, leg, the trunk leant towards the interior. This was con-
firmed by a significant relationship between trunk roll and stance
duration. There is therefore an association between trunk leaning to the
inner side, increase of walking speed during turning (see companion
paper) and increased stance duration of the inner limb. The displace-
ment of the trunk could contribute to the modulation of the temporal
features of the gait pattern, because loading the inner leg (and
unloading the outer leg) might produce a phase modulation through
re-afferent input from the evolving movement (see below).
Fig. 7. Distribution of the ends of soleus EMG burst and onsets of thefirst burst of tibialis anterior in the left (upper panel) and right (lower panel) leg, separatedaccording to the direction of walking. No difference occurred in the end of the soleus burst, regardless of side and trajectory conditions (compare upper and lowergraphs of the left panel). With respect to straight-ahead walking, the distributionof tibialis anterior burst onsets measured during turning wasshifted toward lower andhigher values on the left and right leg, respectively. Limb-specific mean changes ( SD) in the occurrence of the onset of tibialis anterior burst is indicated in the insethistogram. Significant differences are indicated as in Fig. 3.
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EMG pattern
Subtle but consistent changes, which appear to be associated with the
above described motor behaviour, occurred in the leg muscles
recorded. The similarity between the patterns of muscular activation
responsible for the body progression along straight or curved paths
indicates that turning did not induce dramatic changes in the organiza-
tion of the efferent commands to these muscles. Indeed, EMG pattern
presented similar shape- and phase-dependent modulation during the
two types of motion. Nevertheless, amplitudes and timing changes
were consistently observed.
Soleus
The overall pattern of soleus activity was similar during turning andstraight-ahead walking. However, the amplitude of the soleus burst
decreased during stance in the inner leg (11%) and increased during
turning in the outer leg (8%). Overall, the difference between the bursts
of inner and outer legs during walking was 18%. At the same time,left and right strides showed a discrepancy in their length (left stride
longer than right stride) of about the same amount. The precise origin
of extensor muscle modulation during walking along the curve is not
readily explained.
The relationship between EMG amplitude and stride length does not
seem to be generalisable. On the one hand, the decrease in soleus burst
amplitude during turning on the right with respect to left side can be
related to the shortening of the right stride with respect to the left. The
soleus burst of the right leg also diminished during turning with respectto its burst during straight-ahead walking. However, in the two cases
there was no correspondence between average EMG changes and
average stride length changes. However, the left soleus increased not
only with respect to the right muscle during turning, but also with
respect to the same left soleus during straight walking. However,
during straight walking the stride length of the left leg did not change
with respect to its stride length on the curved path.
We feel that any attempt to explain these discrepancies should take
into account the fact that body orientation changes during turning. This
can create nonoptimal biomechanical conditions for the propulsive
action of the leg muscles, owing to the different spatial relationship
between the force vector produced by soleus muscle action and the
direction of the moving body. In turn, any disadvantage would be
differently shared by the two limbs. In the companion paper weshowed that foot yaw in relation to body heading was different for
the two feet during turning with respect to straight walking. In
particular, the left foot tended to approach the body trajectory while
the right foot tended to turn to the inner side of the trajectory. Within
this general trend, however, the relationship between foot positioning
and body trajectory changed during the completion of the stance phase.
At heel strike the left foot was almost aligned with heading direction
but progressively rotated with respect to body direction, thereby
diminishing the mechanical efficiency of the muscle action. This
might therefore require a stronger muscle action to support body
propulsion along the curved trajectory. Soleus activity was also larger
with respect to that recorded during straight-ahead walking,
where stride length was not different from that observed during
turning. Such an enhancement of the outer extensor muscle activity
probably contributes to the generation of the torque necessary for
producing the body turn. Moreover, because the stance phase duration
is shortened, a larger soleus activity would help create the torque for
turning.
An inverse trend was observed for the right foot, which was placed
on thefloor at a wide angle with respect to heading, and became almost
parallel to body direction at the time of toe-off. This might explain the
need for less muscle activity in the right than left soleus muscle during
turning, and in the same right soleus during turning compared to
straight walking. Two further effects of turning, liable to require
modulation in opposing senses of right soleus activity, are the smaller
Fig. 8. Comparison of EMG envelopes of inner and outer legs, recorded duringwalking along the curved trajectory. The mean profiles have been obtained byaveraging the mean traces of all subjects after normalization of their amplitudebased on muscular activity during straight-ahead cycles. The discrepancy inleftright amplitudes is revealed by the hatched area, the pattern of whichindicates the leg for which the muscle activity increases compared to the otherleg (see legend). The quantification of the phase shift between EMG envelopeshas been obtained by cross-correlating thewaveforms of the inner and outer leg.The value of the phase lag is expressed as a percentage of the cycle and inabsolute duration, and is reported close to the corresponding traces. A positivevalue means that the EMGprofile of the outer leg leads thatof the inner leg.Ther-value is also indicated.
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length of the inner stride, thereby requiring less propulsive force for the
right leg, and the upper body displacement toward the inner side,
possibly requiring a stronger supportive action of the right foot
extensor muscles (Fouad et al., 2001).
The EMG profile of the soleus did not shift in time (for either onset
or end time) with the change in the trajectory, for either the left or right
side muscles. One would thus conclude that central commands for
turning almost selectively modulate the amplitude but not the timing of
the command delivered to the two muscles.
Tibialis anterior
There were subtle but significant differences in tibialis anterior muscle
activity. Thefirst component of its double burst began at the onset of
the swing phase and produced foot dorsiflexion. The second compo-
nent anticipated heel strike and persisted for the first part of stance,
braking the foot drop before the burst of the soleus muscle. The tibialis
anterior was almost silent during the burst of the antagonist soleus
during mid stance, and there was no effect of walking type in this
phase. During the swing phase of curved walking, the amplitude of
tibialis anterior activity significantly increased in the left (16%) and
right (13%) legs with respect to the activity recorded during straight-
ahead walking.
The increase in the left tibialis EMG burst was partly due to the factthat swing duration was longer during turning than during straight-
ahead walking. In addition, the burst was earlier during turning (see
below). As a consequence, a larger share of the second component of
the tibialis burst occurred during the swing phase, thereby producing
the overall increase of the tibialis activity during the swing phase of the
gait cycles along the curved path. This event may be connected with
the need to enhance left tibialis stiffness during the swing phase, to
avoid the foot plantar flexion possibly favoured by increased foot
velocity, and to ease foot rotation towards the interior of the curve.
The case of the inner (right) leg was different, and the major increase
in the right tibialis muscle activity was limited to the burst beginning at
the onset of the swing phase. This event can be explained by the
temporal constraint acting on the inner foot. Indeed, owing to body
position being leant towards the interior of the curve, the shorter lengthof the stride and the decreased duration of the swing phase, the foot
must be dorsiflexed more rapidly than during straight walking. As a
corollary, the rate of change of ankle dorsiflexion occurring at the
beginning of the swing phase was increased during turning (see the
ankle angle traces in Fig. 5). It has been shown elsewhere that
modulation of the amplitude of the tibialis burst (as during continuous
soleus or tibialis vibration during walking) is accompanied by a
corresponding modulation of the speed and amplitude of dorsiflexion
(Courtineet al., 2001; Verschueren et al., 2002).
Turning implied a slight but consistent side-specific modulation in
the timing of the tibialis burst: it was advanced in the left leg and
delayed in the right, during curved with respect to straight-ahead
walking. This was possibly responsible for the shorter duration of
the stance phase on the left and the longer duration of the stance phase
on the right (Duysens & Pearson, 1980; Rossignol, 1996). However, the
correlation between onset of tibialis burst and onset of the swing phase
(as a percentage of cycle duration), although mildly significant, was not
consistent across subjects, preventing us from making strong conclu-
sions about this point. Similarly, no correlation between end of
soleus and onset of tibialis was observed across limbs or trajectory
types. The absence of this correlation suggests that the reciprocal
inhibition between ankle antagonists was not responsible for the
modulation of either burst timing change during the turn. If anything,
the mild correlation present during straight trajectories vanished during
turning.
Peroneus longus
During straight-ahead walking, there was a coactivation of peroneus
and soleus muscles. Such activity was not due to crosstalk between
soleus and peroneus muscles, because it was checked that pure foot
plantarflexion did not induce activity in the peroneus (see also Hunt
et al., 2001, for straight walking). Both soleus and peroneus muscles
were active during the stance phase and their bursts were similar in
shape and timing. The peroneus assists in plantar flexion and produces
abduction and eversion of the foot, which counteracts the internal
rotation action of the triceps muscle, and helps to produce the lateral
displacement of the body weight from theactual stance foot to the next,
contralateral, foot (Hunt et al., 2001). During turning, relatively large
changes occurred in the timing and amplitude of the peroneus burst
with respect to straight-ahead. First, the amplitude of the burst
decreased in both legs, but almost two times more in the inner than
in the outer leg. This general decrease in peroneus activity may be due
in part to the decrease in the body velocity during turning. Never-
theless, side-specific modification of muscle activity rather suggests
that these changes are directly connected to the achievement of body
rotation. This would be not particularly astonishing because peroneus
action produces a medio-lateral displacement of the body in addition to
helping progression. Although peroneus muscle action ensures lateral
body equilibrium, regardless of walking conditions, its functionalimplication should be different during turning than during straight-
ahead walking.
Turning implies an opposite, asymmetric, action of the two limbs in
order to produce the force pulling the body to the ever-changing
direction of the curved trajectory. In the companion paper, we reported
that the change in heading direction is associated with a narrowing of
stance width of the left leg. More precisely, the more the body rotates
the closer the distance between the line joining two successive left
(outer) footprints and the right foot print. As a consequence, the body
need not be displaced toward the inner foot because the latter is already
positioned underneath the body weight, as also indicated by the
decrease in the distance of the right foot to the body trajectory, thereby
requiring less action of the right peroneus muscle. The peroneus of the
left side, in turn, need not increase its activity during stance, either,
because its pushing action toward the inner side of the trajectory is
enhanced by the mechanical moment created by the increased distance
between the stance foot and the position of the body. During turning,
the combined muscular action of the peroneus and of the soleus of the
outer leg is then mainly devoted to assisting body rotation.
However, at the beginning of the swing phase the peroneus burst
appears to behave in a different way in the two legs: on the right side,
there is prolonged activity and relative increase of the burst amplitude.
We suggest that it is because of the relative increase in duration of the
stance phase on the right with respect to the left side, and because of
the need for the right feet to be extra-rotated to prepare the subsequent
foot heel strike.
Rectus femoris
On average, the rectus femoris was active around the transition
between swing and stance phases. In general, its activity was of
smaller amplitude than that of the other recorded muscles. No sig-
nificant difference could be found in the amplitude of the bursts of the
same muscle (left or right) between straight and curved walking. No
differences were found, either, when the two limbs were compared
during turning. This was equally true in terms of timing. Increase in
rectus femoris burst has been shown to occur during rapid complete
turning and it has been explained by the need to brake body progres-
sion and allow a quick spin turn (Hase & Stein, 1999). Absence of any
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rectus EMG modulation, in our opinion, can therefore be taken as a
further indication of the smoothness of progression along the curved
trajectory.
Neural substrates for motor implementation of the turn
The actual neural substrates involved in the production of continuous
steering along a curved path cannot be identified from the present
results. Nevertheless, a tentative explanation can be based on the
reconsideration of the known sensory and motor mechanisms that
modulate the muscular pattern for walking.In most animal species, locomotion is controlled by central pattern-
generating networks (CPGs) located within the spinal cord, which are
under the continuous influence of supraspinal signals (Grillner, 1981;
Pearson, 1993; Rossignol, 1996; Burke, 2001). In addition, the sensory
feedback from the moving body parts is integrated within spinal
networks and may even be part of them, directly participating in
the activation of muscles for walking (Duysens & Pearson, 1980;
Gurfinkel et al., 1998; Nielsen & Sinkjaer, 2002). In this section, we
considerfirst the sensory inputs, which may modulate spinal networks
in order to produce and/or accompany the body turn. Then we will deal
with the neural structures possibly involved in re-programming the
appropriate motor output for steering along the curve.
Sensory inputs
During the performance of the turn, the body becomes increasingly
asymmetric in the motion of body parts. Consequently, the asymmetric
inflow of movement-related feedback might contribute to shaping the
motor commands directed to the muscles. From where and which
sensory modality would any asymmetric input come? The role of vision
may be excluded, at least under the present condition where subjects
reproduced a memorized trajectory, because the motor program for
turning was not obviouslymodified by the presence or absence of visual
cues. In normal subjects, the role of vision may be limited to informing
motor centres about the orientation and location of the body in the
earth-based reference frame, thereby simplifying navigation and
dynamic equilibrium. If anything, it is remarkable that, when vision
was allowed, the production of the curved path was not greatlyimproved with respect to BF (see companion paper).
Neck and vestibular receptors might be crucial during turning
(Fitzpatricket al., 1999; Bent et al., 2000; Bove et al., 2001). When
a change of heading is achieved, the head is normally turned towards
the interior (Grasso et al., 1996; Grasso et al., 1998a; Grasso et al.,
1998b; Patla et al., 1999; Hollandset al., 2001; Imaietal., 2001; Vallis
et al., 2001; Glasaueret al., 2002; Hollands et al., 2002). Under our
experimental conditions, the absolute range of periodic oscillations of
the head increased with the trajectory tightness (see companion paper).
Therefore, the pattern of head movement produced two superimposed
asymmetrical components for vestibular and lateral neck propriocep-
tive inputs. Thefirst component lasts throughout the whole duration of
the gait cycle. The second component is phasic and leads a change in
heading by 200 ms. Tonic head orientation may help in monitoringbody orientation with respect to the inertial force produced by the
rotation, and in detecting body deviation from the required equilibrium
(Grassoet al., 1996; Pozzo et al., 1998; Imai et al., 2001). The phasic
input, in turn, may be directly involved in the motor command
producing the rotation of the body. We have previously shown that
lateralized stimulation of neck muscle receptors by vibration provoked
involuntary body deviation during walking (Bove et al., 2001) or
rotation during stepping-in-place (Boveet al., 2002). In the same vein,
galvanic-induced asymmetric vestibular input causes subjects to turn
from their planned trajectory (Fitzpatrick et al., 1999; Bent et al.,
2000; Jahn et al., 2000; Dietz et al., 2001). This hypothesis is
consistent with the observation made by Hollands et al. (2001) that
subjects showed difficulties in achieving changes in walking direction
when the head was immobilized with respect to shoulders. Note,
however, that asymmetrical gait is produced during split-belt walking
despite a neutral head position (Dietz et al., 1994; Zijlstra & Dietz,
1995). Whether the neural mechanisms underlying the split-belt
simulation of turning condition may be similar to those actually used
to perform curved walking is an open question.
Both neck and vestibular inputs project onto vestibular nuclei of the
brainstem (Gdowski & McCrea, 1999, 2000), the discharge of whichincreases the level of extensor muscle activity during gait (Orlovsky,
1972; Matsuyama & Drew, 2000a). Matsuyama & Drew (2000b,a)
showed in the freely walking cat that head movement induces phasic
modulations of vestibular nuclei, which contribute to tuning the level
of EMG activity in leg muscles. During curved walking, asymmetric
vestibular and neck sensory inputs can thus possibly facilitate the
respective increase and decrease of the outer and inner ankle extensor
muscles observed in our experiment.
Information conveyed by proprioceptors embodied in the asymme-
trically moving legs may also be important for the turning-related
regulation of both timing and amplitude of muscular activation
patterns. Displacements of body weight toward the inner leg modify
the input from load receptors on both body sides (Duysens & Pearson,1980; Dietz & Duysens, 2000; Duysens etal., 2000). Consequently, the
onset of the swing phase would be delayed on the inner limb owing to
the persistent input from leg muscles and foot sole receptors (Duysens
& Pearson, 1980; Stephens & Yang, 1999; Pang & Yang, 2000; Fouad
et al., 2001). The contrary would occur on the left, outer, leg. In
addition, the longer step achieved by the left leg and the limb girdle
rotation during turning increases the hip angle range on the left side,
whereas the opposite occurs on theright. The resultant mismatch might
be associated with a delay in the end signal (the inputs from the hip
muscles and joint receptors) for the phase change of the respective gait
cycle (Grillner & Rossignol, 1978; Pang & Yang, 2000), or with the
modification of the relative coupling between the CPG centres of both
sides, otherwise driven at the same gait frequency on both sides by the
supraspinal tonic input. Recently, examination of the linkage betweenpatterns of activity in several hind-limb motor pools and the modula-
tion of cutaneous reflex pathways duringfictive locomotion in cats has
allowed the notion that some aspects of the locomotor pattern forma-
tion can be separated from rhythm generation (Burke etal.,2001)to be
forwarded. This might imply that the two CPG functions may be
embodied in distinct neural organization.
Supraspinal motor output
Obviously, under the present conditions turning is a deliberate action,
both for its initiation (not addressed here) and during its execution
during the steady-state phase of steering. To what extent, or by means
of which mechanisms, higher centres participate in producing walking
along a curved trajectory cannot be thoroughly discussed on the basis
of the present data. The curved trajectory produces inertial forces that
modify the context of dynamic equilibrium. Whereas straight-ahead
walking mainly requires antero-posterior equilibrium, greater
demands in lateral equilibrium emerge during body rotation. Drew
and colleagues showed that reticulo-spinal neurons contribute to the
selection of patterns of postural activity while intact cats walk along
level (Matsuyama & Drew, 2000a) and sloping (Matsuyama & Drew,
2000b) surfaces, or cross obstacles (Prentice & Drew, 2001). Similar
results have been found when lateralfictive turns are generated in the
swimming lamprey (Fagerstedtet al., 2001). Dynamic postural adjust-
ments accompanying body rotation may probably also be derived from
similar mechanisms in humans (Massion, 1992). Further, how much
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the motor cortex contributes to the ultimate motoneuron output during
turning is hard to estimate. It has been recently shown that the motor
cortex has access to leg muscles during locomotion (Capaday et al.,
1999; Christensen etal., 1999; Schubert etal., 1999; Christensen etal.,
2001; Petersenet al., 2001), and that ample areas of the fronto-parietal
cortex are activated during walking (Fukuyama et al., 1997; Miyai
et al., 2001). Admittedly, much more effort is necessary to expand the
story of human turning and its control, given that turning can only
complicate the control of human bipedal walking, which is already
inherently unstable in the straight-ahead condition (Capaday, 2002).In particular, the dual integration within the locomotor spinal
networks of the processes underlying navigation and those controlling
equilibrium appears to pose both theoretical and methodological
challenges.
Acknowlegments
This research was supported by grants from the University of Pavia, the Italian
Ministry of Health and the Fondazione Salvatore Maugeri (IRCCS). G.C. wassupported by a grant from theFrenchMinisterof Research.We aremost gratefulto Dr Paul Stapley, who edited the last version of the manuscript.
Abbreviations
ANCOVA, analysis of covariance; ANOVA, analysis of variance; BF, blindfolded;CPG, central pattern-generating network; EMG, electromyography; EO, eyesopen; SA, straight ahead; TU, turning.
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