| Haptic feedback can be utilized in human machine interfaces to make two-way interactions between the machine and users. How different types of haptic fields can affect the performance of an interaction has been subject of several recent studies. Also several psychophysical and neurophysiological studies have utilized haptic fields to understand how the brain controls movements. In this thesis, a visually guided target acquisition task and pursuit tracking was implemented as a laboratory simulation of certain types of human-machine interactions and by applying different external force fields the effect of each haptic condition on task performance and on brain neural activity was evaluated. Specifically, the discharge of cerebellar neurons were evaluated as functions of the kinematic and dynamic parameters of the task. The ultimate goal is to use this information to design human machine interfaces that by taking advantage of external force fields are more accurate, safer, more compatible with the human nervous system, and easier to use for both normal users as well as users with disabilities. The thesis has three main findings. First, in humans external force loads alter the underlying properties of the submovements. Second, in the monkey cerebellar Purkinje cells are modulated in relation to the geometry of the movement and not the dynamics. Third, the data does not support the hypothesis of an inverse dynamic internal model present in the cerebellum. |
