Limited Transfer of Newly Acquired Movement Patterns
across Walking and Running in Humans
Tetsuya Ogawa1*, Noritaka Kawashima1, Toru Ogata1, Kimitaka Nakazawa2
1 Department of Rehabilitation for the Movement Functions, Research Institute, National Rehabilitation Center for Persons with Disabilities, Namiki, Tokorozawa, Saitama,
Japan, 2 Graduate School of Arts and Sciences, The University of Tokyo, Komaba, Meguro, Tokyo, Japan
Abstract
The two major modes of locomotion in humans, walking and running, may be regarded as a function of different speed
(walking as slower and running as faster). Recent results using motor learning tasks in humans, as well as more direct
evidence from animal models, advocate for independence in the neural control mechanisms underlying different
locomotion tasks. In the current study, we investigated the possible independence of the neural mechanisms underlying
human walking and running. Subjects were tested on a split-belt treadmill and adapted to walking or running on an
asymmetrically driven treadmill surface. Despite the acquisition of asymmetrical movement patterns in the respective
modes, the emergence of asymmetrical movement patterns in the subsequent trials was evident only within the same
modes (walking after learning to walk and running after learning to run) and only partial in the opposite modes (walking
after learning to run and running after learning to walk) (thus transferred only limitedly across the modes). Further, the
storage of the acquired movement pattern in each mode was maintained independently of the opposite mode. Combined,
these results provide indirect evidence for independence in the neural control mechanisms underlying the two locomotive
modes.
Citation: Ogawa T, Kawashima N, Ogata T, Nakazawa K (2012) Limited Transfer of Newly Acquired Movement Patterns across Walking and Running in
Humans. PLoS ONE 7(9): e46349. doi:10.1371/journal.pone.0046349
Editor: Alejandro Lucia, Universidad Europea de Madrid, Spain
Received May 23, 2012; Accepted August 31, 2012; Published September 27, 2012
Copyright:  2012 Ogawa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by a Grand-in-Aid for Young Scientists (B) from the Japan Society for the Promotion of Science to T. Ogawa. The funder had
no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: ogawa-tetsuya@rehab.go.jp
Introduction
In everyday life, humans use two major modes of locomotion:
walking and running. By definition, walking is known as
a movement in which at least one foot is always in contact
with the ground, whereas running involves aerial phases where
both feet are off the ground. Both similarities and dissimilarities
between
the
modes
have
been
demonstrated
from
the
perspectives
of energetics [1], limb movements [2,3], and
muscle functions [2,4,5]. Because of the spontaneous behavior
to transit into the opposite modes in accordance with changing
speed (walk-run or run-walk transition) [2,6–8], these two
movement modes seem dependent on the demand for different
locomotion speeds.
On the other hand, by referring to earlier studies focusing on
the behavioral aspect of human motion in simple upper-limb
movements [9,10] and gait [11,12], neural control mechanisms
underlying human movement are considered as very specific to
given tasks or contexts. Combined with direct evidence obtained in
animal models [13,14], there would be a possible independency in
the neural mechanisms specific to different modes of locomotion.
Walking and running in humans therefore, may not only be
dependent on different speeds but also have discrete control
mechanisms capable of the respective modes. The present study
addressed the possibility by utilizing motor adaptation paradigms
that have been well established in the field of motor control,
especially in the last decade [9–12].
Based on the hypothesis that independent neural control
mechanisms underlie walking and running, we established working
hypotheses as follows. 1) After the acquisition of a novel movement
pattern (adaptation) in one of the modes, the emergence of the
novel pattern in the subsequent trials is evident only within the
same mode and limited in the opposite mode (thus, limited transfer
across walking and running). In addition, 2) storage of the novel
movement pattern in the respective mode is maintained in-
dependently of the opposite mode. The acceptance of these
working hypotheses will provide indirect evidence of independent
neural mechanisms underlying human walking and running. A
section of the results in the present study have been presented in
abstract form [15].
Methods
Subjects
Twenty-four healthy male volunteers (age range, 22 to 49 years
old) with no known history of neurological or orthopedic disorders
participated in the study. Each subject was tested in two of four
experimental protocols (Figure 1). Twelve of them participated in
experiments 1 and 2, while the other 12 participated in
experiments 3 and 4. The order of participation was randomized
across subjects.
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Ethics Statement
Each subject gave written informed consent for his participation
in the study. The experimental procedures were approved by the
local ethics committee of the National Rehabilitation Center for
Persons with Disabilities, Japan, and were conducted in accor-
dance with the Declaration of Helsinki.
Experiment
In the present study, the subjects walked and ran on a split-belt
treadmill (Bertec, Columbus, OH, USA), having two belts (one
underneath each foot), each driven by an independent motor. The
treadmill was operated either symmetrically (both belts moving at
the same velocity) or asymmetrically (at different velocities).
During the baseline period, the treadmill was operated symmet-
rically and the velocity was adjusted to 1.5 m s21. This was the
speed where all the subjects could both walk and run comfortably
in our pilot experiment. Subsequently, the subjects learned to walk
(experiments 1 and 2) or run (experiments 3 and 4) on an
asymmetrically driven treadmill for 10 minutes. The speed of one
belt was increased by one third from the baseline (0.5 m s21),
whereas that of the other was decreased by one third; thus, the belt
speeds were 2.0 and 1.0 m s21, respectively. The direction of
speed change (either faster or slower) was randomized across
subjects and the experimental protocol. After the 10-minute
adaptation period, the belt speed was returned to symmetry (for
the washout periods) as in the baseline periods. Here, the subjects
were instructed to walk and run (experiments 1 and 4) or run and
walk (experiments 2 and 3) in order for 1 minute each in duration
depending on the experimental protocols (Figure 1). Between all
testing periods (baseline walk, run, adaptation, washout walk (run),
and run (walk)), the treadmill was stopped once and restarted
immediately by the experimenter with an acceleration (decelera-
tion) of 0.5 m s22. The subjects were instructed to walk or run
normally as they looked at a wall approximately 5 meters in front
of them and were instructed to refrain from looking down at the
treadmill belts in order to avoid any visual biases on the speed.
The subjects were also instructed to always start their task by
either walking or running from the first step depending on the
testing sessions. For safety, one experimenter always stood by the
treadmill during the experiment, and the subjects could hold onto
handrails mounted on both side of the treadmill in case of risk of
falling. However, all the subjects satisfactorily completed the
testing sessions without using the handrails.
Recordings and Analysis
Three orthogonal ground reaction force (GRF) components
(mediolateral (Fx), anteroposterior (Fy), and vertical (Fz)) were
detected by two force plates mounted underneath each treadmill
belt. The force data were low-pass filtered at 5 Hz and were
digitized at a sampling frequency of 1 kHz (Power Lab, AD
Instruments, Sydney, Australia). From the Fz component of the
GRF, the moments of ground contact and toe-off were detected on
a stride-to-stride basis using a custom-written program (VEE pro
9.0, Agilent Technologies, Santa Clara, CA, USA). Data on the
first stride cycle of each testing session were removed for later
analysis in order to minimize the influences of perturbation
induced by the initiation of the treadmill movements.
The aspects of walking and running were investigated by
addressing the peak anterior braking force upon foot contact for
every stride cycle. In our pilot study, we demonstrated that, among
all of the orthogonal ground reaction force (GRF) components,
only this component showed clear aspects of adaptation and
aftereffects with the return to symmetrical belt condition in both
walking and running. A series of previous studies focused on
temporal and spatial gait parameters such as stride and step
length, stance and swing time, double support time, and the
relationship in the gait phase between the two legs to address
adaptive behavior of the split-belt treadmill walking [11,12,16,17].
However, given that gait speed is a quotient of length (spatial) and
the time (temporal factors), subjects could potentially employ
different strategies across individuals (either walking or running
with spatially symmetrical with temporally asymmetrical move-
ment patters, temporally symmetrical with spatially asymmetrical
movement patterns, or changing the both parameters) with
exposure to belt conditions with changing speed.
Since the stride cycles taken during the testing sessions varied
across subjects and tasks (walk or run), the obtained data were
averaged over stride cycles in 3-second bins and were normalized
to the mean during the baseline of each movement task (walk or
run) to allow intersubject comparisons.
For statistical comparisons, two-way analysis of variance
(ANOVA) with repeated measures was used to test for statistically
Figure 1. Experimental protocols (1 through 4) adopted in the present study. Subjects underwent adaptation tasks of either walking (1 and
2) or running (3 and 4) on an asymmetrically driven treadmill (one belt was set at 1.0 and the other at 2.0 m s21) for 10 minutes. Walking and running
patterns on a normally operated treadmill (at 1.5 m s21 bilaterally and 1 minute each in duration) before and after the adaptation were compared on
the basis of the modes of adaptation.
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significant differences in the aftereffects, with factors of movement
modes (walk or run) or the previously imposed adaptation tasks
and the time in the respective 60-second washout period. Data are
presented as the mean and standard error of the mean (mean6-
SEM). Significance was accepted when P,0.05.
Results
The number of stride cycles taken under the identical speed
differed depending on the movement mode and among subjects.
Regardless of the belt condition (symmetric at 1.5 m s21 or
asymmetric at 1.0 m s21 and 2.0 m s21), subjects on average took
approximately 60 stride cycles for walking and 80 strides for
running every minute.
All of the subjects reported that their movement patterns were
disturbed when returning to the symmetrical belt conditions after
walking on the asymmetrically driven treadmill, as described in
previous studies [11,16]. For running after adapting to run on
asymmetrical belts, subjects also reported their movement patterns
as perturbed. Figures 2 and 3, respectively, show typical examples
of antero-posterior (braking and propulsion, respectively) ground
reaction force waveforms under different time points (A), time
series changes in the peak anterior force for both fast and slow
sides (B), and the differences in the peak force between the sides
(C) on a stride-to-stride basis for walking (Figure 2) and running
(Figure 3).
During the baseline where the belt conditions were symmetrical,
the waveforms were very similar in shape and the amplitude (both
anterior and posterior components) between the sides for both
walking (Figure 2 (A)) and running (Figure 3 (A)). With exposure to
the asymmetrical belt condition, the shapes resulted in prominent
differences, an indication of different movement patterns between
the fast and the slow sides. For both walking and running,
modification in the amplitude of peak anterior braking force took
place in the 10-minutes learning periods, including both rapid
changes in the earlier phase (up to around 1 minute) followed by
slower gradual changes (Figure 2 (B) and Figure 3 (B)). The
modification in the amplitude was an increment for the fast side
and a decrement for the slow side, respectively. It is especially
noticeable here that the braking force in the slow side almost
disappeared at the fully adapted state in running (Final of Learning
period in Figure 3 (A) and near 10 minutes in the Learning period
in Figure 3 (B)). As a consequence, there were large differences
between the sides (asymmetry) (Figure 2 (C) and Figure 3 (C)).
With return to the symmetrical belt condition (washout), the
amplitudes of the force differed to a great extent between the sides
despite the identical belt speed to that during the baseline. In
detail, there were initially an overshoot in the amplitude for the
fast side and an undershoot in the slow side for both walking and
running (in comparison to the baseline). In the 1-minute washout
period, the amplitudes of both sides decayed toward those found in
the baseline (into the opposite direction to the changes during the
learning periods). An important fact here is that the movements
were initially disturbed upon walking on symmetrical belt after
adapting to walk, and running after adapting to run, on the
asymmetrically driven treadmill surface. The disturbance in the
Figure 2. Descriptions of adaptation on the asymmetrically driven treadmill and the emergence of the aftereffect with release from
the novel environment in walking in a single subject (showing only the walking periods from Experiment 1). (A) Waveforms of the
antero-posterior ground reaction force under different time points in the experiment. Each waveform represents an ensemble average of five
consecutive stride cycles (from heel contact to the subsequent heel contact) in the respective time points. The solid lines represent the fast-moving
side and the dotted lines are those of the slow side during the adaptation period. (B) Stride-to-stride profile of the peak anterior braking force for
both fast and slow sides. Filled circles and open circles represent the fast and slow sides, respectively. (C) Stride-to-stride profile of the differences in
peak anterior braking force between the fast and slow sides.
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movements were then, followed by gradual decay (restoring
normal movements) in the following 1 minute.
It should be noted that modification in the force occurred in the
posterior (propulsive) component as well. In the representative
waveform (Figure 3 (A)), for example, the posterior force in the fast
side showed a sudden increase with exposure to the asymmetrical
belt but subsequently disappeared at the end of the learning
period. Combined with that in the slow side which showed
a modification into the opposite direction (increase), there was
large asymmetry at the initial state of the washout period. The
asymmetry, however, was prominent only in running and not in
walking. We therefore used anterior braking force (disturbed both
in walking and running) as parameter in the present study.
Given the initial disturbance in the movement patterns
(asymmetry in the braking force) in both movement modes after
adapting in each mode, the primary interest in the present study
was whether the movement pattern acquired through each mode
transferred to (or shared with) the other mode. Figure 4 (A)
compares the extent of asymmetry in walking on identical belt
conditions after adapting to walk (blue line) and after adapting to
run (light blue line) as differences in the peak force between the
sides. In contrast to the large asymmetry after learning to walk, the
emergence of aftereffect was only partial (only reactively present in
the first few seconds). ANOVA comparison revealed a significant
difference between walking with different history (learned to walk
or run) in previously imposed adaptation modes (F1, 22 = 7.285,
P,0.05). On the other hand, the degree of aftereffect during
running with a different adaptation history is described in Figure 4
(B). In comparison to the prominent asymmetry in the running
patterns after adapting to run, individuals who adapted to walk
showed far less asymmetry (F1, 22 = 15.914, P,0.01).
Secondly, to further consider the independence or commonality
of each movement mode in relation to the other, we investigated
the extent of a possible washout in the acquired movement
patterns in one mode by the other (Figures 5 and 6). As partially
described in the results above, the subjects could both walk and
run as normal at the end of the first washout period after adapting
in the opposite modes (shown in the left columns in Figures 5 and
6). The subsequent attempts to run (right column, Figure 5) and
walk (Figure 6) resulted in prominent asymmetry in the movement
patterns, demonstrating little or no washout by the execution of
the opposite mode. That is, the acquired movement patterns
(asymmetry) were maintained independently of the subsequent
trials
in
the
opposite
modes.
ANOVA
showed
significant
differences in the degree of asymmetry in the movement patterns
between the first and second washout periods (F1, 11 = 6.109,
P,0.05, for 1) walking, and 2) running after adapting to run (F1,
11 = 6.914, P,0.05, for 1) run and 2) walk after adapting to walk).
Discussion
The present results strongly confirmed our working hypotheses
and demonstrated that 1) transfer of the novel movement patterns
learned on an asymmetrically driven treadmill from one mode to
another took place only partially for both directions (walk to run
and run to walk), and 2) the learned movement patterns in the
Figure 3. Descriptions of adaptation on the asymmetrically driven treadmill and the emergence of an aftereffect with release from
the novel environment in running in a single subject (only the running periods from Experiment 3 are shown). (A) Waveforms of the
antero-posterior ground reaction force under different time points in the experiment. Each waveform represents an ensemble average of five
consecutive stride cycles (from heel contact to the subsequent heel contact) in the respective time points. The solid lines represent the fast-moving
side and the dotted lines are those of the slow side during the adaptation period. (B) Stride-to-stride profile of the peak anterior braking force for
both fast and slow sides. Filled circles and open circles represent the fast and slow sides, respectively. (C) Stride-to-stride profile of the differences in
peak anterior braking force between the fast and the slow sides.
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respective modes were rarely washed out by the subsequent
execution in the opposite modes, again, for both directions. That
is, the storage of a learned movement patterns were maintained
independently of the opposite mode. Combined, these results
demonstrated only partially overlapped elements between these
two movement modes and thus support the notion of mostly
independent functional networks within the CNS for the respective
locomotive modes. Walking and running, therefore, reflect not
only functions of different speeds of locomotion, but are different
forms from the perspective of neural control mechanisms.
The notion of task-specific or context-specific neural mechan-
isms has been well established by using simple reaching move-
ments in the upper extremities [9,10]. Locomotive movements
that are more complex and autonomic have also been found as
under the specificity, such as the direction (forward-backward)
[11], the limb (right-left) [11], and the speed of walking [12].
Limitations in the transfer or washout in newly acquired
movement patterns under certain physical constraints in one
movement tasks to or by another have been accepted as indirect
evidence demonstrating the specificity [9–12]. By adopting the
well-established experimental paradigms in the earlier studies, the
present
study
is
the
first
to
address
the
mode-specificity,
comprising an important aspect of locomotion. Because of the
well-known spontaneous behavior to transit into the opposite
mode (walk-run or run-walk transition) in accordance with
changing speed [2,6–8], walking and running may only be
considered as a function of demands for different speeds.
The use of split-treadmill walking to modify gait symmetry has
been studied extensively in the last decade [11,12,6]. After walking
on an asymmetrically-driven treadmill for a certain period of time,
the movement pattern after release from the novel environment
resulted in prominent asymmetry [11,12,16]. The current study,
for the first time, demonstrated that movement patterns in running
also could be modified as in the earlier studies focusing on walking.
Detailed explanations on how the gait patterns could be adapted
with exposure to the asymmetrically driven treadmill and resulted
in the subsequent aftereffect have been provided previously both
behaviorally and mathematically on the basis of locomotion in
decerebrate cat [18].
In the present study, the modification in the gait patterns was
most evident in the anterior braking component of the ground
reaction force both in walking and running and we therefore
focused on this parameter (detailed description in the Methods). As
subjects adapted to walk or run comfortably on the asymmetrically
driven treadmill, the patterns of modification in the anterior
braking force showed gradual increment in the fast side and
decrement in the slow side, both including brief and more rapid
changes in the early phases of exposure. As a consequence, with
return to the symmetrical belt in the washout period, there was
initially an overshoot in the force in the fast side and an
undershoot for the slow side, both followed by gradual decay into
the opposite direction to those during the adaptation periods
(towards baseline). Combined with results in a previous study in
which novel motor pattern could be stored intralimb and
independently for each leg [11], these phenomena occurring for
the each limb may reflect the well-established notion of motor
adaptation or learning where motor output is recalibrated to meet
new task demands [19]. It is reasonable to consider that the
asymmetry in the anterior braking force took place based on the
recalibration of motor output in each leg under different velocity
on an asymmetrically driven treadmill.
The motor output acquired through the above mentioned
recalibration processes, however, were only partially shared across
the movement modes. Given the results, with the possibility of
specificity in the neural mechanisms underlying walking and
running, the discussion will now focus on the possible neural
mechanisms comprising the different modes. Based on the results
of animal studies and of humans, the neural mechanisms
underlying the present results could be attributed to possible
contribution of supraspinal structures in the brain and the
Figure 4. Degree of transfer in the acquired movement pattern across walking and running, shown as differences in the peak
braking force between the sides. The extent of asymmetry in (A) walking after adaptation to walk (first washout period in Experiment 1, darker
line) and after adaptation to run (first washout period in Experiment 4, lighter line), and (B) running after adaptation to run (first washout period in
Experiment 3, darker line) and after adaptation to run (first washout period in Experiment 2, lighter line). Data are normalized to the mean of those
during the baseline on a subject-to-subject basis and are presented as the mean (thick line) and the standard errors of the mean (dotted lines).
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specificity in the locomotor center in the spinal cord, known as the
central pattern generator (CPG).
First, in the emergence of the adaptive phenomena, the
cerebellum is considered to play a significant role by recalibrating
motor output that satisfies the task or environmental demand [20].
Given its function, any aspect of an aftereffect following adaptation
is abolished in humans [17] and in cats [21] with cerebellar
lesions. Morton et al. (2006) [17] reported that a predictive
feedforward motor adaptation in splitbelt treadmill walking that is
demonstrated to occur in healthy subjects [11,12,16] does not in
patients with cerebellar damage. More direct evidence showed
that plasticity of synaptic transmission efficacy in the cerebellum
that was modified by concentration of nitric oxide (NO) played
a significant role in locomotive adaptation in decerebrate cat [21].
Interestingly, regarding movement specificity, various aspects of
limb movement such as direction, velocity, acceleration and force
have been demonstrated to be represented in the cerebellum, as
shown by discharge rate in single unit recording in the cerebellum
[22]. In the present study, since the subjects performed both
walking and running under identical belt speed, in which the limb
movements do not simply depend on locomotion speed but are
demonstrated to differ across the modes [3], it is possible that there
were different representation for each locomotive mode.
Along with the cerebellar function, the contribution of the
descending neural drive from the supraspinal centers, especially
those from the mesencephalic locomotor region (MLR) in the
brainstem, provides an additional explanation for the mode-
specificity. For example, in decerebrate salamander, electrical
microstimulation at a particular site in the MLR resulted in
a phase-dependent electromyographic (EMG) burst and conse-
Figure 5. Degree of washout in the stored motor pattern in running by walking (first and second washout periods shown
consecutively from Experiment 4). The asymmetrical movement pattern was evident with the initiation of running (red lines) despite
a symmetrical walking pattern at the end of the first washout period in walking (blue lines), an indication of only partial washout (also described in
the schematic figure). Data are presented as means (thick lines) and their standard errors of the mean (dotted lines).
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quently locomotor-like movements of the body [23]. In the
emergence of these behaviors, two different locomotor modes
(stepping and swimming) were exhibited with different current
intensities [23]. Or, more classically, an increase in stimulus
intensity to the mid-brain in decerebrate cats walking on
a treadmill caused them to gallop [24]. From these results, the
intensities in the descending drive may significantly affect the
decision of different locomotive modes. In the current study,
although speculative, the gait pattern upon the initiation of
walking after adapting to run was reactively disturbed (the
prominent asymmetry in the first few seconds, shown by the light
blue line in Figure 4). This reaction may reflect the component of
running. That is, to accelerate the center of body mass upon
acceleration of the treadmill by increasing the descending drive
from the locomotor centers. Consequently, this could result in the
partial emergence of the asymmetrical movement pattern pre-
viously acquired in running.
Regarding the specificity in the locomotor center in the spinal
cord, on the other hand, it was recently demonstrated that specific
sets of spinal interneurons are activated depending on locomotion
(swimming) frequency in larval zebrafish [14]. Locomotion
behavior in larval zebrafish was previously characterized as
having two different modes [25]. One is the mode used to move
routinely in water with lower movement frequencies and small
yaw amplitudes, while the other is the escape movement with
higher frequencies with larger yaws [25]. On the execution of
these locomotor behaviors by zebrafish, McLean et al. (2008) [14]
showed that, in contrast to motoneurons that are additionally
recruited with increasing swimming frequencies following classic
size principle, the activities in some sets of interneurons evident
Figure 6. Degree of washout in the stored motor pattern in walking by running (first and second washout periods shown
consecutively from Experiment 2). The asymmetrical movement pattern was evident with the initiation of walking (blue lines) despite the
symmetrical walking pattern at the end of the first washout period in running (red lines), an indication of only partial washout (also described in the
schematic figure). Data are presented as means (thick lines) and their standard errors of the mean (dotted lines).
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under lower swimming frequency were inhibited during swimming
at higher frequencies [14]. In other animal models, such as in
a fictive scratching movement in the turtle hindlimb, it was found
that different populations of propriospinal neurons were identified
with respect to two different modes of scratching movements [13].
Based on these previous results in animal models, it is speculated
that the specific structures to be selected in the spinal cord
depending on the modes might explain the underlying differences
in the neural mechanisms between walking and running in
humans.
Regarding adaptation as observed in the present study and in
previous studies [11 12,16], the spinal cord itself is known to be
capable
of
adapting
locomotor
patterns,
as
predominantly
demonstrated in the stepping movement of human infants [26]
or in cats that underwent complete spinal cord transection [27].
The relationship between mode specificity and adaptation remains
unclear. It is however, reasonable to consider that the acquisition
of the novel movement patterns took place in particular sites in the
spinal cord or in combination with the higher structures
depending on the mode, at least before motoneuron, which is
the final common pathway to muscles. The acquired movement
patterns were therefore only partially transferred to the opposite
modes, which have different responsible sites and were rarely
washed out by the execution of the opposite ones.
In summary, the two major modes of human locomotion,
walking and running, are not only functions of different speed but
have fundamentally different neural control mechanisms. The
present results provide extremely important implications for the
construction of training regimens in locomotive movements in
both
athletic
training
and
rehabilitation
processes.
Further
considerations should be made among other locomotive tasks or
those under different physical constraints.
Acknowledgments
The authors thank Dr. Bimal Lakhani for editing the English in the
manuscript.
Author Contributions
Conceived and designed the experiments: T. Ogawa NK T. Ogata KN.
Performed the experiments: T. Ogawa. Analyzed the data: T. Ogawa.
Contributed reagents/materials/analysis tools: T. Ogawa NK. Wrote the
paper: T. Ogawa NK T. Ogata KN.
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Neural Control of Human Walking and Running
PLOS ONE | www.plosone.org
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September 2012 | Volume 7 | Issue 9 | e46349

Limited transfer of newly acquired movement patterns across walking and running in humans.
Ogawa, Tetsuya,Kawashima, Noritaka,Ogata, Toru,Nakazawa, Kimitaka