Reaching in motion: sensorimotor computations for reaching in accelerating reference frames
01 / 2011 - 01 / 2014
Neurocomputational theories suggest that the brain uses internal representations of body and world dynamics to generate accurate movement. These internal representations transform task goals into appropriate motor commands and estimate the state of the body and world, assisted by sensory feedback. Evidence for their neural implementation has been found in the cerebellum, during adaptation of eye and arm movements to altered kinematic and dynamic environments while the body is stationary. However, in more natural situations, goal-directed motor behavior should also deal with body movements, for example, grasping the safety rail while standing in a bus that unexpectedly decelerates, or trying to catch a ball while running. In such conditions the neural control system should account for ego-motion and integrate inertial forces due to body acceleration in the motor plans. Ego-motion is primarily detected by the vestibular system, but to date, the role of the vestibular system in estimating the state of the body and the world and its role in motor adaptation has been largely ignored. I propose a multi-pronged approach to assess the neural adaptation of the internal models for sensorimotor control in accelerating, non-inertial, reference frames. The proposal contains 4 subprojects that are all connected through a novel reach paradigm during whole-body acceleration with the aim to 1) model and examine the computational mechanisms in the processing and integration of noisy and ambiguous egomotion signals for internal model adaptation in reach control, and 2) identify the neural implementation of these integration and adaptation mechanisms. Especially the role of the cerebellum and vestibular system in reach control and adaptation under whole body acceleration will be studied. Behavioral deficits during reach adaptation in vestibular and cerebellar patient groups and healthy subjects with targeted brain areas turned off using rTMS, will provide valuable insights into the involvement of the affected brain structures.