Quantifying extent based haptic control in human motor adaptation

Humans possess a remarkable ability to rapidly and successful adapt to novel environments by predicting and compensating for external forces. Behavioral studies of human motor control often employ haptic paradigms that use a robotic manipulandum to impose forces on center-out reaching movements. Analysis of kinematic and dynamic data in these experiments can reveal the neurological underpinnings that enable adaptive control. Results from these psychophysical experiments can then be used to create new and improved models for motor control. Rigorous computational simulations can further test the viability of these models and use them to generate novel hypotheses for future behavioral experiments. There are innumerable facets of motor control that can be investigated with computational models and haptic paradigms; here, I will address models of spatial generalization and the quantification of extent based haptic control. In Chapter 2, I identify critical limitations in current neural network models of motor adaptation and test the viability of a new, more flexible network structure as an improved model. This new model is able to account for rapid changes in spatial generalization observed in humans adapting to environments of varying complexity. I use this updated model to predict generalization behavior in environments with sudden changes in spatial complexity; these predictions serve as novel hypotheses that may be tested behaviorally in future human psychophysical experiments. In Chapters 3 and 4, I describe and implement a novel paradigm, called a trajectory clamp, for capturing a complete 2-dimensional adaptive force profile for humans making reaching movements. This trajectory clamp improves upon prior methodology that was limited to measuring lateral forces by being able to also measure forces along the extent direction, or towards a target. I discuss the importance of studying extent based haptic control, and demonstrate the efficacy of the trajectory clamp for characterizing adaptive forces along both the extent and directional dimensions. Finally, I compare and contrast control in these two dimensions. Together, these experiments further current understanding of basic human motor control and theory. Advancements in these areas may also prove useful in clinical applications, including diagnostic and therapeutic implications for patients that exhibit motor deficits due to injury or disease