Biomedical subjects

David C Knill

Publications and source records attributed to David C Knill.

10 recordsLinked to original sources

PubMed2005

Humans use continuous visual feedback from the hand to control both the direction and distance of pointing movements.

Vision of the hand during reaching provides dynamic feedback that can be used to control movement. We investigated the relative contributions of feedback about the direction and distance of the hand relative to a target. Subjects made pointing movements in a 3-D virtual environment, in which a small sphere provided dynamic visual feedback about the position of their unseen fingertip. On a subset of trials, the position of the virtual fingertip was smoothly shifted by 2 cm during movement, either (1) in the direction of movement, which would require adjustments to the distance moved, or (2) orthogonal to the direction of movement, which would require adjustments to the direction moved. Despite not noticing the perturbations, subjects adjusted their movements to compensate for both types of visual shifts. Corrective responses to direction perturbations were observed within 117 ms, and response latencies were invariant to movement speed and perturbation onset time. Initial corrections to distance perturbations were smaller and appeared after longer delays of 130-200 ms, and both the speed and magnitude of responses were reduced for early onset perturbations. Simulations of a feedback control model that optimally integrates visual information over time show that the results can be explained by differences in the sensory noise levels in the visual dimensions relevant for direction and distance control.

Adaptation, Physiological↗

PubMed2005

Reaching for visual cues to depth: the brain combines depth cues differently for motor control and perception.

Vision provides a number of cues about the three-dimensional (3D) layout of objects in a scene that could be used for planning and controlling goal-directed behaviors such as pointing, grasping, and placing objects. An emerging consensus from the perceptual work is that the visual brain is a near-optimal Bayesian estimator of object properties, for example, by integrating cues in a way that accounts for differences in their reliability. We measured how the visuomotor system integrates binocular and monocular cues to 3D surface orientation to guide the placement of objects on a slanted surface. Subjects showed qualitatively similar results to those found in perceptual studies--they gave more weight to binocular cues at low slants and more weight to monocular cues like texture at high slants. We compared subjects' performance in the visuomotor task with their performance on matched perceptual tasks that required an observer to estimate the same 3D surface properties needed to control the motor behavior. The relative influence of binocular and monocular cues changed in qualitatively the same way across stimulus conditions in the two types of task; however, subjects gave significantly more weight to binocular cues for controlling hand movements than for making explicit perceptual judgments in these tasks. Thus, the brain changes how it integrates visual cues based not only on the information content of stimuli, but also on the task for which the information is used.

Brain↗

PubMed2005

Integrating visual cues for motor control: a matter of time.

The visual system continuously integrates multiple sensory cues to help plan and control everyday motor tasks. We quantified how subjects integrated monocular cues (contour and texture) and binocular cues (disparity and vergence) about 3D surface orientation throughout an object placement task and found that binocular cues contributed more to online control than planning. A temporal analysis of corrective responses to stimulus perturbations revealed that the visuomotor system processes binocular cues faster than monocular cues. This suggests that binocular cues dominated online control because they were available sooner, thus affecting a larger proportion of the movement. This was consistent with our finding that the relative influence of binocular information was higher for short-duration movements than long-duration movements. A motor control model that optimally integrates cues with different delays accounts for our findings and shows that cue integration for motor control depends in part on the time course of cue processing.

Cues↗

PubMed2004

Visual feedback control of hand movements.

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.

Biomechanical Phenomena↗

PubMed2004

The Bayesian brain: the role of uncertainty in neural coding and computation.

To use sensory information efficiently to make judgments and guide action in the world, the brain must represent and use information about uncertainty in its computations for perception and action. Bayesian methods have proven successful in building computational theories for perception and sensorimotor control, and psychophysics is providing a growing body of evidence that human perceptual computations are "Bayes' optimal". This leads to the "Bayesian coding hypothesis": that the brain represents sensory information probabilistically, in the form of probability distributions. Several computational schemes have recently been proposed for how this might be achieved in populations of neurons. Neurophysiological data on the hypothesis, however, is almost non-existent. A major challenge for neuroscientists is to test these ideas experimentally, and so determine whether and how neurons code information about sensory uncertainty.

Animals↗

PubMed2003

Visuomotor sensitivity to visual information about surface orientation.

We measured human visuomotor sensitivity to visual information about three-dimensional surface orientation by analyzing movements made to place an object on a slanted surface. We applied linear discriminant analysis to the kinematics of subjects' movements to surfaces with differing slants (angle away form the fronto-parallel) to derive visuomotor d's for discriminating surfaces differing in slant by 5 degrees. Subjects' visuomotor sensitivity to information about surface orientation was very high, with discrimination "thresholds" ranging from 2 to 3 degrees. In a first experiment, we found that subjects performed only slightly better using binocular cues alone than monocular texture cues and that they showed only weak evidence for combining the cues when both were available, suggesting that monocular cues can be just as effective in guiding motor behavior in depth as binocular cues. In a second experiment, we measured subjects' perceptual discrimination and visuomotor thresholds in equivalent stimulus conditions to decompose visuomotor sensitivity into perceptual and motor components. Subjects' visuomotor thresholds were found to be slightly greater than their perceptual thresholds for a range of memory delays, from 1 to 3 s. The data were consistent with a model in which perceptual noise increases with increasing delay between stimulus presentation and movement initiation, but motor noise remains constant. This result suggests that visuomotor and perceptual systems rely on the same visual estimates of surface slant for memory delays ranging from 1 to 3 s.

Acceleration↗

PubMed2003

Humans use continuous visual feedback from the hand to control fast reaching movements.

How visual feedback contributes to the on-line control of fast reaching movements is still a matter of considerable debate. Whether feedback is used continuously throughout movements or only in the "slow" end-phases of movements remains an open question. In order to resolve this question, we applied a perturbation technique to measure the influence of visual feedback from the hand at different times during reaching movements. Subjects reached to touch targets in a virtual 3D space, with visual feedback provided by a small virtual sphere that moved with a subject's fingertip. Small random perturbations were applied to the position of the virtual fingertip at two different points in the movement, either at 25% or 50% of the total movement extent. Despite the fact that subjects were unaware of the perturbations, their hand trajectories showed smooth and accurate corrections. Detectable responses were observed within an average of 160 ms after perturbations, and as early as 60% of the distance to the target. Response latencies were constant across different perturbation times and movement speed conditions, suggesting that a fixed sensori-motor delay is the limiting factor. The results provide direct evidence that the human brain uses visual feedback from the hand in a continuous fashion to guide fast reaching movements throughout their extent.

Analysis of Variance↗

PubMed2003

Mixture models and the probabilistic structure of depth cues.

Monocular cues to depth derive their informativeness from a combination of perspective projection and prior constraints on the way scenes in the world are structured. For many cues, the appropriate priors are best described as mixture models, each of which characterizes a different category of objects, surfaces, or scenes. This paper provides a Bayesian analysis of the resulting model selection problem, showing how the mixed structure of priors creates the potential for non-linear, cooperative interactions between cues and how the information provided by a single cue can effectively determine the appropriate constraint to apply to a given image. The analysis also leads to a number of psychophysically testable predictions. We test these predictions by applying the framework to the problem of perceiving planar surface orientation from texture. A number of psychophysical experiments are described that show that the visual system is biased to interpret textures as isotropic, but that when sufficient image data is available, the system effectively turns off the isotropy constraint and interprets texture information using only a homogeneity assumption. Human performance is qualitatively similar to an optimal estimator that assumes a mixed prior on surface textures--some proportion being isotropic and homogeneous and some proportion being anisotropic and homogeneous.

Adult↗

PubMed2003

Do humans optimally integrate stereo and texture information for judgments of surface slant?

An optimal linear system for integrating visual cues to 3D surface geometry weights cues in inverse proportion to their uncertainty. The problem of integrating texture and stereo information for judgments of planar surface slant provides a strong test of optimality in human perception. Since the accuracy of slant from texture judgments changes by an order of magnitude from low to high slants, optimality predicts corresponding changes in cue weights as a function of surface slant. Furthermore, since humans show significant individual differences in their abilities to use both texture and stereo information for judgments of 3D surface geometry, the problem admits the stronger test that individual differences in subjects' thresholds for discriminating slant from the individual cues should predict individual differences in cue weights. We tested both predictions by measuring slant discrimination thresholds and stereo/texture cue weights as a function of surface slant for multiple subjects. The results bear out both predictions of optimality, with the exception of an apparent slight under-weighting of texture information. This may be accounted for by factors specific to the stimuli used to isolate stereo information in the experiments. Taken together, the results are consistent with the hypothesis that humans optimally combine the two cues to surface slant, with cue weights proportional to the subjective reliability of the cues.

Cues↗

PubMed2003

Experience-dependent visual cue recalibration based on discrepancies between visual and haptic percepts.

We studied the hypothesis that observers can recalibrate their visual percepts when visual and haptic (touch) cues are discordant and the haptic information is judged to be reliable. Using a novel visuo-haptic virtual reality environment, we conducted a set of experiments in which subjects interacted with scenes consisting of two fronto-parallel surfaces. Subjects judged the distance between the two surfaces based on two perceptual cues: a visual stereo cue obtained when viewing the scene binocularly and a haptic cue obtained when subjects grasped the two surfaces between their thumb and index fingers. Visual and haptic cues regarding the scene were manipulated independently so that they could either be consistent or inconsistent. Experiment 1 explored the effect of visuo-haptic inconsistencies on depth-from-stereo estimates. Our findings suggest that when stereo and haptic cues are inconsistent, subjects recalibrate their interpretations of the visual stereo cue so that depth-from-stereo percepts are in greater agreement with depth-from-haptic percepts. In Experiment 2 the visuo-haptic discrepancy took a different form when the two surfaces were near the subject than when they were far from the subject. The results indicate that subjects recalibrated their interpretations of the stereo cue in a context-sensitive manner that depended on viewing distance, thereby making them more consistent with depth-from-haptic estimates at all viewing distances. Together these findings suggest that observers' visual and haptic percepts are tightly coupled in the sense that haptic percepts provide a standard to which visual percepts can be recalibrated when the visual percepts are deemed to be erroneous.

Adolescent↗