The purpose of this project is to develop a deeper understanding of the mechanisms that allow reorganization of motor functions, and to identify means of exploiting these adaptive mechanisms to facilitate training of novel hand movements. Movement reorganization is needed to compensate for disability as well in normal daily activities, for example when one learns to operate a new vehicle. These studies will use and expand a novel, non-invasive paradigm to investigate the behavioral, neural and computational mechanisms for remapping of motor functions. This paradigm has been developed by the PI and the two co-investigators in a set of preliminary studies. Subjects wear an instrumented data glove that records the angular motions of the fingers. The signals generated by the glove operate a remotely-controlled endpoint - such as a cursor on a computer screen. Subjects are instructed to execute movements of this endpoint with controlled motions of the fingers. The overarching question addressed through this new paradigm concerns the representation of motor space - the space in which the controlled actions take place. How flexible, or """"""""plastic"""""""", is this representation and what is its relation to the space of motor control signals? The studies are organized in three specific aims:
Aim 1 : To investigate the formation of new coordinated hand movements for the control of a low- dimensional device Aim 2: To test the adaptive neural representations for reaching and grasping.
Aim 3 : To facilitate the learning of new motor maps for hand movements The expected outcomes will likely lead to more successful human-machine interactions and rehabilitation techniques for the disabled by identifying ways of selectively enhancing task-relevant visual feedback in order to better promote desired movement features, including more highly-individuated finger movements.
This proposal is directed at understanding the mechanisms underlying the reorganization of motor functions and motor coordination through a combination of behavioral observations, functional neuroimaging and computational techniques. It is expected that this study will identify new means for exploiting the ability of the nervous system to reorganize itself so as to facilitate training novel hand movements and to recover skills lost to stroke and other neuromotor disorders
| Ranganathan, Rajiv; Wieser, Jon; Mosier, Kristine M et al. (2014) Learning redundant motor tasks with and without overlapping dimensions: facilitation and interference effects. J Neurosci 34:8289-99 |
| Wang, Xue; Casadio, Maura; Weber 2nd, Kenneth A et al. (2014) White matter microstructure changes induced by motor skill learning utilizing a body machine interface. Neuroimage 88:32-40 |
| Ranganathan, Rajiv; Adewuyi, Adenike; Mussa-Ivaldi, Ferdinando A (2013) Learning to be lazy: exploiting redundancy in a novel task to minimize movement-related effort. J Neurosci 33:2754-60 |
| Eccarius, Petra; Bour, Rebecca; Scheidt, Robert A (2012) Dataglove measurement of joint angles in sign language handshapes. Sign Lang Linguist 15:39-72 |
| Huang, Felix C; Mussa-Ivaldi, Ferdinando A; Pugh, Carla M et al. (2012) Learning Kinematic Constraints in Laparoscopic Surgery. IEEE Trans Haptics 5:356-364 |
| Casadio, Maura; Ranganathan, Rajiv; Mussa-Ivaldi, Ferdinando A (2012) The body-machine interface: a new perspective on an old theme. J Mot Behav 44:419-33 |
| Scheidt, Robert A; Zimbelman, Janice L; Salowitz, Nicole M G et al. (2012) Remembering forward: neural correlates of memory and prediction in human motor adaptation. Neuroimage 59:582-600 |
| Danziger, Zachary; Mussa-Ivaldi, Ferdinando A (2012) The influence of visual motion on motor learning. J Neurosci 32:9859-69 |
| Mussa-Ivaldi, Ferdinando A; Casadio, Maura; Danziger, Zachary C et al. (2011) Sensory motor remapping of space in human-machine interfaces. Prog Brain Res 191:45-64 |
| Casadio, M; Pressman, A; Acosta, S et al. (2011) Body machine interface: remapping motor skills after spinal cord injury. IEEE Int Conf Rehabil Robot 2011:5975384 |
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