This research is aimed at understanding the relationship between (a) the acquisition of new coordinated movements and (b) the adaptation to novel mechanical environments. Both processes entail long-lasting changes in behavior induced by sensorimotor experience. However, while learning of new movements may require intense training and well-focused attention, motor adaptation may occur spontaneously, without need for explicit instructions. The central goal of this proposal is to create a unified experimental and theoretical framework for the analysis of motor learning and adaptation, based on the working hypothesis that both endeavors may be obtained by the central nervous system combining the operation of a few simple modules of control. Accordingly, the investigations are divided in three sets of experiments: (1) In the first, mechanical perturbations will be used to estimate the force fields generated by subjects maintaining their hand at rest in different locations. These fields will be considered as the expression of the most elementary modules of control. (2) The second is aimed at representing more complex control fields as a combination of the above modules. Mechanical perturbations will be used to estimate the force fields generated by the subjects (a) during the execution of different trajectories of the hand and (b) during the process of adaptation to complex mechanical environments generated by a servo-controlled manipulandum. (3) The third will investigate how subjects learn complex hand trajectories and to what extent trajectory learning may be obtained or facilitated by adapting to specifically designed mechanical environments. The design of these environments will be made possible by the common representation of learning and adaptation as measurable fields of forces. The proposed experiments have significance to clinical problems: If the motor system has automatic processes for adapting to changes in the mechanics of the environment, then these experiments will determine how to take advantage of adaptive processes for facilitating the recovery of motor skills that have been lost due to stroke or other CNS injuries.
| Farshchiansadegh, Ali; Melendez-Calderon, Alejandro; Ranganathan, Rajiv et al. (2016) Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation. PLoS Comput Biol 12:e1004861 |
| Casadio, Maura; Pressman, Assaf; Mussa-Ivaldi, Ferdinando A (2015) Learning to push and learning to move: the adaptive control of contact forces. Front Comput Neurosci 9:118 |
| Saha, Devjani J; Hu, Xiao; Perreault, Eric et al. (2015) The coordinate system for force control. Exp Brain Res 233:899-908 |
| Berniker, Max; Franklin, David W; Flanagan, J Randall et al. (2014) Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning. J Neurophysiol 111:1165-82 |
| Patton, James L; Wei, Yejun John; Bajaj, Preeti et al. (2013) Visuomotor learning enhanced by augmenting instantaneous trajectory error feedback during reaching. PLoS One 8:e46466 |
| Piovesan, D; Melendez-Calderon, A; Mussa-Ivaldi, F A (2013) Haptic recognition of dystonia and spasticity in simulated multi-joint hypertonia. IEEE Int Conf Rehabil Robot 2013:6650449 |
| Melendez-Calderon, A; Piovesan, D; Mussa-Ivaldi, F A (2013) Therapist recognition of impaired muscle groups in simulated multi-joint hypertonia. IEEE Int Conf Rehabil Robot 2013:6650425 |
| Piovesan, D; Melendez-Calderon, A; Mussa-Ivaldi, F A (2013) Haptic perception of multi-joint hypertonia during simulated patient-therapist physical tele-interaction. Conf Proc IEEE Eng Med Biol Soc 2013:4143-7 |
| Piovesan, Davide; Morasso, Pietro; Giannoni, Psiche et al. (2013) Arm stiffness during assisted movement after stroke: the influence of visual feedback and training. IEEE Trans Neural Syst Rehabil Eng 21:454-65 |
| Piovesan, Davide; Casadio, Maura; Mussa-Ivaldi, Ferdinando A et al. (2012) Comparing Two Computational Mechanisms for Explaining Functional Recovery in Robot-Therapy of Stroke Survivors. Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatron 2012:1488-1493 |
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