Pregnancy leads to changes in the brain functional network: a connectome analysis

Author(s):  
Tongpeng Chu ◽  
Yuna Li ◽  
Kaili Che ◽  
Fanghui Dong ◽  
Heng Ma ◽  
...  
2021 ◽  
Vol 15 ◽  
Author(s):  
Jia Tuo ◽  
Wei He ◽  
Shuai Yang ◽  
Lihui Liu ◽  
Xiaojuan Liu ◽  
...  

Purpose: Previous studies have found that there are significant changes in functional network properties for patients with moderate to severe carotid artery stenosis. Our study aimed to explore the topology properties of brain functional network in asymptomatic patients with carotid plaque without significant stenosis.Methods: A total of 61 asymptomatic patients with carotid plaque (mean age 61.79 ± 7.35 years) and 25 healthy control subjects (HC; 58.12 ± 6.79 years) were recruited. General data collection, carotid ultrasound examination and resting state functional magnetic resonance imaging were performed on all subjects. Graph-theory was applied to examine the differences in the brain functional network topological properties between two groups.Results: In the plaque group, Eloc(P = 0.03), γ (P = 0.01), and σ (P = 0.01) were significantly higher than in the HC group. The degree centrality of left middle frontal gyrus and the nodal efficiency of left middle frontal gyrus and right inferior parietal angular gyrus were significantly higher in the plaque group than in HC. The degree centrality and betweenness centrality of right middle temporal gyrus, as well as the nodal efficiency of right middle temporal gyrus, were significantly lower in the plaque group than in HC.Conclusions: The brain functional networks of patients with carotid plaques differ from those of healthy controls. Asymptomatic patients with carotid plaques exhibit increased local and global connectivity, which may reflect subtle reorganizations in response to early brain damage.


2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  

Abstract Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state functional magnetic resonance imaging studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here, we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50–64 years versus older group (n = 310); age range, 65–91 years). Applying the intrinsic-ignition framework to assess the effect of spontaneous local activation events on local–global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.


2013 ◽  
Vol 9 (9) ◽  
pp. 1404-1412 ◽  
Author(s):  
Chang-hyun Park ◽  
Sheng-Min Wang ◽  
Hae-Kook Lee ◽  
Yong-Sil Kweon ◽  
Chung Tai Lee ◽  
...  

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0132518 ◽  
Author(s):  
Xue Wen ◽  
Delong Zhang ◽  
Bishan Liang ◽  
Ruibin Zhang ◽  
Zengjian Wang ◽  
...  

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Ziqing Zhang ◽  
Shu Sun ◽  
Ming Yi ◽  
Xia Wu ◽  
Yiming Ding

Using an effective method to measure the brain functional connectivity is an important step to study the brain functional network. The main methods for constructing an undirected brain functional network include correlation coefficient (CF), partial correlation coefficient (PCF), mutual information (MI), wavelet correlation coefficient (WCF), and coherence (CH). In this paper we demonstrate that the maximal information coefficient (MIC) proposed by Reshef et al. is relevant to constructing a brain functional network because it performs best in the comprehensive comparisons in consistency and robustness. Our work can be used to validate the possible new functional connection measures.


Author(s):  
Xiaomeng Li ◽  
Longlun Wang ◽  
Bin Qin ◽  
Yun Zhang ◽  
Zhiming Zhou ◽  
...  

Objectives: The brain functional network of autism spectrum disorders (ASDs) in the earlier stages of life has been almost unknown due to difficulties in obtaining a resting-state functional magnetic resonance imaging (rs-fMRI). This study aimed to perform rs-MRI under a sedated sleep state and reveal possible alterations in the brain functional network. Methods: Rs-fMRI was performed in a group of preschool children (aged 2–6 years, 53 with ASD, 63 as controls) under a sedated sleeping state. Based on graph theoretical analysis, global and local topological metrics were calculated to investigate alterations in brain functional networks. Besides, correlation analyses were conducted between the abnormal attribute values and the Childhood Autism Rating Scale (CARS) scores. Results: The graph theoretical analysis showed that the nodal degree of the right medial frontal gyrus and the nodal efficiency of the right lingual gyrus in the ASD group were higher than those in the control group (P<0.05). There was a statistically significant positive correlation (R=0.318, P<0.05) between the right midfrontal gyrus nodal degree values and CARS scores in the ASD patients. Conclusion: Alterations of some nodal attributes in the brain network occurred in preschool autistic children which could serve as potential imaging biomarkers for evaluating ASD in earlier stages.


2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Yu Shi ◽  
Yanyan Zeng ◽  
Lei Wu ◽  
Ziping Liu ◽  
Shanshan Zhang ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Gang Li ◽  
Yanting Xu ◽  
Yonghua Jiang ◽  
Weidong Jiao ◽  
Wanxiu Xu ◽  
...  

Mental fatigue has serious negative impacts on the brain cognitive functions and has been widely explored by the means of brain functional networks with the neuroimaging technique of electroencephalogram (EEG). Recently, several researchers reported that brain functional network constructed from EEG signals has fractal feature, raising an important question: what are the effects of mental fatigue on the fractal dimension of brain functional network? In the present study, the EEG data of alpha1 rhythm (8-10 Hz) at task state obtained by a mental fatigue model were chosen to construct brain functional networks. A modified greedy colouring algorithm was proposed for fractal dimension calculation in both binary and weighted brain functional networks. The results indicate that brain functional networks still maintain fractal structures even when the brain is at fatigue state; fractal dimension presented an increasing trend along with the deepening of mental fatigue fractal dimension of the weighted network was more sensitive to mental fatigue than that of binary network. Our current results suggested that mental fatigue has great regular impacts on the fractal dimension in both binary and weighted brain functional networks.


2014 ◽  
Vol 111 (7) ◽  
pp. 1455-1465 ◽  
Author(s):  
Seung-Hyun Jin ◽  
Woorim Jeong ◽  
Dong-Soo Lee ◽  
Beom Seok Jeon ◽  
Chun Kee Chung

A question to be addressed in the present study is how different the eyes-closed (EC) and eyes-open (EO) resting states are across frequency bands in terms of efficiency and centrality of the brain functional network. We investigated both the global and nodal efficiency and betweenness centrality in the EC and EO resting states from 39 volunteers. Mutual information was used to obtain the functional connectivity for each of the four frequency bands (theta, alpha, beta, and gamma). We showed that the cortical hubs with high betweenness centrality were maintained in the EC and EO resting states. We further showed that these hubs were associated with more than three frequency bands, suggesting that these hubs play an important role in the brain functional network at multiple temporal scales in the resting states. Enhanced global efficiency values were found in the theta and alpha bands in the EO state compared with those in the EC state. Moreover, it turned out that in the EO state the functional network was reorganized to enhance nodal efficiency at the nodes related to both the default mode and the dorsal attention networks and sensory-related resting-state networks. This result suggests that in the EO state the brain functional network was efficiently reorganized, facilitating the adaptation of the brain network to the change in state, which could help in understanding brain disorders that have a disturbance in communication with external environments by using the adaptation ability of brain functional networks.


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