Sensory-motor integration has frequently been studied using a single-step change in a control variable such as prismatic lens angle and has revealed human visuomotor adaptation to often be partial and inefficient. We propose that the changes occurring in everyday life are better represented as the accumulation of many smaller perturbations contaminated by measurement noise. We have therefore tested human performance to random walk variations in the visual feedback of hand movements during a pointing task. Subjects made discrete targeted pointing movements to a visual target and received terminal feedback via a cursor the position of which was offset from the actual movement endpoint by a random walk element and a random observation element. By applying ideal observer analysis, which for this task compares human performance against that of a Kalman filter, we show that the subjects' performance was highly efficient with Fisher efficiencies reaching 73%. We then used system identification techniques to characterize the control strategy used. A "modified" delta-rule algorithm best modeled the human data, which suggests that they estimated the random walk perturbation of feedback in this task using an exponential weighting of recent errors. The time constant of the exponential weighting of the best-fitting model varied with the rate of random walk drift. Because human efficiency levels were high and did not vary greatly across three levels of observation noise, these results suggest that the algorithm the subjects used exponentially weighted recent errors with a weighting that varied with the level of drift in the task to maintain efficient performance.
The role of proprioception in the control and adaptation of visuomotor relationships is still unclear. We have studied a deafferented subject, IW, and control subjects in a task in which they used single joint elbow extension to move to a visual target, with visual feedback of the terminal position provided by a cursor displayed in the plane of their movements. We report the differences in movement accuracy between the deafferented subject and controls in the normal task and when challenged with a cognitive load, counting backwards. All subjects were less accurate when counting; this was a small effect for the controls (<10% change) but much greater for the deafferented subject (>60% change). We also examined changes in movement kinematics when the instructed amplitude was altered via a changed gain between final arm position and presentation of the feedback cursor. The deafferented subject maintained temporal movement parameters stable and altered amplitude by scaling force (i.e. changed peak velocity), whereas the controls scaled both movement velocity and duration. Finally, we compared the subjects' adaptation of movement amplitude after a period of exposure to the changed visuomotor gain. The deafferented subject was able to adapt, but his adaptation was severely impaired by the counting task. These results suggest that proprioception is not an absolute requirement for adaptation to occur. Instead, proprioception has a more subtle role to play in the adjustment to visuomotor perturbations. It has an important role in the control of reaching movements, while in the absence of proprioception, attention appears necessary to monitor movements.
It is not yet certain which sources of information are most important in judging the weight of a held object. In order to study this question further, a "deafferented" man and five controls flexed their wrist to lift a container weighing 1,000 g. Direct vision of the arm and weight was denied; the container's vertical position was displayed to the subjects on an oscilloscope at the start of each trial and, then, in most experimental conditions, this display was removed. The weight was then either gradually increased or decreased over 20 s or left unchanged, on a pseudorandom basis. A verbal judgement of its change was required at the end of each trial, lasting 20 or 40 s. Under these conditions, the "deafferented" subject was unable to correctly judge the weight changes (38% accuracy, n.s. chi2, compared with 77% in control subjects), and even the control subjects, when exposed to muscle vibration, made many errors (54% accuracy). However, in many trials, including those in which the weight was unchanged, the vertical height of the container was not held constant by the subjects, but drifted up or down (mean absolute drift: approximately 2 cm). Hence, the change in muscular activation or stiffness could be estimated by the observers in the majority of trials. This allowed the verbal judgements of both the "deafferented" man and of control subjects undergoing muscle vibration to be correlated with the muscle activation produced, independent of the actual weight being tested. Post-hoc predictions of controls' responses during vibration, based on the direction of the change in muscle activity which these drifts in position implied, were 77% and 66% accurate for +/-750 g and +/-375 g tasks and 73% accurate for forearm-vibration trials (P<0.0001, chi2). Predictions of the "deafferented" subject's responses were 64% accurate (P=0.0002, chi2), even though his own responses were at a chance level with respect to the actual weight change. The judgements made by these subjects might have been based upon a peripheral sensory input, as small afferent fibres are still present in the "deafferented" man and vibration only partly blocked sensory function in the control subjects. Care was taken to minimise all other possible cues to the weight changes, e.g. vestibular, thermal, pressure or pain cues. However, peripheral inputs may not be the only signals used in the subjects' perceptual judgements. They might, instead, be based upon a centrally originating, but illusory changing sense of body position or, possibly, a changing sense of effort. In both cases, a perceived discordance between voluntary muscle activation and body image could underlie the subjects' responses. Our data do not yet allow us to distinguish between these alternative peripheral and central hypotheses, but do highlight the need to include perceptions of body position and motion into judgements of force control.
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