Simulation of Motor Cortex Connectivity in Different States

Motor cortex network was represented as a directed graph and implemented as a dynamic system in order to study the mechanisms of impairment and recovery. Complexity was used to express the extent to which a system is both functionally segregated and functionally integrated. Motor cortex network was optimized by pattern search to investigate the change of connectivity in rest, movement and stroke state. The simulation results show that motor areas have stronger connections in movement state. The strength decreases in stroke, which relates to disconnection mode. The intra-hemisphere connections are stronger than others and self-connections are week in either state. It indicates the model can reflect the plasticity of cerebral motor cortex qualitatively according to clinical trials. An understanding of the connectivity changes in cerebral networks following stroke will facilitate the development of novel therapeutic techniques that are based on neurobiological principles and will allow the delivery of specific therapies to appropriately targeted patients suffering from stroke.