scholarly journals Hemispheric Asymmetry of Functional Brain Networks under Different Emotions Using EEG Data

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 939
Author(s):  
Rui Cao ◽  
Huiyu Shi ◽  
Xin Wang ◽  
Shoujun Huo ◽  
Yan Hao ◽  
...  
Keyword(s):  
Hemispheric Asymmetry ◽  
Right Hemisphere ◽  
Brain Networks ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Phase Lag ◽  
Characteristic Path Length ◽  
High Arousal ◽  
Eeg Data ◽  
The Right

Despite many studies reporting hemispheric asymmetry in the representation and processing of emotions, the essence of the asymmetry remains controversial. Brain network analysis based on electroencephalography (EEG) is a useful biological method to study brain function. Here, EEG data were recorded while participants watched different emotional videos. According to the videos’ emotional categories, the data were divided into four categories: high arousal high valence (HAHV), low arousal high valence (LAHV), low arousal low valence (LALV) and high arousal low valence (HALV). The phase lag index as a connectivity index was calculated in theta (4–7 Hz), alpha (8–13 Hz), beta (14–30 Hz) and gamma (31–45 Hz) bands. Hemispheric networks were constructed for each trial, and graph theory was applied to quantify the hemispheric networks’ topological properties. Statistical analyses showed significant topological differences in the gamma band. The left hemispheric network showed significantly higher clustering coefficient (Cp), global efficiency (Eg) and local efficiency (Eloc) and lower characteristic path length (Lp) under HAHV emotion. The right hemispheric network showed significantly higher Cp and Eloc and lower Lp under HALV emotion. The results showed that the left hemisphere was dominant for HAHV emotion, while the right hemisphere was dominant for HALV emotion. The research revealed the relationship between emotion and hemispheric asymmetry from the perspective of brain networks.

The Effects of Valence and Arousal on Hemispheric Asymmetry of Emotion

2011 ◽  
Vol 25 (2) ◽  
pp. 95-103 ◽  
Author(s):  
Jing Zhang ◽  
Renlai Zhou ◽  
Tian P. S. Oei
Keyword(s):  
Hemispheric Asymmetry ◽  
Right Hemisphere ◽  
Event Related Potentials ◽  
Main Role ◽  
High Arousal ◽  
Late Positive Potentials ◽  
Right Hemisphere Hypothesis ◽  
Related Potentials ◽  
Valence And Arousal ◽  
The Right

The independent influence of valence and arousal on emotional hemispheric brain asymmetry was investigated to decide between three contrasting hypotheses: the right hemisphere hypothesis, the valence hypothesis, and the integrative hypothesis. Event-related potentials (ERPs) were recorded while participants (N = 20) viewed positive high arousal, positive low arousal, negative high arousal, and negative low arousal pictures, following a baseline measure of ERPs while viewing gray squares. Self-ratings of emotional state in terms of valence and arousal were taken after each of the four emotion blocks. Valence and arousal effects on hemispheric asymmetry were analyzed for the time windows 130–170, 170–280, 280–450, and 450–600 ms. Right dominance on N2 during negative high arousal and left dominance on P3 and late positive potentials during negative low arousal were found over the frontal lobe. Right dominance on P2, P3, and late positive potentials over the parietal lobes appeared during high arousal. No frontal asymmetry was found in positive emotion. Our result partly supported the integrative hypothesis and did not provide evidence for the right hemisphere hypothesis or the valence hypothesis. These results suggested that arousal plays the main role in the ERPs’ hemispheric asymmetry.

scholarly journals Aberrant Brain Network Integration and Segregation in Diabetic Peripheral Neuropathy Revealed by Structural Connectomics

2020 ◽  
Vol 14 ◽  
Author(s):  
Fangxue Yang ◽  
Minli Qu ◽  
Youming Zhang ◽  
Linmei Zhao ◽  
Wu Xing ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Large Scale ◽  
Brain Networks ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Global Integration ◽  
Characteristic Path Length ◽  
Structural Covariance ◽  
The Central Nervous System

Diabetic peripheral neuropathy (DPN) is one of the most common forms of peripheral neuropathy, and its incidence has been increasing. Mounting evidence has shown that patients with DPN have been associated with widespread alterations in the structure, function and connectivity of the brain, suggesting possible alterations in large-scale brain networks. Using structural covariance networks as well as advanced graph-theory-based computational approaches, we investigated the topological abnormalities of large-scale brain networks for a relatively large sample of patients with DPN (N = 67) compared to matched healthy controls (HCs; N = 88). Compared with HCs, the structural covariance networks of patients with DPN showed an increased characteristic path length, clustering coefficient, sigma, transitivity, and modularity, suggestive of inefficient global integration and increased local segregation. These findings may improve our understanding of the pathophysiological mechanisms underlying alterations in the central nervous system of patients with DPN from the perspective of large-scale structural brain networks.

scholarly journals Connectome-Scale Assessments of Functional Connectivity in Children with Primary Monosymptomatic Nocturnal Enuresis

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Du Lei ◽  
Jun Ma ◽  
Jilei Zhang ◽  
Mengxing Wang ◽  
Kaihua Zhang ◽  
...  
Keyword(s):  
Nocturnal Enuresis ◽  
Brain Networks ◽  
Brain Network ◽  
Blood Oxygenation ◽  
Clustering Coefficient ◽  
Global Perspective ◽  
Characteristic Path Length ◽  
Network Analyses ◽  
Monosymptomatic Nocturnal Enuresis ◽  
Primary Monosymptomatic Nocturnal Enuresis

Primary monosymptomatic nocturnal enuresis (PMNE) is a common developmental disorder in children. Previous literature has suggested that PMNE not only is a micturition disorder but also is characterized by cerebral structure abnormalities and dysfunction. However, the biological mechanisms underlying the disease are not thoroughly understood. Graph theoretical analysis has provided a unique tool to reveal the intrinsic attributes of the connectivity patterns of a complex network from a global perspective. Resting-state fMRI was performed in 20 children with PMNE and 20 healthy controls. Brain networks were constructed by computing Pearson’s correlations for blood oxygenation level-dependent temporal fluctuations among the 2 groups, followed by graph-based network analyses. The functional brain networks in the PMNE patients were characterized by a significantly lower clustering coefficient, global and local efficiency, and higher characteristic path length compared with controls. PMNE patients also showed a reduced nodal efficiency in the bilateral calcarine sulcus, bilateral cuneus, bilateral lingual gyri, and right superior temporal gyrus. Our findings suggest that PMNE includes brain network alterations that may affect global communication and integration.

Differences in Functional Brain Networks Between Subjective Cognitive Decline with and without Worry Groups: A Graph Theory Study from SILCODE

2021 ◽  
pp. 1-11
Author(s):  
Yi Liu ◽  
Zhuoyuan Li ◽  
Xueyan Jiang ◽  
Wenying Du ◽  
Xiaoqi Wang ◽  
...  
Keyword(s):  
Graph Theory ◽  
Cognitive Decline ◽  
Path Length ◽  
Brain Networks ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Subjective Cognitive Decline ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Functional Brain Networks

Background: Evidence suggests that subjective cognitive decline (SCD) individuals with worry have a higher risk of cognitive decline. However, how SCD-related worry influences the functional brain network is still unknown. Objective: In this study, we aimed to explore the differences in functional brain networks between SCD subjects with and without worry. Methods: A total of 228 participants were enrolled from the Sino Longitudinal Study on Cognitive Decline (SILCODE), including 39 normal control (NC) subjects, 117 SCD subjects with worry, and 72 SCD subjects without worry. All subjects completed neuropsychological assessments, APOE genotyping, and resting-state functional magnetic resonance imaging (rs-fMRI). Graph theory was applied for functional brain network analysis based on both the whole brain and default mode network (DMN). Parameters including the clustering coefficient, shortest path length, local efficiency, and global efficiency were calculated. Two-sample T-tests and chi-square tests were used to analyze differences between two groups. In addition, a false discovery rate-corrected post hoc test was applied. Results: Our analysis showed that compared to the SCD without worry group, SCD with worry group had significantly increased functional connectivity and shortest path length (p = 0.002) and a decreased clustering coefficient (p = 0.013), global efficiency (p = 0.001), and local efficiency (p <  0.001). The above results appeared in both the whole brain and DMN. Conclusion: There were significant differences in functional brain networks between SCD individuals with and without worry. We speculated that worry might result in alterations of the functional brain network for SCD individuals and then result in a higher risk of cognitive decline.

Brain Network Dysfunction in Poststroke Delirium and Spatial Neglect: An fMRI Study

Stroke ◽  
2021 ◽  
Author(s):  
Olga Boukrina ◽  
Mateusz Kowalczyk ◽  
Yury Koush ◽  
Yekyung Kong ◽  
A.M. Barrett
Keyword(s):  
Right Hemisphere ◽  
Functional Neuroimaging ◽  
Brain Network ◽  
Spatial Neglect ◽  
Stroke Recovery ◽  
Network Activity ◽  
Brain Disorder ◽  
Fmri Study ◽  
The Right ◽  
Right Hemisphere Stroke

Background and Purpose: Delirium, an acute reduction in cognitive functioning, hinders stroke recovery and contributes to cognitive decline. Right-hemisphere stroke is linked with higher delirium incidence, likely, due to the prevalence of spatial neglect (SN), a right-brain disorder of spatial processing. This study tested if symptoms of delirium and SN after right-hemisphere stroke are associated with abnormal function of the right-dominant neural networks specialized for maintaining attention, orientation, and arousal. Methods: Twenty-nine participants with right-hemisphere ischemic stroke undergoing acute rehabilitation completed delirium and SN assessments and functional neuroimaging scans. Whole-brain functional connectivity of 4 right-hemisphere seed regions in the cortical-subcortical arousal and attention networks was assessed for its relationship to validated SN and delirium severity measures. Results: Of 29 patients, 6 (21%) met the diagnostic criteria for delirium and 16 (55%) for SN. Decreased connectivity of the right basal forebrain to brain stem and basal ganglia predicted more severe SN. Increased connectivity of the arousal and attention network regions with the parietal, frontal, and temporal structures in the unaffected hemisphere was also found in more severe delirium and SN. Conclusions: Delirium and SN are associated with decreased arousal network activity and an imbalance of cortico-subcortical hemispheric connectivity. Better understanding of neural correlates of poststroke delirium and SN will lead to improved neuroscience-based treatment development for these disorders.

scholarly journals Altered Functional Connectivity after Epileptic Seizure Revealed by Scalp EEG

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yi Liang ◽  
Chunli Chen ◽  
Fali Li ◽  
Dezhong Yao ◽  
Peng Xu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Local Area ◽  
Brain Network ◽  
Fuzzy Entropy ◽  
Clustering Coefficient ◽  
Characteristic Path Length ◽  
Functional Brain Network ◽  
Before And After

Epileptic seizures are considered to be a brain network dysfunction, and chronic recurrent seizures can cause severe brain damage. However, the functional brain network underlying recurrent epileptic seizures is still left unveiled. This study is aimed at exploring the differences in a related brain activity before and after chronic repetitive seizures by investigating the power spectral density (PSD), fuzzy entropy, and functional connectivity in epileptic patients. The PSD analysis revealed differences between the two states at local area, showing postseizure energy accumulation. Besides, the fuzzy entropies of preseizure in the frontal, central, and temporal regions are higher than that of postseizure. Additionally, attenuated long-range connectivity and enhanced local connectivity were also found. Moreover, significant correlations were found between network metrics (i.e., characteristic path length and clustering coefficient) and individual seizure number. The PSD, fuzzy entropy, and network analysis may indicate that the brain is gradually impaired along with the occurrence of epilepsy, and the accumulated effect of brain impairment is observed in individuals with consecutive epileptic bursts. The findings of this study may provide helpful insights into understanding the network mechanism underlying chronic recurrent epilepsy.

scholarly journals Mindfulness Meditation Is Related to Long-Lasting Changes in Hippocampal Functional Topology during Resting State: A Magnetoencephalography Study

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Anna Lardone ◽  
Marianna Liparoti ◽  
Pierpaolo Sorrentino ◽  
Rosaria Rucco ◽  
Francesca Jacini ◽  
...  
Keyword(s):  
Resting State ◽  
Mindfulness Meditation ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Brain Network ◽  
Long Term Effects ◽  
Age Related ◽  
Functional Topology ◽  
The Right ◽  
The Brain

It has been suggested that the practice of meditation is associated to neuroplasticity phenomena, reducing age-related brain degeneration and improving cognitive functions. Neuroimaging studies have shown that the brain connectivity changes in meditators. In the present work, we aim to describe the possible long-term effects of meditation on the brain networks. To this aim, we used magnetoencephalography to study functional resting-state brain networks in Vipassana meditators. We observed topological modifications in the brain network in meditators compared to controls. More specifically, in the theta band, the meditators showed statistically significant (p corrected = 0.009) higher degree (a centrality index that represents the number of connections incident upon a given node) in the right hippocampus as compared to controls. Taking into account the role of the hippocampus in memory processes, and in the pathophysiology of Alzheimer’s disease, meditation might have a potential role in a panel of preventive strategies.

scholarly journals Brain Network Modeling Based on Mutual Information and Graph Theory for Predicting the Connection Mechanism in the Progression of Alzheimer’s Disease

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 300 ◽  
Author(s):  
Shuaizong Si ◽  
Bin Wang ◽  
Xiao Liu ◽  
Chong Yu ◽  
Chao Ding ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Graph Theory ◽  
Mutual Information ◽  
Brain Networks ◽  
Brain Network ◽  
Network Efficiency ◽  
Characteristic Path Length ◽  
Anatomical Space ◽  
The Brain

Alzheimer’s disease (AD) is a progressive disease that causes problems of cognitive and memory functions decline. Patients with AD usually lose their ability to manage their daily life. Exploring the progression of the brain from normal controls (NC) to AD is an essential part of human research. Although connection changes have been found in the progression, the connection mechanism that drives these changes remains incompletely understood. The purpose of this study is to explore the connection changes in brain networks in the process from NC to AD, and uncovers the underlying connection mechanism that shapes the topologies of AD brain networks. In particular, we propose a mutual information brain network model (MINM) from the perspective of graph theory to achieve our aim. MINM concerns the question of estimating the connection probability between two cortical regions with the consideration of both the mutual information of their observed network topologies and their Euclidean distance in anatomical space. In addition, MINM considers establishing and deleting connections, simultaneously, during the networks modeling from the stage of NC to AD. Experiments show that MINM is sufficient to capture an impressive range of topological properties of real brain networks such as characteristic path length, network efficiency, and transitivity, and it also provides an excellent fit to the real brain networks in degree distribution compared to experiential models. Thus, we anticipate that MINM may explain the connection mechanism for the formation of the brain network organization in AD patients.

scholarly journals Approximate Entropy of Brain Network in the Study of Hemispheric Differences

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1220
Author(s):  
Francesca Alù ◽  
Francesca Miraglia ◽  
Alessandro Orticoni ◽  
Elda Judica ◽  
Maria Cotelli ◽  
...  
Keyword(s):  
Brain Networks ◽  
Approximate Entropy ◽  
Brain Network ◽  
Hemispheric Differences ◽  
Eyes Closed ◽  
Age Related ◽  
Eeg Recordings ◽  
The Right ◽  
The Impact ◽  
Adult Volunteers

Human brain, a dynamic complex system, can be studied with different approaches, including linear and nonlinear ones. One of the nonlinear approaches widely used in electroencephalographic (EEG) analyses is the entropy, the measurement of disorder in a system. The present study investigates brain networks applying approximate entropy (ApEn) measure for assessing the hemispheric EEG differences; reproducibility and stability of ApEn data across separate recording sessions were evaluated. Twenty healthy adult volunteers were submitted to eyes-closed resting EEG recordings, for 80 recordings. Significant differences in the occipital region, with higher values of entropy in the left hemisphere than in the right one, show that the hemispheres become active with different intensities according to the performed function. Besides, the present methodology proved to be reproducible and stable, when carried out on relatively brief EEG epochs but also at a 1-week distance in a group of 36 subjects. Nonlinear approaches represent an interesting probe to study the dynamics of brain networks. ApEn technique might provide more insight into the pathophysiological processes underlying age-related brain disconnection as well as for monitoring the impact of pharmacological and rehabilitation treatments.

Hemispheric Specialization and Cognitive Development: Implications for Mathematics Education

1978 ◽  
Vol 9 (1) ◽  
pp. 20-32
Author(s):  
Grayson H. Wheatley ◽  
Robert Mitchell ◽  
Robert L. Frankland ◽  
Rosemarie Kraft
Keyword(s):  
Left Hemisphere ◽  
Hemispheric Asymmetry ◽  
Right Hemisphere ◽  
Mathematics Curriculum ◽  
Hemispheric Specialization ◽  
Brain Hemispheres ◽  
Spatial Tasks ◽  
Concrete Operational ◽  
The Right ◽  
Hemisphere Specialization

Evidence is presented for hemisphere specialization of the two brain hemispheres: the left hemisphere specialized for logico-analytic tasks and the right hemisphere, visuo-spatial tasks. A hypothesis is put forth for the emergence of the specialization that suggests a shift from predominant right hemisphere processing in infancy to predominant left hemisphere processing in adulthood. Results of the studies reviewed suggest the emergence of concrete-operational thought as the left hemisphere becomes capable of processing logical tasks. Electroencephalography seems particularly useful in determining specialization and mapping changes in hemispheric asymmetry. Implications for school mathematics curriculum are presented.

Sign in / Sign up

Export Citation Format

Share Document