Identification and Modeling of Sensory Feedback Processing in a Brain System for Voluntary Movement Control

Sammanfattning: The body shows impressive control capabilities in terms of the speed and the precision with which movements can be carried out under a wide variety of circumstances. The cerebellum and brainstem nuclei, including the cuneate nucleus, are believed to play a crucial role in this control. If these control mechanisms can be unveiled, this could yield important insights in not only medicine and neurophysiology, but could also control theory in general, which could then potentially be applied in a variety of industry-based control applications. In this thesis system identification and modeling of one subsystem is considered: the cuneate nucleus. The aim of this project is to create a quantitative model for control of a network of neurons in this structure and to create a detailed single-cell model of the cuneate neuron. A two-pronged approach is used to study the function of this structure. First a black-box like system identification using Matlab with experimental data as in- and output signals is considered. Then, building on a previously developed Scicos neuron model, a detailed neuron model of one cuneate neuron is developed, incorporating many aspects of recently described cellular neurophysiology. Our findings suggest that the cuneate nucleus acts as filter for its input sensory signal, applying a differentiating and phase-lead effect on the transmitted signal. These are interesting features of a control system, and could help understand how the body can attain such a high degree of precision in its movements.