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Published on: May 10, 2017
System-specific reductions of resting-state BOLD signal entropy in disorders of consciousness
Shanshan Chen1,2, Haoran Chen3, Nan Zhang4
1Xinjing Normal University, Urumqi, China. shanchen0923@gmail.com.
Objective:
Disorders of consciousness (DoC) are associated with large-scale abnormalities in brain function, but system-specific alterations in regional resting-state BOLD signal entropy remain poorly understood. Here, we examined regional entropy of resting-state fMRI signals in patients with minimally conscious state (MCS) and unresponsive wakefulness syndrome (UWS).
Methods:
Resting-state fMRI was acquired in 23 MCS patients, 31 UWS patients, and 20 age-matched healthy controls. Regional entropy was estimated from voxel-wise BOLD signals within anatomically defined brain regions using a PCA-based framework, allowing quantification of covariance-based regional BOLD signal variability across the whole brain. Pairwise group comparisons were performed at both the ROI level and in grouped functionally relevant regional sets.
Results:
Relative to healthy controls, MCS patients showed reduced regional entropy mainly in sensory- and memory-related regions, whereas UWS patients showed widespread reductions across sensory, memory-related, and high-order cognitive regions. In grouped regional-set analyses, entropy in sensory and memory systems showed a graded decrease from healthy controls to MCS and from MCS to UWS. In contrast, entropy in high-order cognitive systems remained relatively preserved in MCS and was significantly reduced only in UWS, with the exception of the posterior cingulate cortex and precuneus.
Conclusion:
These findings demonstrate system-specific reductions in resting-state BOLD signal entropy in DoC and reveal distinct patterns of altered regional BOLD signal variability across sensory, memory-related, and high-order cognitive systems in MCS and UWS. Regional BOLD signal entropy may provide a quantitative regional description of altered brain dynamics in DoC and complement existing work on large-scale communication and network dysfunction.

