The development of mathematical tools for describing dynamical systems has made it possible to characterize forms of behavior that could not be characterized before. This represents progress, but the enterprise runs the risk of being nothing more than curve fitting if investigators fail to identify the physical, biological, or psychological mechanisms which are common to systems that follow the same dynamical regime and which are not common to systems that do not follow the same dynamical regime.
David A. Rosenbaum
Esa M. Rantanen and David A. Rosenbaum
There is anecdotal evidence of drift in various reciprocal motor tasks, but as far as is known, no investigations into this phenomenon have been reported. Yet, systematic drift can potentially explain a significant proportion of the total variability in motor output. Three experiments were conducted to ascertain the nature of drift in reciprocal aiming tasks and to develop methods and measures to isolate and quantify drift for analyses. We also evaluated a computational posture-based model of reaching movements with respect to the findings of the experiments. Drift was observed in all three experiments, generally toward the middle of the joint motility range. Simulations based on the model produced drift to the middle of the task movement range rather than middle of the joint movement range. Adding noise to the model could increase its power for simulating the underlying principles of movement control as reflected in performance features such as drift.
Bradley P. Wyble and David A. Rosenbaum
Smeets et al. (2016) suggested that motor adjustments may be quick because they don’t require stimulus detection. We agree that these rapid adjustments probably reflect rapid perceptual processing rather than rapid motor execution, but we question whether the absence of detection is the best way to explain the effect. We suggest that it is unclear what mechanisms would be involved in detection and why detection would be required in some of the cases discussed by Smeets et al. Instead, we suggest that ultra-fast motor adjustments require very little competition among possible stimuli or responses. We suggest that escaping competition rather than avoiding detection may be the cause of the very short reaction times that Smeets et al. identified.
Jonathan Vaughan, David A. Rosenbaum, and Ruud G. J. Meulenbroek
In this article, we review a model of the movement-planning processes that people use for direct reaching, reaching around obstacles, and grasping, and we present observations of subjects' repeated movements of the hand to touch 2 target locations, circumventing an intervening obstacle. The model defines an obstacle as a posture that, if adopted, would intersect with any part of the environment (including the actor himself or herself). The model finds a trajectory that is likely to bring the end-effector to me target by means of a one- or two-stage planning process. Each stage exploits the principles of instance retrieval and instance generation. In the first stage, a goal posture is identified, and the trajectory of a direct transition to that posture is tested for collision. If that direct movement has no collision, the movement to the target is immediately executed in joint space. If. however, the direct movement is foreseen to result in a collision, a second planning stage is invoked. The second planning stage identifies a via posture, movement through which will probably avoid the collision. Movement to and from the via posture is then superimposed on the main movement to the target so that the combined movement reaches the target without colliding with intervening obstacles. We describe the details of instance retrieval and instance generation for each of these planning stages and compare the model's performance with the observed kinematics of direct movements as well as movements around an obstacle. Then we suggest how the model might contribute to the study of movements in people with motor disorders such as spastic hemiparesis.
Ruud C.J. Meulenbroek, David A. Rosenbaum, and Jonathan Vaughan
In this paper we describe how a theory of posture-based motion planning recently applied to human grasping may contribute to the understanding of grasping pathology. The theory is implemented as a computer model rendered as a stick-figure animation capable of generating realistic multi-joint grasping movements. As shown here, the model can also be used to simulate grasping movements whose kinematics resemble those of grasps performed by people with spastic hemiparesis. The simulations demonstrate effects of: (a) reduced ranges of motion of arm joints on the size of the reachable workspace, (b) awkward starting postures on me time course of the hand closing around an object, (c) increased costs of joint rotations on movement time, and (d) addition of noise to biphasic joint rotations on the low-velocity phase of wrist transport.
David A. Rosenbaum, Ruud G.J. Meulenbroek, and Jonathan Vaughan
This paper presents the background, premises, and results of a model of movement planning. The model's central claims are fourfold: (a) A task is defined by a set of prioritized requirements, or what we call a constraint hierarchy; (b) movement planning works first by specifying a goal posture and then by specifying a movement to that goal posture; (c) movements have characteristic forms; and (d) movements can be shaped through simultaneous performance of different movements, even by the same effector. We review the model and then speculate on its implications for clinical concerns, especially spasticity.
David A. Rosenbaum, Ruud J.G. Meulenbroek, Jonathan Vaughan, and Catherine Elsinger
The hypothesis introduced by Smeets and Brenner concerning the perpendicular approach of the thumb and index finger during grasping has heuristic value, but it also has limitations. Among the limitations are the following: (a) the approach parameter is not directly testable and it is unclear how the values of deceleration at contact and movement time are set theoretically; (b) it is questionable that motion of the thumb and index finger are independent; (c) reliance on the minimum-jerk account ignores critiques of that account; and (d) the model begs the question of how the effectors proximal to the index finger and thumb are controlled. We briefly review an alternative model that can handle these challenges.