Brain language: Uncovering functional connectivity codes

Abstract

The functional connectivity within a specific set of brain networks (or domain) can assume different configurations known as domain states that change with time. Recently, we proposed an information theoretical framework that models the finite set of domain states as elements of an alphabet. Significant bits of information have been found to be shared among domains, but specific domain codification was not explored. This work describes a method to identify code words used to transmit and receive information between the cerebrum and the cerebellum based on dynamic domain connectivity estimated from functional magnetic resonance imaging (fMRI). Following the theory of jointly typical sets, the developed method identifies the codeword length and the specific combination of domain states on each codeword. Resting state fMRI data was taken from 121 subjects with no significant age difference between males and females. Group independent component analysis was utilized to identify important brain networks and group them in a cerebellum and six other domains representing the cerebrum. The amount of information between the cerebellum, the executive control and sensorimotor domains showed a statistically significant number of bits. The proposed method quantified specific temporal sequences of domain states encoded within bits shared between cerebellum and cerebrum.