Learning and decay of prediction in object manipulation.

Anticipating the consequences of our own actions is a fundamental component of normal sensorimotor control and is seen, for example, during the manipulation of objects. When one hand pulls on an object held in the other hand, there is an anticipatory increase in grip force in the restraining hand that prevents the object from slipping. This anticipation is thought to rely on a forward internal model of the manipulated object and motor system, enabling the prediction of the consequences of our motor commands. Here we investigate the development of such a predictive response. Each hand held an object that was attached to its own torque motor. On each trial the subject was required to pull on the object held in the left hand and to maintain the position of the object held in the right hand. The torque motors were computer controlled so that the objects could be either "linked" so that the forces on the objects were equal and opposite, acting as though they were a single object, or "unlinked," so that they acted as two independent objects. A predictive response in the restraining hand is only necessary when the objects are linked and is unnecessary in the unlinked condition where there is no risk of the object slipping. To examine the learning and decay of predictive responses, we measured the grip force responses during unlinked trials that followed a linked trial. After a single linked trial, anticipatory grip force was quick to develop, but decayed slowly over the following unlinked trials. Varying the time between trials showed that the rate of decay depended on the number of trials since the last linked trial rather than time. Increasing the frequency of linked trials showed an increased level of subsequent grip force modulation, but did not alter the decay rate. When the torque motors simulated a linked object that did not have normal physical properties, prediction was reduced. These results show that the use of predictive responses has a different time course for learning and decay, and the response depends on experience and the physical properties of the objects.

Predictive motor learning of temporal delays.

Anticipatory responses can minimize the disturbances that result from the action of one part of the body on another. Such a predictive response is evident in the anticipatory increase in grip force seen when one hand pulls on an object held in the other hand, thereby preventing the object from slipping. It is postulated that such a response depends on predicting the consequences of the descending motor command, as signaled by efference copy, using an internal model of both one's own body and the object. Here we investigate how the internal model learns the temporal consequences of the motor command. We employed two robots to simulate a virtual object held in one hand and acted on by the other. Delays were introduced between the action of one hand on the object and the effects of this action on the other hand. An initial reactive grip force response to the delayed load decayed with the development of appropriate anticipatory grip force modulation. However, no predictive modulation was seen when the object's movement was not generated by the subject, even when the motion was cued by a tone. These results suggest that, when an internal model learns new temporal relationships between actions and their consequences, this learning involves generating a novel response rather than adapting the original predictive response.

The effect of visuomotor displacements on arm movement paths.

The gently curved paths evident in point-to-point arm movements have been attributed to both an imperfect execution of a planned straight-hand path or as an emergent property of a control strategy in which an intrinsic cost, dependent on arm dynamics, is minimised. We used a virtual visual feedback system to test whether path curvature was mainly determined by the visually perceived or actual location of the moving limb. Hand paths were measured for movements between three pairs of targets under both veridical and uniformly translated visual feedback. This allowed us to decouple the actual and perceived hand location during movement. Under different conditions of visual feedback the curvature of the hand paths did not correlate with either the visually perceived location of the limb or the actual location but rather with the relative displacement between the actual and visually perceived limb locations. The results are consistent with the hypothesis that in planning a movement the internal estimate of intrinsic coordinates, such as joint angles, is at least partially derived from visual information.

Evidence for an eye-centered spherical representation of the visuomotor map.

During visually guided movement, visual coordinates of target location must be transformed into coordinates appropriate for movement. To investigate the representation of this visuomotor coordinate transformation, we examined changes in pointing behavior induced by a local visuomotor remapping. The visual feedback of finger position was limited to one location within the workspace, at which a discrepancy was introduced between the actual and visually perceived finger position. This remapping induced a change in pointing that extended over the entire workspace and was best captured by a spherical coordinate system centered near the eyes.

Predicting the consequences of our own actions: the role of sensorimotor context estimation.

During self-generated movement it is postulated that an efference copy of the descending motor command, in conjunction with an internal model of both the motor system and environment, enables us to predict the consequences of our own actions (von Helmholtz, 1867; Sperry, 1950; von Holst, 1954; Wolpert, 1997). Such a prediction is evident in the precise anticipatory modulation of grip force seen when one hand pushes on an object gripped in the other hand (Johansson and Westling, 1984; Flanagan and Wing, 1933). Here we show that self-generation is not in itself sufficient for such a prediction. We used two robots to simulate virtual objects held in one hand and acted on by the other. Precise predictive grip force modulation of the restraining hand was highly dependent on the sensory feedback to the hand producing the load. The results show that predictive modulation requires not only that the movement is self-generated, but also that the efference copy and sensory feedback are consistent with a specific context; in this case, the manipulation of a single object. We propose a novel computational mechanism whereby the CNS uses multiple internal models, each corresponding to a different sensorimotor context, to estimate the probability that the motor system is acting within each context.

Temporal and amplitude generalization in motor learning.

A fundamental feature of human motor control is the ability to vary effortlessly over a substantial range, both the duration and amplitude of our movements. We used a three-dimensional robotic interface, which generated novel velocity dependent forces on the hand, to investigate how adaptation to these altered dynamics experienced only for movements at one temporal rate and amplitude generalizes to movements made at a different rate or amplitude. After subjects had learned to make a single point-to-point movement in a novel velocity-dependent force field, we examined the generalization of this learning to movements of both half the duration or twice the amplitude. Such movements explore a state-space not experienced during learning-any changes in behavior are due to generalization of the learning, the form of which was used to probe the intrinsic constraints on the motor control process. The generalization was assessed by determining the force field in which subjects produced kinematically normal movements. We found substantial generalization of the motor learning to the new movements supporting a nonlocal representation of the control process. Of the fields tested, the form of the generalization was best characterized by linear extrapolation in a state-space representation of the controller. Such an intrinsic constraint on the motor control process can facilitate the scaling of natural movements.

Maintaining internal representations: the role of the human superior parietal lobe.

In sensorimotor integration, sensory input and motor output signals are combined to provide an internal estimate of the state of both the world and one's own body. Although a single perceptual and motor snapshot can provide information about the current state, computational models show that the state can be optimally estimated by a recursive process in which an internal estimate is maintained and updated by the current sensory and motor signals. These models predict that an internal state estimate is maintained or stored in the brain. Here we report a patient with a lesion of the superior parietal lobe who shows both sensory and motor deficits consistent with an inability to maintain such an internal representation between updates. Our findings suggest that the superior parietal lobe is critical for sensorimotor integration, by maintaining an internal representation of the body's state.