Energetically costly functional network dynamics in cognitively impaired multiple sclerosis patients
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Background and objectives
Patients with multiple sclerosis (MS) often experience cognitive impairment, and this is related to structural disconnection and subsequent functional reorganization. It is not clear how specific patterns of functional reorganization might make it harder for cognitively impaired (CI) MS patients to dynamically adapt how brain regions communicate, which is crucial for normal cognition. To identify patterns relevant to cognitive impairment in MS, we performed a temporally detailed analysis of connectivity state transitions and quantified the effort associated with such dynamic alterations.
Methods
Resting-state functional and diffusion MRI was acquired from 95 controls and 330 MS patients (mean disease duration: 15 years) in a cross-sectional design, of whom 86 were classified as CI (≥2/7 domains Z < −2) and 65 as mildly CI (≥2/7 domains Z < −1.5) based on the performance on an expanded Brief Repeatable Battery of Neuropsychological Tests. Four functional connectivity states were determined using K -means clustering of moment-to- moment co-fluctuations (i.e., edge time series), and the resulting state sequence was used to characterize the frequency of transitions between network configurations. The control energy associated with the transitions between states was then calculated using the structural network of each subject with network control theory.
Results
CI patients transition less frequently between connectivity states. Relative to the time spent in a particular state, CI patients specifically transition less from a weakly connected and highly modular state (i.e., the weakly connected state ) to a more integrated state that featured strong involvement of the visual network (i.e., the visual network state ), but more in the opposite direction. CI patients also required more control energy to transition between states.
Discussion
This study showed that it became more effortful for MS patients with cognitive impairment to dynamically change the organization of the functional network, providing an intuitive understanding of why these transitions occur less frequently in some patients. In particular, transitions between the weakly connected state and the more integrated visual network state were relevant for cognition in these patients. The findings highlight a possible underpinning of disturbed cognition in MS patients and also provide novel avenues for studying and possibly improving network dynamics.
