State-Dependent Effective Connectivity in Resting-State fMRI - Park, Hae-Jeong; Eo, Jinseok; Pae, Chongwon; Son, Junho; Park, Sung Min; Kang, Jiyoung (Frontiers in Neural Circuits, 2021)
The human brain at rest exhibits intrinsic dynamics transitioning among multiple metastable states of inter-regional functional connectivity. Accordingly, the demand for exploring the state-specific functional connectivity increases for a deeper understanding of mental diseases. Functional connectivity, however, lacks information about the directed causal influences among brain regions, called effective connectivity. This study presents a dynamic causal modeling (DCM) framework to explore state-dependent effective connectivity using spectral DCM for resting-state functional magnetic resonance imaging (rsfMRI). We established the sequence of brain states using the hidden Markov model with multivariate autoregressive coefficients of rsfMRI, summarizing functional connectivity. We decomposed state-dependent effective connectivity using a parametric empirical Bayes scheme that models effective connectivity of consecutive windows with the time course of discrete states as regressors. We showed the plausibility of the state-dependent effective connectivity analysis in a simulation setting. To test the clinical applicability, we applied the proposed method to characterize the state- and subtype-dependent effective connectivity of the default mode network in children with combined-type attention deficit hyperactivity disorder (ADHD-C) compared to age-matched, typically developed children (TDC). All 88 children were subtyped according to the occupation times (i.e., dwell times) of the three dominant functional connectivity states, independently of clinical diagnosis. State-dependent effective connectivity differences between ADHD-C and TDC according to subtypes and those between subtypes of ADHD-C were expressed mainly in self-inhibition, speaking to the importance of excitation inhibition balance in the subtyping. These findings provide a clear motivation for decomposing state-dependent dynamic effective connectivity and state-dependent analysis of the directed coupling in exploring mental diseases.