Pattern analysis of motor functional connectivity

Functional connectivity among brain regions has been widely researched in terms of spatial maps or between-region connectivity strengths. Yet it is not easy to interpret the results of such research. In this paper, a pattern analysis framework based on the general linear model and the fuzzy c-means clustering algorithm is presented. This schema is applied to a real fMRI dataset from unilateral finger movement tasks. The patterns of connectivity between the associative parietal cortex and BA6, and between the cerebellum and BA6, were detected and demonstrated their close integration. The connectivity patterns between BA6 and the primary motor cortex reflected the asymmetrical motor function organization related to handedness. Patterns between BA6 and the primary sensory cortex were complicated, which reflected their highly functional specialization.