1,721,013 research outputs found
Are we ready to move beyond the reductionist approach of classical synergy control?: Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al
No full textLacquaniti F, Ivanenko YP, Zago M. Are we ready to move beyond the reductionist approach of classical synergy control?: Comment on" Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al. Physics of Life Reviews. 2016;17:38
Control of foot trajectory in walking toddlers: adaptation to load changes
No full textOn earth, body weight is an inherent constraint, and accordingly, load-regulating mechanisms play an important role in terrestrial locomotion. How do toddlers deal with the effects of their full body weight when faced with the task of independent upright locomotion for the first time? Here we studied the effect of load variation on walking in 12 toddlers during their first unsupported steps, 15 older children (1.3-5 yr), and 10 adults. To simulate various levels of body weight, an experimenter held the trunk of the subject with both hands and supplied an approximately constant vertical force during stepping on a force platform. During unsupported stepping, the shape of the foot path in toddlers (typically single-peak toe trajectory) was different from that of adults and older children (double-peak trajectory). In contrast to adults and older children, who showed only limited changes in kinematic coordination, the "reduced-gravity" condition considerably affected the shape of the foot path in toddlers: they tended to make a high lift and forward foot overshoot at the end of swing. In addition, stepping at high levels of body unloading was characterized by a significant change in the initial direction of foot motion during early swing. Intermediate walkers (1.5-5 mo after walking onset) showed only partial improvement in foot trajectory characteristics. The results suggest that, at the onset of walking, changes in vertical body loads are not compensated accurately by the kinematic controllers; compensation necessitates a few months of independent walking experience
Tonic and Rhythmic Spinal Activity Underlying Locomotion
No full textIvanenko YP, Gurfinkel VS, Selionov V, et al. Tonic and Rhythmic Spinal Activity Underlying Locomotion. Current Pharmaceutical Design. 2017;23(12):1753-1763
Fast adaptation of the internal model of gravity for manual interceptions: evidence for event-dependent learning
No full textast adaptation of the
internal model of gravity for manual interceptions: evidence for
event-dependent learning. J Neurophysiol 93: 1055–1068, 2005. First
published September 29, 2004; doi:10.1152/jn.00833.2004. We studied
how subjects learn to deal with two conflicting sensory environments
as a function of the probability of each environment and the
temporal distance between repeated events. Subjects were asked to
intercept a visual target moving downward on a screen with randomized
laws of motion. We compared five protocols that differed in the
probability of constant speed (0g) targets and accelerated (1g) targets.
Probability ranged from 9 to 100%, and the time interval between
consecutive repetitions of the same target ranged from about 1 to 20
min. We found that subjects systematically timed their responses
consistent with the assumption of gravity effects, for both 1 and 0g
trials. With training, subjects rapidly adapted to 0g targets by shifting
the time of motor activation. Surprisingly, the adaptation rate was
independent of both the probability of 0g targets and their temporal
distance. Very few 0g trials sporadically interspersed as catch trials
during immersive practice with 1g trials were sufficient for learning
and consolidation in long-term memory, as verified by retesting after
24 h. We argue that the memory store for adapted states of the internal
gravity model is triggered by individual events and can be sustained
for prolonged periods of time separating sporadic repetitions. This
form of event-related learning could depend on multiple-stage memory,
with exponential rise and decay in the initial stages followed by
a sample-and-hold module
Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions
No full textnternal models of
target motion: expected dynamics overrides measured kinematics in
timing manual interceptions. J Neurophysiol 91: 1620–1634, 2004.
First published November 19, 2003; 10.1152/jn.00862.2003. Prevailing
views on how we time the interception of a moving object assume
that the visual inputs are informationally sufficient to estimate the
time-to-contact from the object’s kinematics. Here we present evidence
in favor of a different view: the brain makes the best estimate
about target motion based on measured kinematics and an a priori
guess about the causes of motion. According to this theory, a predictive
model is used to extrapolate time-to-contact from expected dynamics
(kinetics). We projected a virtual target moving vertically
downward on a wide screen with different randomized laws of motion.
In the first series of experiments, subjects were asked to intercept
this target by punching a real ball that fell hidden behind the screen
and arrived in synchrony with the visual target. Subjects systematically
timed their motor responses consistent with the assumption of
gravity effects on an object’s mass, even when the visual target did not
accelerate. With training, the gravity model was not switched off but
adapted to nonaccelerating targets by shifting the time of motor
activation. In the second series of experiments, there was no real ball
falling behind the screen. Instead the subjects were required to intercept
the visual target by clicking a mousebutton. In this case, subjects
timed their responses consistent with the assumption of uniform
motion in the absence of forces, even when the target actually accelerated.
Overall, the results are in accord with the theory that motor
responses evoked by visual kinematics are modulated by a prior of the
target dynamics. The prior appears surprisingly resistant to modifications
based on performance errors
Modularity in motor control: from muscle synergies to cognitive action representation
No full textd'Avella A, Giese M, Ivanenko YP, Schack T, Flash T. Modularity in motor control: from muscle synergies to cognitive action representation. Frontiers Comp. Neuroscience. 2015;9: 126
Five basic muscle activation patterns account for muscle activity during human locomotion
No full textAn electromyographic (EMG) activity pattern for individual muscles in the gait cycle exhibits a great deal of intersubject, intermuscle and context-dependent variability. Here we examined the issue of common underlying patterns by applying factor analysis to the set of EMG records obtained at different walking speeds and gravitational loads. To this end healthy subjects were asked to walk on a treadmill at speeds of 1, 2,3 and 5 km h(-1) as well as when 35-95% of the body weight was supported using a harness. We recorded from 12-16 ipsilateral leg and trunk muscles using both surface and intramuscular recording and determined the average, normalized EMG of each record for 10-15 consecutive step cycles. We identified five basic underlying factors or component waveforms that can account for about 90% of the total waveform variance across different muscles during normal gait. Furthermore, while activation patterns of individual muscles could vary dramatically with speed and gravitational load, both the limb kinematics and the basic EMG components displayed only limited changes. Thus, we found a systematic phase shift of all five factors with speed in the same direction as the shift in the onset of the swing phase. This tendency for the factors to be timed according to the lift-off event supports the idea that the origin of the gait cycle generation is the propulsion rather than heel strike event. The basic invariance of the factors with walking speed and with body weight unloading implies that a few oscillating circuits drive the active muscles to produce the locomotion kinematics. A flexible and dynamic distribution of these basic components to the muscles may result from various descending and proprioceptive signals that depend on the kinematic and kinetic demands of the movements
Motor control programs and walking
No full textThe question of how the central nervous system coordinates muscle activity is central to an understanding of motor control. The authors argue that motor programs may be considered as a characteristic timing of muscle activations linked to specific kinematic events. In particular, muscle activity occurring during human locomotion can be accounted for by five basic temporal components in a variety of locomotion conditions. Spatiotemporal maps of spinal cord motoneuron activation also show discrete periods of activity. Furthermore, the coordination of locomotion with voluntary tasks is accomplished through a superposition of motor programs or activation timings that are separately associated with each task. As a consequence, the selection of muscle synergies appears to be downstream from the processes that generate activation timings. Copyright © 2006 Sage Publications
Development of independent walking in toddlers
No full textSurprisingly, despite millions of years of bipedal walking evolution, the gravity-related pendulum mechanism of walking does not seem to be implemented at the onset of independent walking, requiring each toddler to develop it. We discuss the precursor of the mature locomotor pattern in infants as an optimal starting point strategy for gait maturation. ©2007The Amercian College of Sports Medicine
Distributed neural networks for controlling human locomotion Lessons from normal and SCI subjects
No full textThe control of human locomotion engages various brain structures and numerous muscles. Even though the hypothetical central pattern generator (CPG) and sensory feedback can sustain the basic locomotor rhythm, the resultant motor output is highly adaptable and context-dependent. Indeed, while the temporal architecture of the locomotor output (basic EMG components) is relatively conserved across subjects and conditions, the spatial architecture (muscle activations) shows considerable non-linear changes with walking speed, level of body unloading or the direction of progression. Even so, leg kinematics are remarkably similar in all cases. Spinal cord injured (SCI) patients may learn new motor patterns with training rather than re-activate normal motor patterns, and such locomotor improvements may not transfer to untrained tasks. Redundancy in the neuromuscular system or malfunctioning of injured 'elements' may often result in motor equivalent compensatory solutions. injured pathways can partially recover while uninjured pathways can augment or modify their activity. As a result, the reconstructed spatiotemporal maps of motor neuron activity in SCI patients might be quite different from those of healthy subjects but they nevertheless achieve nearly normal foot kinematics. Kinematics training may thus provide a more successful rehabilitation than training based on reconstructing normal muscle activation patterns. Taken together, recent data support the idea of plasticity and distributed networks for controlling human locomotion. A new generation of robotic devices takes advantage of this by providing the opportunity for patients to generate and correct limb movements rather than just adapting muscle activation to the fixed kinematic template imposed by a gait orthosis. (c) 2008 Elsevier Inc. All rights reserved
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