Abstract:1. Forward reaching movements made during body rotation generate tangential Coriolis forces that are proportional to the cross product of the angular velocity of rotation and the linear velocity of the arm. Coriolis forces are inertial forces that do not involve mechanical contact. Virtually no constant centrifugal forces will be present in the background when motion of the arm generates transient Coriolis forces if the radius of body rotation is small. 2. We measured the trajectories of arm movements made in … Show more
“…The idea that movement trajectory and final position are differentially controlled is also consistent with studies that have examined adaptation to novel forces (DiZio & Lackner, 1995;Lackner & DiZio, 1994) and visuomotor rotations (Sainburg & Wang, 2002;Wang & Sainburg, 2003. In the studies by Lackner and DiZio (DiZio & Lackner, 1995;Lackner & DiZio, 1994), participants reached to a target when adapting to Coriolis force fields, without any visual feedback.…”
Section: Differential Control Of Trajectory and Positionsupporting
confidence: 66%
“…In the studies by Lackner and DiZio (DiZio & Lackner, 1995;Lackner & DiZio, 1994), participants reached to a target when adapting to Coriolis force fields, without any visual feedback. When participants first experienced these forces, their handpaths were curved and inaccurate.…”
Section: Differential Control Of Trajectory and Positionmentioning
Previous research on single joint movements has lead to the development of models of control that propose that movement speed and distance are controlled through an initial pulsatile signal that can be modified in both amplitude and duration. However, the manner in which the amplitude and duration are modulated during the control of movement speed and distance remains controversial. We now report two studies that were designed to test and refine the pulse-step model of movement control. In our first study, participants move at a series of speeds to a single spatial target. In this task, acceleration duration (pulse-width) varied substantially across targets, and was negatively correlated with peak acceleration (pulse-height). In a second experiment, we removed the spatial target, but required movements at three speeds similar to those used in the first study. In this task, acceleration amplitude varied extensively across the speed targets, while acceleration duration remained constant across the three speeds. Taken together, our current findings demonstrate that pulse-width measures can be modulated independently from pulse-height measures, and that a positive correlation between such measures is not obligatory, even when sampled across a range of movement speeds. In addition, our findings suggest that pulse-height modulation plays a primary role in controlling movement speed and specifying target distance, whereas pulse-width mechanisms are employed to correct errors in pulse-height control, as required to achieve spatial precision in final limb position.
“…The idea that movement trajectory and final position are differentially controlled is also consistent with studies that have examined adaptation to novel forces (DiZio & Lackner, 1995;Lackner & DiZio, 1994) and visuomotor rotations (Sainburg & Wang, 2002;Wang & Sainburg, 2003. In the studies by Lackner and DiZio (DiZio & Lackner, 1995;Lackner & DiZio, 1994), participants reached to a target when adapting to Coriolis force fields, without any visual feedback.…”
Section: Differential Control Of Trajectory and Positionsupporting
confidence: 66%
“…In the studies by Lackner and DiZio (DiZio & Lackner, 1995;Lackner & DiZio, 1994), participants reached to a target when adapting to Coriolis force fields, without any visual feedback. When participants first experienced these forces, their handpaths were curved and inaccurate.…”
Section: Differential Control Of Trajectory and Positionmentioning
Previous research on single joint movements has lead to the development of models of control that propose that movement speed and distance are controlled through an initial pulsatile signal that can be modified in both amplitude and duration. However, the manner in which the amplitude and duration are modulated during the control of movement speed and distance remains controversial. We now report two studies that were designed to test and refine the pulse-step model of movement control. In our first study, participants move at a series of speeds to a single spatial target. In this task, acceleration duration (pulse-width) varied substantially across targets, and was negatively correlated with peak acceleration (pulse-height). In a second experiment, we removed the spatial target, but required movements at three speeds similar to those used in the first study. In this task, acceleration amplitude varied extensively across the speed targets, while acceleration duration remained constant across the three speeds. Taken together, our current findings demonstrate that pulse-width measures can be modulated independently from pulse-height measures, and that a positive correlation between such measures is not obligatory, even when sampled across a range of movement speeds. In addition, our findings suggest that pulse-height modulation plays a primary role in controlling movement speed and specifying target distance, whereas pulse-width mechanisms are employed to correct errors in pulse-height control, as required to achieve spatial precision in final limb position.
“…The cause of the discrepancy between these results and those of Lackner & Dizio (1994) has yet to be determined.…”
Section: The Equilibrium-point Hypothesismentioning
confidence: 79%
“…Another challenge to the equilibrium-point hypothesis comes from the work of Lackner & Dizio (1994) who asked subjects to execute reaching hand movements while sitting at the centre of a slowly rotating room. Because of this rotation, a Coriolis force proportional to the speed of the hand p erturbs the subject's arm.…”
Section: The Equilibrium-point Hypothesismentioning
In this paper we discuss a new perspective on how the central nervous system (CNS) represents and solves some of the most fundamental computational problems of motor control. In particular, we consider the task of transforming a planned limb movement into an adequate set of motor commands. To carry out this task the CNS must solve a complex inverse dynamic problem. This problem involves the transformation from a desired motion to the forces that are needed to drive the limb. The inverse dynamic problem is a hard computational challenge because of the need to coordinate multiple limb segments and because of the continuous changes in the mechanical properties of the limbs and of the environment with which they come in contact. A number of studies of motor learning have provided support for the idea that the CNS creates, updates and exploits internal representations of limb dynamics in order to deal with the complexity of inverse dynamics. Here we discuss how such internal representations are likely to be built by combining the modular primitives in the spinal cord as well as other building blocks found in higher brain structures. Experimental studies on spinalized frogs and rats have led to the conclusion that the premotor circuits within the spinal cord are organized into a set of discrete modules. Each module, when activated, induces a speci¢c force ¢eld and the simultaneous activation of multiple modules leads to the vectorial combination of the corresponding ¢elds. We regard these force ¢elds as computational primitives that are used by the CNS for generating a rich grammar of motor behaviours.
“…The form of these movements is competently described as though they were chosen to be maximally smooth [44] in visually relevant coordinates: the path of the hand is straight and the speed profile has a single peak. Exposure to mechanical perturbations (such as motion-dependent force fields) that perturb this kinematic pattern evokes a spontaneous adaptation that restores the original pattern [45][46]. Conversely, exposure to visual displays that distort the appearance of the motion also evokes adaptation, again restoring the original kinematic pattern, even though that may require substantially different patterns of actual limb motion and muscle force [47][48].…”
Abstract-Robotics and related technologies have begun to realize their promise to improve the delivery of rehabilitation therapy. However, the mechanism by which they enhance recovery remains unclear. Ultimately, recovery depends on biology, yet the details of the recovery process remain largely unknown; a deeper understanding is important to accelerate refinements of robotic therapy or suggest new approaches. Fortunately, robots provide an excellent instrument platform from which to study recovery at the behavioral level. This article reviews some initial insights about the process of upper-limb behavioral recovery that have emerged from our work. Evidence to date suggests that the form of therapy may be more important than its intensity: muscle strengthening offers no advantage over movement training. Passive movement is insufficient; active participation is required. Progressive training based on measures of movement coordination yields substantially improved outcomes. Together these results indicate that movement coordination rather than muscle activation may be the most appropriate focus for robotic therapy.
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