Altered Topological Properties of Gray Matter Structural Covariance Networks in Minimal Hepatic Encephalopathy

Zou, Tian-Xiu; She, Lilan; Zhan, Chuanyin; Gao, Yuying; Chen, Hua-Jun

doi:10.3389/fnana.2018.00101

Cited by 12 publications

(8 citation statements)

References 57 publications

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“…Basal ganglia are directly or indirectly connected to the cerebellum, thalamus, and prefrontal cortex, and these connections may be mediated by the cortico-basal ganglia-thalamo-cortical circuit (CBGTC). Therefore, CBF–FCS coupling was also calculated in these regions, as extracted from the AAL template that was used widely by brain image researchers (Dimitriadis et al, 2017; Zou et al, 2018). Given the difference between the AAL template and the standard MNI template used in this study, we firstly co-registered the AAL template to the standard GM mask and further mask it with the standard GM mask.…”

Section: Methodsmentioning

confidence: 99%

Aberrant Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Wilson’s Disease

et al. 2019

Front. Neural Circuits

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Both abnormalities of resting-state cerebral blood flow (CBF) and functional connectivity in Wilson’s disease (WD) have been identified by several studies. Whether the coupling of CBF and functional connectivity is imbalanced in WD remains largely unknown. To assess this possibility, 27 patients with WD and 27 sex- and age-matched healthy controls were recruited to acquire functional MRI and arterial spin labeling imaging data. Functional connectivity strength (FCS) and CBF were calculated based on standard gray mask. Compared to healthy controls, the CBF–FCS correlations of patients with WD were significantly decreased in the basal ganglia and the cerebellum and slightly increased in the prefrontal cortex and thalamus. In contrast, decreased CBF of patients with WD occurred predominately in subcortical and cognitive- and emotion-related brain regions, including the basal ganglia, thalamus, insular, and inferior prefrontal cortex, whereas increased CBF occurred primarily in the temporal cortex. The FCS decrease in WD patients was predominately in the basal ganglia and thalamus, and the increase was primarily in the prefrontal cortex. These findings suggest that aberrant neurovascular coupling in the brain may be a possible neuropathological mechanism underlying WD.

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Section: Methodsmentioning

confidence: 99%

Aberrant Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Wilson’s Disease

et al. 2019

Front. Neural Circuits

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“…The distribution of age and sex between groups was assessed using the two-sample t-test and the chi-squared test, respectively. The differences in network measures between the two groups were tested using a non-parametric permutation algorithm (Bullmore et al, 1999;He et al, 2008;Liu et al, 2016;Zou et al, 2018). First, we calculated the network metrics (Cp, Lp), small-world parameter (Sigma), and nodal characteristic (nodal betweenness) separately for the two groups across the density range (0.1:0.02:0.5).…”

Section: Statistical Analysesmentioning

confidence: 99%

“…Resilience indicates the tolerance of the network against random or targeted attack, and is relevant to the stability of the network ( Achard et al, 2006 ; He et al, 2008 ). Various neurological diseases are characterized by the topological properties of the brain structural covariance network ( Yao et al, 2010 ; Shi et al, 2012 ; Tao et al, 2018 ; Zou et al, 2018 ; Liu et al, 2019 ), such as the small-world property, network centrality, and resilience ( He et al, 2008 , 2009 ).…”

Section: Introductionmentioning

confidence: 99%

Altered Topological Properties of Brain Structural Covariance Networks in Patients With Cervical Spondylotic Myelopathy

Kuang

Zha

Liu

et al. 2020

Front. Hum. Neurosci.

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Background: Brain structural alterations play an important role in patients with cervical spondylotic myelopathy (CSM). However, while there have been studies on regional brain structural alterations, only few studies have focused on the topological organization of the brain structural covariance network. This work aimed to describe the structural covariance network architecture alterations that are possibly linked to cortex reorganization in patients with CSM. Methods: High-resolution anatomical images of 31 CSM patients and 31 healthy controls (HCs) were included in the study. The images were acquired using a sagittal three-dimensional T1-weighted BRAVO sequence. Firstly, the gray matter volume of 90 brain regions of automated anatomical labeling atlas were computed using a VBM toolbox based on the DARTEL algorithm. Then, the brain structural covariance network was constructed by thresholding the gray matter volume correlation matrices. Subsequently, the network measures and nodal property were calculated based on graph theory. Finally, the differences in the network metrics and nodal property between groups were compared using a non-parametric test. Results: Patients with CSM showed larger global efficiency and smaller local efficiency, clustering coefficient, characteristic path length, and sigma values than HCs. Patients with CSM had greater betweenness in the left superior parietal gyrus (SPG.L) and the left supplementary motor area (SMA.L) than HCs. Besides, patients with CSM had smaller betweenness in right middle occipital gyrus. The brain structural covariance networks of CSM patients exhibited equal resilience to random failure as those of HCs. However, the maximum relative size of giant connected components was approximately 10% larger in HCs than in CSM patients, upon removal of 44 nodes in targeted attack. Conclusion: These observed alternations in global network measures in CSM patients reflect that the brain structural covariance network in CSM exhibits the less optimal small-world model compared to that in HCs. Increased betweenness in SPG.L and

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“…Given that morphological measures, especially gray matter volume, have specific neurological and genetic bases, MBNs reflect the level of synchronous maturation between anatomical regions during brain development (Alexander‐Bloch, Giedd, & Bullmore, 2013). Converging evidence suggests that group‐level MBNs using structural covariance exhibit specific network patterns (Duan et al, 2020; Lim, Jung, & Aizenstein, 2013; Yun et al, 2020; Zou, She, Zhan, Gao, & Chen, 2018). Duan et al (2020) reported a decrease in long‐range structural covariance and an increase in structural covariance in subcortical structures in ASD, suggesting the crucial role of aberrant synchronized maturation between subcortical regions in social cognition and behavior in ASD.…”

Section: Introductionmentioning

confidence: 99%

Individual‐based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder

Cortés

Kang

et al. 2021

Human Brain Mapping

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Individual‐based morphological brain networks built from T1‐weighted magnetic resonance imaging (MRI) reflect synchronous maturation intensities between anatomical regions at the individual level. Autism spectrum disorder (ASD) is a socio‐cognitive and neurodevelopmental disorder with high neuroanatomical heterogeneity, but the specific patterns of morphological networks in ASD remain largely unexplored at the individual level. In this study, individual‐based morphological networks were constructed by using high‐resolution structural MRI data from 40 young children with ASD (age range: 2–8 years) and 38 age‐, gender‐, and handedness‐matched typically developing children (TDC). Measurements were recorded as threefold. Results showed that compared with TDC, young children with ASD exhibited lower values of small‐worldness (i.e., σ) of individual‐level morphological brain networks, increased morphological connectivity in cortico‐striatum‐thalamic‐cortical (CSTC) circuitry, and decreased morphological connectivity in the cortico‐cortical network. In addition, morphological connectivity abnormalities can predict the severity of social communication deficits in young children with ASD, thus confirming an associational impact at the behavioral level. These findings suggest that the morphological brain network in the autistic developmental brain is inefficient in segregating and distributing information. The results also highlight the crucial role of abnormal morphological connectivity patterns in the socio‐cognitive deficits of ASD and support the possible use of the aberrant developmental patterns of morphological brain networks in revealing new clinically‐relevant biomarkers for ASD.

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Altered Topological Properties of Gray Matter Structural Covariance Networks in Minimal Hepatic Encephalopathy

Cited by 12 publications

References 57 publications

Aberrant Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Wilson’s Disease

Aberrant Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Wilson’s Disease

Altered Topological Properties of Brain Structural Covariance Networks in Patients With Cervical Spondylotic Myelopathy

Individual‐based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder

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