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Hemispheric asymmetry of electroencephalography-based functional brain networks
, Article NeuroReport ; Volume 25, Issue 16 , 12 November , 2014 , Pages 1266-1271 ; ISSN: 09594965 ; Sharif University of Technology
Abstract
Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically...
EEG-based functional brain networks: Hemispheric differences in males and females
, Article Networks and Heterogeneous Media ; Volume 10, Issue 1 , March , 2015 , Pages 223-232 ; 15561801 (ISSN) ; Sharif University of Technology
American Institute of Mathematical Sciences
2015
Abstract
Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks whose nodes are brain regions and edges correspond to functional links between them are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using...
Analyzing Directed Functional Brain Networks Based On Electroencephalogram Data
, M.Sc. Thesis Sharif University of Technology ; Rabiei, Hamid Reza (Supervisor)
Abstract
Over the past few years, various studies have demonstrated that the complex networks can be used to model the structure and functions of human brain. Some of these studies indi- cated that diseases such as Alzheimer, Epilepsy, and Schizophrenia can cause changes in this network. The main idea behind the methods proposed to analyze human brain’s behav- ior, is to identify regions of the brain with specific tasks. Recent studies show that multiple regions of human brain are involved in complex activities, so it’s important to detect their interactions. Using functional high resolution multichannel neurophysiological signals, like electroencephalographic (EEG) and magnetoencephalographic...
Directed functional networks in Alzheimer's disease: disruption of global and local connectivity measures
, Article IEEE Journal of Biomedical and Health Informatics ; Volume 21, Issue 4 , 2017 , Pages 949-955 ; 21682194 (ISSN) ; Jalili, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
Techniques available in graph theory can be applied to signals recorded from human brain. In network analysis of EEG signals, the individual nodes are EEG sensor locations and the edges correspond to functional relations between them that are extracted from EEG time series. In this paper, we study EEG-based directed functional networks in Alzheimer's disease (AD). To this end, directed connectivity matrices of 25 AD patients and 26 healthy subjects are processed and a number of meaningful graph theory metrics are studied. Our data show that functional networks of AD brains have significantly reduced global connectivity in alpha and beta bands (P < 0.05). The AD brains have significantly...