How Position, Velocity, and Temporal Information Combine in the Prospective Control of Catching: Data and Model

2005 ◽  
Vol 17 (4) ◽  
pp. 668-686 ◽  
Author(s):  
Joost C. Dessing ◽  
C. (Lieke) E. Peper ◽  
Daniel Bullock ◽  
Peter J. Beek

The cerebral cortex contains circuitry for continuously computing properties of the environment and one's body, as well as relations among those properties. The success of complex perceptuomotor performances requires integrated, simultaneous use of such relational information. Ball catching is a good example as it involves reaching and grasping of visually pursued objects that move relative to the catcher. Although integrated neural control of catching has received sparse attention in the neuroscience literature, behavioral observations have led to the identification of control principles that may be embodied in the involved neural circuits. Here, we report a catching experiment that refines those principles via a novel manipulation. Visual field motion was used to perturb velocity information about balls traveling on various trajectories relative to a seated catcher, with various initial hand positions. The experiment produced evidence for a continuous, prospective catching strategy, in which hand movements are planned based on gaze-centered ball velocity and ball position information. Such a strategy was implemented in a new neural model, which suggests how position, velocity, and temporal information streams combine to shape catching movements. The model accurately reproduces the main and interaction effects found in the behavioral experiment and provides an interpretation of recently observed target motion-related activity in the motor cortex during interceptive reaching by monkeys. It functionally interprets a broad range of neurobiological and behavioral data, and thus contributes to a unified theory of the neural control of reaching to stationary and moving targets.

2014 ◽  
Vol 149 ◽  
pp. 24-31 ◽  
Author(s):  
Justin M. Fine ◽  
Kimberly L. Ward ◽  
Eric L. Amazeen

Author(s):  
Rudy Cepeda-Gomez ◽  
Nejat Olgac

In this study we consider the consensus problem for a group of second order agents interacting under a fixed, undirected communication topology. Communication lines are affected by two rationally independent delays. The first delay is assumed to be in the position information channels whereas the second one is in the velocity information exchange. The delays are assumed to be uniform throughout the entire network. We first reduce the complexity of the problem, by performing a state transformation that allows the decomposition of the characteristic equation of the system into a set of second order factors. The stability of the resulting subsystems is analyzed exactly and exhaustively in the domain of the time delays using the Cluster Treatment of Characteristic Roots (CTCR) paradigm. CTCR is a recent method which declares the stability features of the system for any composition of the time delays. Example cases are provided to verify the analytical conclusions.


Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1274 ◽  
Author(s):  
Alma Y. Alanis ◽  
Jorge D. Rios ◽  
Javier Gomez-Avila ◽  
Pavel Zuniga ◽  
Francisco Jurado

This work introduces a neural-feedback control scheme for discrete-time quantized nonlinear systems with time delay. Traditionally, a feedback controller is designed under ideal assumptions that are unrealistic for real-work problems. Among these assumptions, they consider a perfect communication channel for controller inputs and outputs; such a perfect channel does not consider delays, or noise introduced by the sensors and actuators even if such undesired phenomena are well-known sources of bad performance in the systems. Moreover, traditional controllers are also designed based on an ideal plant model without considering uncertainties, disturbances, sensors, actuators, and other unmodeled dynamics, which for real-life applications are effects that are constantly present and should be considered. Furthermore, control system design implemented with digital processors implies sampling and holding processes that can affect the performance; considering and compensating quantization effects of measured signals is a problem that has attracted the attention of control system researchers. In this paper, a neural controller is proposed to overcome the problems mentioned above. This controller is designed based on a neural model using an inverse optimal approach. The neural model is obtained from available measurements of the state variables and system outputs; therefore, uncertainties, disturbances, and unmodeled dynamics can be implicitly considered from the available measurements. This paper shows the performance and effectiveness of the proposed controller presenting real-time results obtained on a linear induction motor prototype. Also, this work includes stability proof for the whole scheme using the Lyapunov approach.


Author(s):  
Hossein Rastgoftar ◽  
Suhada Jayasuriya

The effect of time delays on the stability of a recently proposed continuum approach for controlling a multi agent system (MAS) evolving in n-D under a special local inter-agent communication protocol is considered. There a homogenous map determined by n+1 leaders is learned by the follower agents each communicating with n+1 adjacent agents. In this work both position and velocity information of adjacent agents are used for local control of follower agents whereas in previous work [1, 2] only position information of adjacent agents was used. Stability of the proposed method under a time delay h is studied using the cluster treatment of characteristic roots (CTCR) [3]. It is shown that the stability of MAS evolution can be preserved when (i) the velocity of any follower agent is updated using both position and velocity of its adjacent agents at time (t-h); and (ii) the communication matrix has real eigenvalues. In addition, it is shown that when there is no communication delay, deviations from a selected homogenous map during transients may be minimized by updating only the position of a follower using both position and velocity of its adjacent agents.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251371
Author(s):  
Woong Choi ◽  
Naoki Yanagihara ◽  
Liang Li ◽  
Jaehyo Kim ◽  
Jongho Lee

The analysis of visually guided tracking movements is important to the understanding of imitation exercises and movements carried out using the human visuomotor control system. In this study, we analyzed the characteristics of visuomotor control in the intermittent performance of circular tracking movements by applying a system that can differentiate between the conditions of invisible and visible orbits and visible and invisible target phases implemented in a 3D VR space. By applying visuomotor control based on velocity control, our study participants were able to track objects with visible orbits with a precision of approximately 1.25 times greater than they could track objects with invisible orbits. We confirmed that position information is an important parameter related to intermittent motion at low speeds (below 0.5 Hz) and that tracked target velocity information could be obtained more precisely than position information at speeds above 0.5 Hz. Our results revealed that the feedforward (FF) control corresponding to velocity was delayed under the visible-orbit condition at speeds over 0.5 Hz, suggesting that, in carrying out imitation exercises and movements, the use of visually presented 3D guides can interfere with exercise learning and, therefore, that the effects of their use should be carefully considered.


2009 ◽  
Vol 102 (1) ◽  
pp. 490-495 ◽  
Author(s):  
Femke Maij ◽  
Eli Brenner ◽  
Jeroen B. J. Smeets

To localize objects relative to ourselves, we need to combine various sensory and motor signals. When these signals change abruptly, as information about eye orientation does during saccades, small differences in latency between the signals could introduce localization errors. We examine whether independent temporal information can influence such errors. We asked participants to follow a randomly jumping dot with their eyes and to point at flashes that occurred near the time they made saccades. Such flashes are mislocalized. We presented a tone at different times relative to the flash. We found that the flash was mislocalized as if it had occurred closer in time to the tone. This demonstrates that temporal information is taken into consideration when combining sensory information streams for localization.


Author(s):  
Atefeh Einafshar ◽  
Farrokh Sassani

An adaptable control system within and on-board a network of interacting satellites is an important module which is desired for unmanned space vehicles. However, such a control system is not easy to develop since it is the core of the network’s operation and all the earth-linked operational information is reviewed and analyzed through it. Due to multipurpose missions of satellites, several decisions are made simultaneously about necessary changes to the satellite’s operational parameters (i.e., orbit, inclination, etc.). In this paper, a neural network model-based control scheme is developed for a network of interacting satellites. The proposed neural control scheme refers to a methodology in which the controller is assumed as a neural network and the dynamical model of the system is identified through the training stages of the neural model. The simulation results show that the neural control method can be effectively applied in monitoring and controlling the satellite networks, without the necessity of determining the mathematical model of the system.


2010 ◽  
Vol 3 (4) ◽  
Author(s):  
Patricia M. Cisarik ◽  
Sanjeev Kasthurirangan ◽  
Frank E. Visco Jr. ◽  
Harold E. Bedell ◽  
Scott B. Stevenson ◽  
...  

Experiments with the Rashbass ‘step-ramp’ paradigm have revealed that the initial catchup saccade that occurs near pursuit onset uses target velocity as well as position information in its programming. Information about both position and motion also influences smooth pursuit. To investigate the timing of velocity sampling near the initiation of saccades and smooth pursuit, we analyzed the eye movements made in nine ‘step-ramp’ conditions, produced by combining –2, 0 and +2 deg steps with –8, 0 and +8 deg/s ramps. Each trial had either no temporal gap or a 50-ms gap during which the laser target was extinguished, beginning 25, 50, 75 or 100 ms after the step. Six subjects repeated each of the resulting 45 conditions 25 times. With no temporal gap, saccades were larger in the step-ramp-away’ than the ‘step-only’ condition, confirming that saccade programming incorporates ramp velocity information. A temporal gap had no effect on the accuracy of saccades on ‘step-only’ trials, but often caused undershoots in ‘step-ramp’ trials. A 50-ms gap within the first 100 ms also increased the latency of the initial saccade. Although initial pursuit velocity was unaffected by a temporal gap, a gap that started at 25 ms reliably delayed pursuit onset for ramp motion of the target toward the fovea. Later gaps had a minimal effect on initial pursuit latency. The similar timing of the temporal gaps in target motion information that affect the initiation of saccades and pursuit provides further behavioral evidence that the two types of eye movements share pre-motor neural mechanisms.


1998 ◽  
Vol 48 (3) ◽  
pp. 375-376
Author(s):  
Robert A. Steiner
Keyword(s):  

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