The discrimination of abrupt changes in speed and direction of visual motion

252

190

We investigated what visual information contributes to on-line control of hand movements. It has been suggested that motion information predominates early in movements but that position information predominates for endpoint control. We used a perturbation method to determine the relative contributions of motion and position information to feedback control. Subjects reached to touch targets in a dynamic virtual environment in which subjects viewed a moving virtual fingertip in place of their own finger. On some trials, we perturbed the virtual fingertip while it moved behind an occluder. Subjects responded to perturbations that selectively altered either motion or position information, indicating that both contribute to feedback control. Responses to perturbations that changed both motion and position information were consistent with superimposed motion-based and position-based control. Results were well fit by a control model that optimally integrates noisy, delayed sensory feedback about both motion and position to estimate hand state.

Section: Methodssupporting

confidence: 89%

Visual Feedback Control of Hand Movements

Saunders¹,

Knill²

2004

252

190

“…Up to speeds of 64°/s (close to the peak velocity measured in our experiments), Weber fractions for speed decrease to a minimum of .08 for viewing durations of 500 ms (Mateeff, Dimitrov et al 2000). These results are consistent across a number of studies and types of stimuli (Orban, Van Calenbergh et al 1985; De Bruyn and Orban 1988).…”

Section: Methodssupporting

confidence: 76%

Flexible, Task-Dependent Use of Sensory Feedback to Control Hand Movements

Knill¹,

Bondada²,

Chhabra³

2011

We tested whether changing accuracy demands for simple pointing movements leads humans to adjust the feedback control laws that map sensory signals from the moving hand to motor commands. Subjects made repeated pointing movements in a virtual environment to touch a button whose shape varied randomly from trial to trial-between squares, rectangles oriented perpendicular to the movement path, and rectangles oriented parallel to the movement path. Subjects performed the task on a horizontal table but saw the target configuration and a virtual rendering of their pointing finger through a mirror mounted between a monitor and the table. On one-third of trials, the position of the virtual finger was perturbed by Ϯ1 cm either in the movement direction or perpendicular to the movement direction when the finger passed behind an occluder. Subjects corrected quickly for the perturbations despite not consciously noticing them; however, they corrected almost twice as much for perturbations aligned with the narrow dimension of a target than for perturbations aligned with the long dimension. These changes in apparent feedback gain appeared in the kinematic trajectories soon after the time of the perturbations, indicating that they reflect differences in the feedback control law used throughout the duration of movements. The results indicate that the brain adjusts its feedback control law for individual movements "on demand" to fit task demands. Simulations of optimal control laws for a two-joint arm show that accuracy demands alone, coupled with signal-dependent noise, lead to qualitatively the same behavior.

“…Psychophysical studies have shown that humans have a Weber fraction for motion discrimination of 0.08 (Mateef et al, 2000). Further, this value is largely invariant to the retinal eccentricity of the motion.…”

Section: Modeling the Motor Systemmentioning

confidence: 99%

Adaptive Allocation of Vision under Competing Task Demands

Sims¹,

Jacobs²,

Knill³

2011

Human behavior in natural tasks consists of an intricately coordinated dance of cognitive, perceptual, and motor activities. While much research has progressed in understanding the nature of cognitive, perceptual, or motor processing in isolation or in highly constrained settings, few studies have sought to examine how these systems are coordinated in the context of executing complex behavior. Previous research has suggested that in the course of visually-guided reaching movements, the eye and hand are yoked, or linked in a nonadaptive manner. In this work we report an experiment that manipulated the demands that a task placed on the motor and visual systems, and then examined in detail the resulting changes in visuomotor coordination. We develop an ideal actor model that predicts the optimal coordination of vision and motor control in our task. On the basis of our model’s predictions, we demonstrate that human performance in our experiment reflects an adaptive response to the varying costs imposed by our experimental manipulations. Our results stand in contrast to previous theories that have assumed a fixed control mechanism for coordinating vision and motor control in reaching behavior.