Abstract
The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome.
Highlights
Previous studies found that the scan conditions of eyes-open (EO) or eyes-closed (EC) might have impacts on resting state functional connectivity [1]
Dynamical univariate and bivariate features of neural signals could be investigated in the unified framework of Hilbert transform, and could be supplementary features to investigate the neurophysiological processes in human brain
We demonstrated a unified framework to investigate the dynamical temporal patterns within and between ICNs under EO/EC
Summary
Previous studies found that the scan conditions of eyes-open (EO) or eyes-closed (EC) might have impacts on resting state functional connectivity [1]. Different active patterns were found in visual cortex under scan conditions of EO/EC [2]. Through voxel-level measures, the different dynamical attributes of spontaneous brain activities during EO/EC were discovered by the amplitude of low frequency fluctuations (ALFF) [1, 3,4,5]. Neurophysiological and identical alpha-band activities of MEG signals were related to resting states of EO/EC [8]. Reorganized functional networks were found between EO/EC across different frequency bands of MEG signals, suggesting the complexity of brain dynamics [9]. The directional properties of interactions among large-scale brain networks between EO/EC have been investigated by Gaussian Bayesian network [10], the dynamical patterns of brain networks under EO/EC still remain largely unexplored
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