scholarly journals Mental Fatigue Has Great Impact on the Fractal Dimension of Brain Functional Network

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Gang Li ◽  
Yanting Xu ◽  
Yonghua Jiang ◽  
Weidong Jiao ◽  
Wanxiu Xu ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Mental Fatigue ◽  
Functional Network ◽  
Functional Networks ◽  
Fractal Structures ◽  
Brain Functional Network ◽  
Brain Functional Networks ◽  
Negative Impacts ◽  
Binary Network ◽  
The Brain

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.

scholarly journals Correlation between the oral microbiome and brain resting state connectivity in smokers

2018 ◽  
Author(s):  
Dongdong Lin ◽  
Kent E. Hutchison ◽  
Salvador Portillo ◽  
Victor Vegara ◽  
Jarrod M. Ellingson ◽  
...  
Keyword(s):  
Microbial Community ◽  
Network Connectivity ◽  
Oral Microbiome ◽  
Functional Network ◽  
Functional Networks ◽  
Functional Network Connectivity ◽  
Brain Functional Network ◽  
Brain Functional Networks ◽  
The Brain

AbstractRecent studies have shown a critical role of the gastrointestinal microbiome in brain and behavior via the complex gut–microbiome–brain axis, however, the influence of the oral microbiome in neurological processes is much less studied, especially in response to the stimuli in the oral microenvironment such as smoking. Additionally, given the complex structural and functional networks in brain system, our knowledge about the relationship between microbiome and brain function in specific brain circuits is still very limited. In this pilot work, we leveraged next generation microbial sequencing with functional neuroimaging techniques to enable the delineation of microbiome-brain network links as well as their relationship to cigarette smoking. Thirty smokers and 30 age- and sex- matched non-smokers were recruited for measuring both microbial community and brain functional networks. Statistical analyses were performed to demonstrate the influence of smoking on the abundance of the constituents within the oral microbial community and functional network connectivity among brain regions as well as the associations between microbial shifts and the brain functional network connectivity alternations. Compared to non-smokers, we found a significant decrease in beta diversity (p = 6×10−3) in smokers and identified several classes (Betaproteobacteria, Spirochaetia, Synergistia, and Mollicutes) as having significant alterations in microbial abundance. Taxonomic analyses demonstrate that the microbiota with altered abundance are mainly involved in pathways related to cell processes, DNA repair, immune system, and neurotransmitters signaling. One brain functional network connectivity component was identified to have a significant difference between smokers and nonsmokers (p = 0.033), mainly including connectivity between brain default network and other task-positive networks. The brain functional component was also significantly associated with some smoking related oral microbiota, suggesting a potential link between smoking-induced oral microbiome dysbiosis and brain functional connectivity, possibly through immunological and neurotransmitter signaling pathways. This work is the first attempt to link oral microbiome and brain functional networks, and provides support for future work in characterizing the role of oral microbiome in mediating smoking effects on brain activity.

scholarly journals Disrupted Topological Organization of Functional Networks in Asymptomatic Carotid Plaque Without Significant Carotid Stenosis: A Resting-State fMRI Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Jia Tuo ◽  
Wei He ◽  
Shuai Yang ◽  
Lihui Liu ◽  
Xiaojuan Liu ◽  
...  
Keyword(s):  
Resting State ◽  
Carotid Plaque ◽  
Functional Network ◽  
Middle Temporal Gyrus ◽  
Functional Networks ◽  
Middle Temporal ◽  
Brain Functional Network ◽  
Asymptomatic Patients ◽  
The Brain ◽  
Left Middle

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.

scholarly journals The Maximum Eigenvalue of the Brain Functional Network Adjacency Matrix: Meaning and Application in Mental Fatigue Evaluation

2020 ◽  
Vol 10 (2) ◽  
pp. 92 ◽  
Author(s):  
Gang Li ◽  
Yonghua Jiang ◽  
Weidong Jiao ◽  
Wanxiu Xu ◽  
Shan Huang ◽  
...  
Keyword(s):  
Adjacency Matrix ◽  
Mental Fatigue ◽  
Functional Network ◽  
Maximum Eigenvalue ◽  
Characteristic Path Length ◽  
Brain Functional Network ◽  
Large Maximum ◽  
Fatigue Estimation ◽  
Fatigue Evaluation ◽  
High Degree

The maximum eigenvalue of the adjacency matrix (AM) has been supposed to contain rich information about the corresponding network. An experimental study focused on revealing the meaning and application of the maximum eigenvalue is missing. To this end, AM was constructed using mutual information (MI) to determine the functional connectivity with electroencephalogram (EEG) data recorded with a mental fatigue model, and then was converted into both binary and weighted brain functional network (BFN) and corresponding random networks (RNs). Both maximum eigenvalue and corresponding network characters in BFNs and RNs were considered to explore the changes during the formation of mental fatigue. The results indicated that large maximum eigenvalue means more edges in the corresponding network, along with a high degree and a short characteristic path length both in weighted and binary BFNs. Interestingly, the maximum eigenvalue of AM was always a little larger than that of the corresponding random matrix (RM), and had an obvious linearity with the sum of the AM elements, indicating that the maximum eigenvalue can be able to distinguish the network structures which have the same mean degree. What is more, the maximum eigenvalue, which increased with the deepening of mental fatigue, can become a good indicator for mental fatigue estimation.

scholarly journals Whole-Brain Dynamics in Aging: Disruptions in Functional Connectivity and the Role of the Rich Club

2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Network ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Rich Club ◽  
Brain Functional Network ◽  
Age Related ◽  
Age Range ◽  
The Brain

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.

scholarly journals Affective state-dependent changes in the brain functional network in major depressive disorder

2013 ◽  
Vol 9 (9) ◽  
pp. 1404-1412 ◽  
Author(s):  
Chang-hyun Park ◽  
Sheng-Min Wang ◽  
Hae-Kook Lee ◽  
Yong-Sil Kweon ◽  
Chung Tai Lee ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Affective State ◽  
Functional Network ◽  
Major Depressive ◽  
Brain Functional Network ◽  
State Dependent ◽  
The Brain

scholarly journals Reconfiguration of the Brain Functional Network Associated with Visual Task Demands

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0132518 ◽  
Author(s):  
Xue Wen ◽  
Delong Zhang ◽  
Bishan Liang ◽  
Ruibin Zhang ◽  
Zengjian Wang ◽  
...  
Keyword(s):  
Task Demands ◽  
Visual Task ◽  
Functional Network ◽  
Brain Functional Network ◽  
The Brain

Windows Into the Brain: Functional Networks Informing Treatment in Late-Life Depression

2017 ◽  
Vol 25 (3) ◽  
pp. S14-S15
Author(s):  
Warren D. Taylor ◽  
Sara Weisenbach ◽  
Faith Gunning ◽  
Olu Ajilore
Keyword(s):  
Late Life ◽  
Functional Networks ◽  
Late Life Depression ◽  
Brain Functional Networks ◽  
The Brain

scholarly journals MIC as an Appropriate Method to Construct the Brain Functional Network

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Ziqing Zhang ◽  
Shu Sun ◽  
Ming Yi ◽  
Xia Wu ◽  
Yiming Ding
Keyword(s):  
Correlation Coefficient ◽  
Partial Correlation ◽  
Functional Network ◽  
Functional Connection ◽  
Brain Functional Network ◽  
Information Coefficient ◽  
Brain Functional Connectivity ◽  
Maximal Information Coefficient ◽  
The Brain ◽  
Partial Correlation Coefficient

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.

Sign in / Sign up

Export Citation Format

Share Document