Force Field Generalization and the Internal Representation of Motor Learning

When learning a new motor behavior, e.g. reaching in a force field, the nervous system builds an internal representation. Examining how subsequent reaches in unpracticed directions generalize reveals this representation. Though it is the subject of frequent studies, it is not known how this representation changes across training directions, or how changes in reach direction and the corresponding changes in limb impedance, influence measurements of it. We ran a force field adaptation experiment using eight groups of subjects each trained on one of eight standard directions and then tested for generalization in the remaining seven directions. Generalization in all directions was local and asymmetric, providing limited and unequal transfer to the left and right side of the trained target. These asymmetries were not consistent in either magnitude or direction even after correcting for changes in limb impedance, at odds with previous explanations. Relying on a standard model for generalization the inferred representations inconsistently shifted to one side or the other of their respective training direction. A second model that accounted for limb impedance and variations in baseline trajectories explained more data and the inferred representations were centered on their respective training directions. Our results highlight the influence of limb mechanics and impedance on psychophysical measurements and their interpretations for motor learning.Comment: Accepted for Publication in PLoS One Journa

Linearity, motor primitives and low-dimensionality in the spinal organization of motor control

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 149-154).The typical biological system is nonlinear, high-dimensional and highly redundant, all of which are burdens on controller design. Yet despite these complications, the central nervous system is able to control motor systems with an impressive level of complexity and effectivity. One such example is the frog. Evidence suggests that in frogs, the central nervous system, and the spinal cord in particular, may adopt simplifying strategies to ease the motor control problem. For instance, despite the known nonlinear nature of muscle, it has been demonstrated experimentally that spinally induced force production in the frog limb is linear in stimulation. Spinally encoded force fields have also been implicated as building blocks for generating hind limb movements. Furthermore, muscle EMG measurements for both intact and spinalized animals, have been shown to be low-dimensional; these measurements can be reconstructed as linear combinations of fixed muscle activations, or synergies. The evidence above suggests that the central nervous system may adopt simplifying strategies for the motor control problem. First, the thesis addresses the issue of linearity in isometric force fields. It proposes that this behavior can be explained as a result of biomechanical properties. To this end, a physiologically realistic model of the frog hind limb is analyzed.(cont.) The results suggest that, due to features of the musculo-skeletal structure, forces produced by the hind limb muscles are linear in activation, in large part and within the limb's workspace. The results, therefore, support our hypothesis that muscle forces which scale linearly in activation are a natural biomechanical result. The second portion of the thesis centers on the evidence of low-dimensional motor commands and the hypothesized motor primitives (in the form both of force fields and of muscle synergies). Many investigations have examined muscle synergies, probed motor behaviors for modular features in the form of force fields, and looked for connections between synergies and force fields. However, this work has largely been descriptive in nature, trying to explain the data without reference to the underlying control structure. We offer a principled explanation for motor primitives, for how force fields and synergies arise, and for how they are implicated in the organization of motor control. A controller that utilizes a reduced order model is proposed. Using apparatuses drawn from model order reduction theory, a method for finding a low-dimensional model that estimates a nonlinear model of the frog hind limb is examined. A formalism for defining motor primitives is proposed and the resulting primitives are compared with experimentally derived synergies.(cont.) The motor primitives are found to correspond well with several synergies, and to offer practical interpretations in terms of limb biomechanics. The reduced model is shown to be capable of generating natural motor behaviors as well as optimal control solutions. The evidence suggests that frog hind limb motor behaviors, and the spinal circuitry that coordinates these behaviors, are consistent with a control architecture that utilizes a reduced order model of the musculo-skeletal system in an effort to simplify motor control.by Max Berniker.Ph.D

Learning Priors for Bayesian Computations in the Nervous System

Our nervous system continuously combines new information from our senses with information it has acquired throughout life. Numerous studies have found that human subjects manage this by integrating their observations with their previous experience (priors) in a way that is close to the statistical optimum. However, little is known about the way the nervous system acquires or learns priors. Here we present results from experiments where the underlying distribution of target locations in an estimation task was switched, manipulating the prior subjects should use. Our experimental design allowed us to measure a subject's evolving prior while they learned. We confirm that through extensive practice subjects learn the correct prior for the task. We found that subjects can rapidly learn the mean of a new prior while the variance is learned more slowly and with a variable learning rate. In addition, we found that a Bayesian inference model could predict the time course of the observed learning while offering an intuitive explanation for the findings. The evidence suggests the nervous system continuously updates its priors to enable efficient behavior

Estimating the Relevance of World Disturbances to Explain Savings, Interference and Long-Term Motor Adaptation Effects

Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters

A biologically motivated paradigm for heuristic motor control in multiple contexts

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.Includes bibliographical references (p. 121-124).by Max Berniker.S.M

Visual feedback of hand and target location does not explain the tendency for straight adapted reaches.

Subjects in laboratory settings exhibit straight hand paths-typified by the minimum jerk path-even in the presence of a learned but disturbing force field. At the same time it is known that in this setting, visual feedback strongly influences reaches, biasing them to be straight. Here we examine whether or not this bias can account for the straightness of movements made in a force field. We ran three curl field experiments to investigate how the lack of visual feedback influences adapted reaches. In a first experiment, hand position was displayed at the beginning and at the end of each trial, but extinguished during movement, and the hand was passively brought back to the home location. In the second experiment, visual feedback of neither the hand nor the target was provided, and targets were haptically rendered as "dimples." In order to provide extended practice, a third experiment was run with a single target and an active reach back to the home location. In all three cases we found minor changes in the adapted reaches relative to control groups that had full visual feedback. Our subjects adopted trajectories that were better explained by minimum jerk paths over those that minimize effort. The results indicate that for point-to-point reaching movements the visual feedback, or lack there of, cannot explain why reaches appear to be straight, even after adapting to a perturbing force field

Correction: Force field generalization and the internal representation of motor learning.

[This corrects the article DOI: 10.1371/journal.pone.0225002.]

Error clamps and spontaneous rebound.

<p>A) Inferred body and world rotation parameters and probability of relevance during adaptation to a visuomotor disturbance and subsequent error clamp. In the error clamp, feedback indicates a lack of errors regardless of movements. B) Experimental data of normalized reaching forces during adaptation to a force disturbance and subsequent error clamp (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Scheidt1" target="_blank">[24]</a>). C) Inferred body and world rotations and the probability of relevance during presentation of a visuomotor disturbance, visuomotor disturbance of opposite orientation and subsequent error clamp. D) Experimental data of normalized reaching forces during a force disturbance, opposite disturbance and subsequent error clamp (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Smith1" target="_blank">[5]</a>).</p

Short-term savings after washout.

<p>A) Angular reach errors during the first presentation of a visuomotor disturbance, washout (while grasping robot) and subsequent presentation of the same disturbance B) Inferred body and world rotation parameters during adaptation and the corresponding probability of relevance. C) Angular reach errors from first and second presentation of visuomotor disturbance overlaid.</p