Aberrant functional brain network dynamics in patients with functional constipation

Abstract

The aberrant static functional connectivity of brain network has been widely investigated in patients with functional constipation (FCon). However, the dynamics of brain functional connectivity in FCon patients remained unknown. This study aimed to detect the brain dynamics of functional connectivity states and network topological organizations of FCon patients and investigate the correlations of the aberrant brain dynamics with symptom severity. Eighty-three FCon patients and 80 healthy subjects (HS) were included in data analysis. The spatial group independent component analysis, sliding-window approach, k-means clustering, and graph-theoretic analysis were applied to investigate the dynamic temporal properties and coupling patterns of functional connectivity states, as well as the time-variation of network topological organizations in FCon patients. Four reoccurring functional connectivity states were identified in k-means clustering analysis. Compared to HS, FCon patients manifested the lower occurrence rate and mean dwell time in the state with a complex connection between default mode network and cognitive control network, as well as the aberrant anterior insula-cortical coupling patterns in this state, which were significantly correlated with the symptom severity. The graph-theoretic analysis demonstrated that FCon patients had higher sample entropy at the nodal efficiency of anterior insula than HS. The current findings provided dynamic perspectives for Tao Yin, Zhaoxuan He, and Peihong Ma contributed equally to this study and are also the co-first authors.

The Role of Medial Prefrontal Cortex in Acupuncture Treatment for Functional Dyspepsia

“…The DMN is a functional network composed of brain regions that maintain synchronous, low-frequency spontaneous neuronal activity in a resting state and continue to be negatively activated in a task state ( Lei et al, 2013 ) and is thought to be associated with social behavior, emotional control, and sensory-visceral movements. Several neuroimaging studies have demonstrated the DMN alternations in patients with gastrointestinal diseases, including FD ( Liu et al, 2013 ), functional constipation (FC) ( Yin et al, 2021 ), irritable bowel syndrome (IBS) ( Qi et al, 2016 ), Crohn’s disease (CD) ( Thomann et al, 2017 ), and ulcerative colitis (UC) ( Skrobisz et al, 2020 ), and suggested the involvement of DMN in the abnormal process of brain–gut interaction in these gastrointestinal diseases. For example, a structural MRI indicated that, compared with healthy subjects, FD patients showed significant cortical thickness alterations in some regions of DMN such as mPFC, PCC, AG, etc.…”

Abnormal Static and Dynamic Functional Connectivity in Left and Right Temporal Lobe Epilepsy

“…The remaining volumes underwent slice timing correction and realignment. To eliminate the influence of head motion, participants were excluded if they presented mean frame-wise displacement (FD) values > 0.2 mm, or if the maximum displacement was > 3 mm, or 3° in angular rotation (Power et al, 2014 ; Yin et al, 2021 ). The functional images were co-registered to the individual T1 image, then normalized to the Montreal Neurological Institute (MNI) space using an affine transformation with the voxels resampled to a resolution of 3 × 3 × 3 mm.…”

Aberrant resting-state functional connectivity and topological properties of the subcortical network in functional dyspepsia patients

“…To characterize the topological properties of the SCN, graph-theoretic analysis was conducted with the Graph Theoretical Network Analysis toolbox (GRETNA) 2.0 toolbox 3 ( Wang et al, 2015 ). First, the constructed SCN rsFC matrix was post-processed with the following three steps: (1) sparsity all matrices with the thresholds of 0.1 to 0.35 (step = 0.05) ( Tu et al, 2019 ; Yin et al, 2021a ), and thresholded each symmetrical matrix into a binarized matrix with a fixed sparsity value, and only positive connections were analyzed, and then six binary matrixes were created; (2) generate benchmark random networks that match real SCN with respect to the number of nodes and edges and degree distribution; and (3) calculate graph-based global and nodal network metrics, and the details and interpretations of global and nodal topological properties were described in Supplementary material 2 . Second, the integrated area under the curve (AUC) value of all related network metrics over the corresponding sparsity range (0.1 ≤ range ≤ 0.35, step = 0.05) was calculated to explore the SCN topological properties differences between FD patients and HC.…”