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Graph Theory

Carlos Gomez, Jesus Poza, Javier Gomez-Pilar, Alejandro Bachiller, Celia Juan-Cruz, Miguel A Tola-Arribas, Alicia Carreres, Monica Cano, Roberto Hornero
The aim of this pilot study was to analyze spontaneous electroencephalography (EEG) activity in Alzheimer's disease (AD) by means of Cross-Sample Entropy (Cross-SampEn) and two local measures derived from graph theory: clustering coefficient (CC) and characteristic path length (PL). Five minutes of EEG activity were recorded from 37 patients with dementia due to AD and 29 elderly controls. Our results showed that Cross-SampEn values were lower in the AD group than in the control one for all the interactions among EEG channels...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Nantia D Iakovidou, Manolis Christodoulakis, Eleftherios S Papathanasiou, Savvas S Papacostas, Georgios D Mitsis
The human brain has been called the most complex object in the known universe and in many ways it constitutes the final frontier of science. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using electroencephalography (EEG) signals. This means that the brain is studied as a connected system, where nodes represent different specialized brain regions and links or connections, represent communication pathways between the nodes. It is also fairly established that graph theory provides a variety of measures, methods and tools that can be useful to efficiently model, analyze and study an EEG network...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Masoumeh Sadeghi, Reza Khosrowabadi, Fatemeh Bakouie, Hoda Mahdavi, Changiz Eslahchi, Hamidreza Pouretemad
Studies on autism spectrum disorder (ASD) have indicated several dysfunctions in the structure, and functional organization of the brain. However, findings have not been established as a general diagnostic tool yet. In this regard, current study proposed an automatic screening method for recognition of ASDs from healthy controls (HCs) based on their brain functional abnormalities. In this paradigm, brain functional networks of 60 adolescent and young adult males (29 ASDs and 31 HCs) were estimated from subjects' task-free fMRI data...
March 9, 2017: Psychiatry Research
Francisco J Román, Yasser Iturria-Medina, Kenia Martínez, Sherif Karama, Miguel Burgaleta, Alan C Evans, Susanne M Jaeggi, Roberto Colom
The structural connectome provides relevant information about experience and training-related changes in the brain. Here, we used network-based statistics (NBS) and graph theoretical analyses to study structural changes in the brain as a function of cognitive training. Fifty-six young women were divided in two groups (experimental and control). We assessed their cognitive function before and after completing a working memory intervention using a comprehensive battery that included fluid and crystallized abilities, working memory and attention control, and we also obtained structural MRI images...
March 16, 2017: Neurobiology of Learning and Memory
Demetrius Ribeiro de Paula, Erik Ziegler, Pubuditha M Abeyasinghe, Tushar K Das, Carlo Cavaliere, Marco Aiello, Lizette Heine, Carol di Perri, Athena Demertzi, Quentin Noirhomme, Vanessa Charland-Verville, Audrey Vanhaudenhuyse, Johan Stender, Francisco Gomez, Jean-Flory L Tshibanda, Steven Laureys, Adrian M Owen, Andrea Soddu
INTRODUCTION: Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. OBJECTIVE: Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory...
March 2017: Brain and Behavior
Yao Han, Hong Li, Yiran Lang, Yuwei Zhao, Hongji Sun, Peng Zhang, Xuan Ma, Jiuqi Han, Qiyu Wang, Jin Zhou, Changyong Wang
γ-Aminobutyric acid (GABA) is an inhibitory transmitter, acting on receptor channels to reduce neuronal excitability in matured neural systems. However, electrophysiological responses of whole neuronal ensembles to the exposure to GABA are still unclear. We used micro-electrode arrays (MEAs) to study the effects of the increasing amount of GABA on functional network of cortical neural cultures. Then the recorded data were analyzed by the cross-covariance analysis and graph theory. Results showed that after the GABA treatment, the activity parameters of firing rate, bursting rate, bursting duration and network burst frequency in neural cultures decreased as expected...
March 13, 2017: Neurochemical Research
Yajuan Zhang, Min Li, Ruonan Wang, Yanzhi Bi, Yangding Li, Zhang Yi, Jixin Liu, Dahua Yu, Kai Yuan
Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in some specific fiber bundles in smokers. However, little is known about the changes in topological organization of WM structural network in young smokers. In current study, we acquired DTI datasets from 58 male young smokers and 51 matched nonsmokers and constructed the WM networks by the deterministic fiber tracking approach. Graph theoretical analysis was used to compare the topological parameters of WM network (global and nodal) and the inter-regional fractional anisotropy (FA) weighted WM connections between groups...
March 13, 2017: Brain Imaging and Behavior
Caiyun Wu, Jing Xiang, Wenwen Jiang, Shuyang Huang, Yuan Gao, Lu Tang, Yuchen Zhou, Di Wu, Qiqi Chen, Zheng Hu, Xiaoshan Wang
Using multi-frequency magnetoencephalography (MEG) data, we investigated whether the effective connectivity (EC) network of patients with childhood absence epilepsy (CAE) is altered during the inter-ictal period in comparison with healthy controls. MEG data from 13 untreated CAE patients and 10 healthy controls were recorded. Correlation analysis and Granger causality analysis were used to construct an EC network at the source level in eight frequency bands. Alterations in the spatial pattern and topology of the network in CAE were investigated by comparing the patients with the controls...
March 12, 2017: Brain Topography
Seyed Hani Hojjati, Ata Ebrahimzadeh, Ali Khazaee, Abbas Babajani-Feremi
BACKGROUND: We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI). NEW METHOD: Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73...
March 9, 2017: Journal of Neuroscience Methods
Antonino Naro, Antonino Leo, Alfredo Manuli, Antonino Cannavò, Alessia Bramanti, Placido Bramanti, Rocco Salvatore Calabrò
Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic Disorders of Consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC...
March 7, 2017: Neuroscience
J Castro-Medina, D García-Toral, M López-Fuentes, A Sánchez-Castillo, S Torres-Morales, L Morales de la Garza, Gregorio H Cocoletzi
First-principles total-energy calculations were performed to investigate the structural and electronic properties of thymine (T) adsorption on pristine and Al-doped two-dimensional hexagonal boron nitride (2D-hBN) surfaces. Periodic density functional theory, as developed in the PWscf code of the quantum espresso package, was applied. The pseudopotential theory was used to deal with electron-ion interactions. The generalized gradient approximation was applied to treat the exchange-correlation energies. Van der Waals interactions were incorporated in the calculations...
April 2017: Journal of Molecular Modeling
Peter V Pikhitsa, Stanislaw Pikhitsa
We provide a complete classification of possible configurations of mutually pairwise-touching infinite cylinders in Euclidian three-dimensional space. It turns out that there is a maximum number of such cylinders possible in three dimensions independently of the shape of the cylinder cross-sections. We give the explanation of the uniqueness of the non-trivial configuration of seven equal mutually touching round infinite cylinders found earlier. Some results obtained for the chirality matrix, which is equivalent to the Seidel adjacency matrix, may be found useful for the theory of graphs...
January 2017: Royal Society Open Science
Jong-Yun Park, Han Kyu Na, Sungsoo Kim, Hyunwook Kim, Hee Jin Kim, Sang Won Seo, Duk L Na, Cheol E Han, Joon-Kyung Seong
Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset...
March 9, 2017: Scientific Reports
V C Chirumamilla, V Fleischer, A Droby, T Anjum, M Muthuraman, F Zipp, S Groppa
In the present study we investigated brain network connectivity differences between patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC) as derived from functional resonance magnetic imaging (fMRI) using graph theory. Resting state fMRI data of 18 RRMS patients (12 female, mean age ± SD: 42 ± 12.06 years) and 25 HC (8 female, 29.2 ± 5.38 years) were analyzed. In order to obtain information of differences in entire brain network, we focused on both, local and global network connectivity parameters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Matteo Mancini, Giovanni Giulietti, Barbara Spano, Marco Bozzali, Mara Cercignani, Silvia Conforto
Graph-theoretical approaches have become a popular way to model brain data collected using magnetic resonance imaging (MRI), both from the structural and the functional perspectives. In structural networks, tract-based mapping allows to model different aspects of brain structures by means of the specific characteristics of the different MRI modalities. However, there has been little effort to join the information carried by each modality and to understand what level of common variance is shown in these data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
N Nader, M Hassan, W Falou, C Marque, M Khalil
The recent past years have seen a noticeable increase of interest in the correlation analysis of electrohysterographic (EHG) signals in the perspective of improving the pregnancy monitoring. Here we propose a new approach based on the functional connectivity between multichannel (4×4 matrix) EHG signals recorded from the women's abdomen. The proposed pipeline includes i) the computation of the statistical couplings between the multichannel EHG signals, ii) the characterization of the connectivity matrices, computed by using the imaginary part of the coherence, based on the graph-theory analysis and iii) the use of these measures for pregnancy monitoring...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
J Gomez-Pilar, J Poza, A Bachiller, P Nunez, C Gomez, A Lubeiro, V Molina, R Hornero
The aim of this study was to assess brain complexity dynamics in schizophrenia (SCH) patients during an auditory oddball task. For this task, we applied a novel graph measure based on the balance of the node weights distribution. Previous studies applied complexity parameters that were strongly dependent on network topology. This could bias the results, as well as making correction techniques, such as surrogating process, necessary. In the present study, we applied a novel graph complexity measure derived from the information theory: Shannon Graph Complexity (SGC)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Dan Cao, Yingjie Li, Ling Wei, Yingying Tang
Prefrontal cortex (PFC) plays an important role in the emotional processing as well as in the functional brain network. Hyperactivity in the right dorsolateral prefrontal cortex (DLPFC) would be found in anxious participants. However, it is still unclear what the role of PFC played in a resting functional network. Continuous theta burst transcranial magnetic stimulation (cTBS) is an effective tool to create virtual lesions on brain regions. In this paper, we applied cTBS over right prefrontal area, and investigated the effects of cTBS on the brain activity for functional connectivity by the method of graph theory...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Hongru Zhu, Changjian Qiu, Yajing Meng, Minlan Yuan, Yan Zhang, Zhengjia Ren, Yuchen Li, Xiaoqi Huang, Qiyong Gong, Su Lui, Wei Zhang
Recent studies involving connectome analysis including graph theory have yielded potential biomarkers for mental disorders. In this study, we aimed to investigate the differences of resting-state network between patients with social anxiety disorder (SAD) and healthy controls (HCs), as well as to distinguish between individual subjects using topological properties. In total, 42 SAD patients and the same number of HCs underwent resting functional MRI, and the topological organization of the whole-brain functional network was calculated using graph theory...
March 7, 2017: Scientific Reports
Je-Yeon Yun, Jae-Chang Kim, Jeonghun Ku, Jung-Eun Shin, Jae-Jin Kim, Soo-Hee Choi
BACKGROUND: Previous studies on patients diagnosed with social anxiety disorder (SAD) reported changed patterns of the resting-state functional connectivity network (rs-FCN) between the prefrontal cortices and other prefrontal, amygdalar or striatal regions. Using a graph theory approach, this study explored the modularity-based community profile and patterns of inter-/intra-modular communication for the rs-FCN in SAD. METHODS: In total, for 28 SAD patients and 27 healthy controls (HC), functional magnetic resonance imaging (fMRI) data were acquired in resting-state and subjected to a graph theory analysis...
March 4, 2017: Journal of Affective Disorders
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