Determining functional units of tongue motion from magnetic resonance imaging

Abstract

The human tongue produces oromotor behaviors such as speaking, swallowing, and breathing, which are executed by deforming local functional units using complex muscular array. Therefore, identifying functional units and understanding the mechanisms of coupling among them in relation to the underlying anatomical structures can aid significantly in the understanding of normal motor control and the development of clinical diagnoses and surgical procedures. Magnetic resonance imaging (MRI) has been widely used to observe detailed structures in the vocal tract and to measure internal tissue motion of the tongue. This work aims at determining the functional units from tagged MRI and muscle maps are extracted from high-resolution MRI. A non-negative matrix factorization method with a sparsity constraint is utilized to extract an activation map for each tissue point using a set of motion quantities extracted from tagged MRI including information from point trajectories (i.e., displacement, angle, and curvature) and strain. The activation map is then used to determine the coherent region using spectral clustering, revealing functional units and their relations to the underlying muscles. We test our algorithm on simple protrusion and speech tasks, demonstrating that the proposed algorithm can determine the correlated patterns of the tissue point tracking trajectories and strain.