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https://www.readbyqxmd.com/read/28705239/nap-the-network-analysis-profiler-a-web-tool-for-easier-topological-analysis-and-comparison-of-medium-scale-biological-networks
#1
Theodosios Theodosiou, Georgios Efstathiou, Nikolas Papanikolaou, Nikos C Kyrpides, Pantelis G Bagos, Ioannis Iliopoulos, Georgios A Pavlopoulos
OBJECTIVE: Nowadays, due to the technological advances of high-throughput techniques, Systems Biology has seen a tremendous growth of data generation. With network analysis, looking at biological systems at a higher level in order to better understand a system, its topology and the relationships between its components is of a great importance. Gene expression, signal transduction, protein/chemical interactions, biomedical literature co-occurrences, are few of the examples captured in biological network representations where nodes represent certain bioentities and edges represent the connections between them...
July 14, 2017: BMC Research Notes
https://www.readbyqxmd.com/read/28695358/retained-executive-abilities-in-mild-cognitive-impairment-are-associated-with-increased-white-matter-network-connectivity
#2
Danielle C Farrar, Asim Z Mian, Andrew E Budson, Mark B Moss, Bang Bon Koo, Ronald J Killiany
PURPOSE: To describe structural network differences in individuals with mild cognitive impairment (MCI) with high versus low executive abilities, as reflected by measures of white matter connectivity using diffusion tensor imaging (DTI). MATERIALS AND METHODS: This was a retrospective, cross-sectional study. Of the 128 participants from the Alzheimer's Disease Neuroimaging Initiative database who had both a DTI scan as well as a diagnosis of MCI, we used an executive function score to classify the top 15 scoring patients as high executive ability, and the bottom-scoring 16 patients as low executive ability...
July 10, 2017: European Radiology
https://www.readbyqxmd.com/read/28675389/topologically-convergent-and-divergent-functional-connectivity-patterns-in-unmedicated-unipolar-depression-and-bipolar-disorder
#3
Y Wang, J Wang, Y Jia, S Zhong, M Zhong, Y Sun, M Niu, L Zhao, L Zhao, J Pan, L Huang, R Huang
Bipolar disorder (BD), particularly BD II, is frequently misdiagnosed as unipolar depression (UD), leading to inappropriate treatment and poor clinical outcomes. Although depressive symptoms may be expressed similarly in UD and BD, the similarities and differences in the architecture of brain functional networks between the two disorders are still unknown. In this study, we hypothesized that UD and BD II patients would show convergent and divergent patterns of disrupted topological organization of the functional connectome, especially in the default mode network (DMN) and the limbic network...
July 4, 2017: Translational Psychiatry
https://www.readbyqxmd.com/read/28667481/disrupted-topological-organization-of-brain-structural-network-associated-with-prior-overt-hepatic-encephalopathy-in-cirrhotic-patients
#4
Hua-Jun Chen, Hai-Bin Shi, Long-Feng Jiang, Lan Li, Rong Chen
OBJECTIVES: To investigate structural brain connectome alterations in cirrhotic patients with prior overt hepatic encephalopathy (OHE). METHODS: Seventeen cirrhotic patients with prior OHE (prior-OHE), 18 cirrhotic patients without prior OHE (non-prior-OHE) and 18 healthy controls (HC) underwent diffusion tensor imaging. Neurocognitive functioning was assessed with Psychometric Hepatic Encephalopathy Score (PHES). Using a probabilistic fibre tracking approach, we depicted the whole-brain structural network as a connectivity matrix of 90 regions (derived from the Automated Anatomic Labeling atlas)...
June 30, 2017: European Radiology
https://www.readbyqxmd.com/read/28666351/brain-networks-predict-metabolism-diagnosis-and-prognosis-at-the-bedside-in-disorders-of-consciousness
#5
Srivas Chennu, Jitka Annen, Sarah Wannez, Aurore Thibaut, Camille Chatelle, Helena Cassol, Géraldine Martens, Caroline Schnakers, Olivia Gosseries, David Menon, Steven Laureys
Recent advances in functional neuroimaging have demonstrated novel potential for informing diagnosis and prognosis in the unresponsive wakeful syndrome and minimally conscious states. However, these technologies come with considerable expense and difficulty, limiting the possibility of wider clinical application in patients. Here, we show that high density electroencephalography, collected from 104 patients measured at rest, can provide valuable information about brain connectivity that correlates with behaviour and functional neuroimaging...
June 27, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28657774/integrative-structural-brain-network-analysis-in-diffusion-tensor-imaging
#6
Moo K Chung, Jamie L Hanson, Nagesh Adluru, Andrew L Alexander, Richard J Davidson, Seth D Pollak
In diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length, and FA values into the connectivity model. Using various node-degree-based graph theory features, the three connectivity models are compared...
June 28, 2017: Brain Connectivity
https://www.readbyqxmd.com/read/28657334/large-scale-network-analysis-of-whole-brain-resting-state-functional-connectivity-in-spinal-cord-injury-a-comparative-study
#7
Mayank Kaushal, Akinwunmi Oni-Orisan, Gang Chen, Wenjun Li, Jack Leschke, Doug Ward, Benjamin Kalinosky, Matthew Budde, Brain Schmit, Shi-Jiang Li, Vaishnavi Muqeet, Shekar Kurpad
BACKGROUND: Network analysis based on graph theory depicts the brain as a complex network that allows for inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. OBJECTIVE: To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects...
June 28, 2017: Brain Connectivity
https://www.readbyqxmd.com/read/28645844/modeling-and-interpreting-mesoscale-network-dynamics
#8
REVIEW
Ankit N Khambhati, Ann E Sizemore, Richard F Betzel, Danielle S Bassett
Recent advances in brain imaging techniques, measurement approaches, and storage capacities have provided an unprecedented supply of high temporal resolution neural data. These data present a remarkable opportunity to gain a mechanistic understanding not just of circuit structure, but also of circuit dynamics, and its role in cognition and disease. Such understanding necessitates a description of the raw observations, and a delineation of computational models and mathematical theories that accurately capture fundamental principles behind the observations...
June 20, 2017: NeuroImage
https://www.readbyqxmd.com/read/28635541/association-between-abnormal-brain-functional-connectivity-in-children-and-psychopathology-a-study-based-on-graph-theory-and-machine-learning
#9
João Ricardo Sato, Claudinei Eduardo Biazoli, Giovanni Abrahão Salum, Ary Gadelha, Nicolas Crossley, Gilson Vieira, André Zugman, Felipe Almeida Picon, Pedro Mario Pan, Marcelo Queiroz Hoexter, Edson Amaro, Mauricio Anés, Luciana Monteiro Moura, Marco Antonio Gomes Del'Aquilla, Philip Mcguire, Luis Augusto Rohde, Euripedes Constantino Miguel, Andrea Parolin Jackowski, Rodrigo Affonseca Bressan
OBJECTIVES: One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a novel method for assessing brain networks based on the combination of a graph theory measure (eigenvector centrality) and a one-class support vector machine (OC-SVM). METHODS: We applied this approach to resting-state fMRI data from 622 children and adolescents...
February 8, 2017: World Journal of Biological Psychiatry
https://www.readbyqxmd.com/read/28633299/structural-covariance-networks-in-children-with-autism-or-adhd
#10
R A I Bethlehem, R Romero-Garcia, E Mak, E T Bullmore, S Baron-Cohen
Background: While autism and attention-deficit/hyperactivity disorder (ADHD) are considered distinct conditions from a diagnostic perspective, clinically they share some phenotypic features and have high comorbidity. Regardless, most studies have focused on only one condition, with considerable heterogeneity in their results. Taking a dual-condition approach might help elucidate shared and distinct neural characteristics. Method: Graph theory was used to analyse topological properties of structural covariance networks across both conditions and relative to a neurotypical (NT; n = 87) group using data from the ABIDE (autism; n = 62) and ADHD-200 datasets (ADHD; n = 69)...
June 13, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28622528/band-specific-atypical-functional-connectivity-pattern-in-childhood-autism-spectrum-disorder
#11
Tetsuya Takahashi, Teruya Yamanishi, Sou Nobukawa, Shinya Kasakawa, Yuko Yoshimura, Hirotoshi Hiraishi, Chiaki Hasegawa, Takashi Ikeda, Tetsu Hirosawa, Toshio Munesue, Haruhiro Higashida, Yoshio Minabe, Mitsuru Kikuchi
OBJECTIVE: Altered brain connectivity has been theorized as a key neural underpinning of autism spectrum disorder (ASD), but recent investigations have revealed conflicting patterns of connectivity, particularly hyper-connectivity and hypo-connectivity across age groups. The application of graph theory to neuroimaging data has become an effective approach for characterizing topographical patterns of large-scale functional networks. We used a graph approach to investigate alteration of functional networks in childhood ASD...
May 23, 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28620239/shared-and-specific-intrinsic-functional-connectivity-patterns-in-unmedicated-bipolar-disorder-and-major-depressive-disorder
#12
Ying Wang, Junjing Wang, Yanbin Jia, Shuming Zhong, Meiqi Niu, Yao Sun, Zhangzhang Qi, Ling Zhao, Li Huang, Ruiwang Huang
Identifying brain differences and similarities between bipolar disorder (BD) and major depressive disorder (MDD) is necessary for increasing our understanding of the pathophysiology and for developing more effective treatments. However, the features of whole-brain intrinsic functional connectivity underlying BD and MDD have not been directly compared. We collected resting-state fMRI data from 48 BD patients, 48 MDD patients, and 51 healthy subjects. We constructed voxel-wise whole-brain functional networks and computed regional functional connectivity strength (FCS) using graph-theory and further divided the regional FCS into long-range FCS (lFCS) and short-range FCS (sFCS)...
June 15, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28618557/scale-free-networks-emerging-from-multifractal-time-series
#13
Marcello A Budroni, Andrea Baronchelli, Romualdo Pastor-Satorras
Methods connecting dynamical systems and graph theory have attracted increasing interest in the past few years, with applications ranging from a detailed comparison of different kinds of dynamics to the characterization of empirical data. Here we investigate the effects of the (multi)fractal properties of a signal, common in time series arising from chaotic dynamics or strange attractors, on the topology of a suitably projected network. Relying on the box-counting formalism, we map boxes into the nodes of a network and establish analytic expressions connecting the natural measure of a box with its degree in the graph representation...
May 2017: Physical Review. E
https://www.readbyqxmd.com/read/28618512/cavity-master-equation-for-the-continuous-time-dynamics-of-discrete-spin-models
#14
E Aurell, G Del Ferraro, E Domínguez, R Mulet
We present an alternate method to close the master equation representing the continuous time dynamics of interacting Ising spins. The method makes use of the theory of random point processes to derive a master equation for local conditional probabilities. We analytically test our solution studying two known cases, the dynamics of the mean-field ferromagnet and the dynamics of the one-dimensional Ising system. We present numerical results comparing our predictions with Monte Carlo simulations in three different models on random graphs with finite connectivity: the Ising ferromagnet, the random field Ising model, and the Viana-Bray spin-glass model...
May 2017: Physical Review. E
https://www.readbyqxmd.com/read/28617222/an-extensive-assessment-of-network-alignment-algorithms-for-comparison-of-brain-connectomes
#15
Marianna Milano, Pietro Hiram Guzzi, Olga Tymofieva, Duan Xu, Christofer Hess, Pierangelo Veltri, Mario Cannataro
BACKGROUND: Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation...
June 6, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28612393/network-theory-and-metapopulation-persistence-incorporating-node-self-connections
#16
Jessica Zamborain-Mason, Garry R Russ, Rene A Abesamis, Abner A Bucol, Sean R Connolly
Network analysis is gaining increasing importance in conservation planning. However, which network metrics are the best predictors of metapopulation persistence is still unresolved. Here, we identify a critical limitation of graph theory-derived network metrics that have been proposed for this purpose: their omission of node self-connections. We resolve this by presenting modifications of existing network metrics, and developing entirely new metrics, that account for node self-connections. Then, we illustrate the performance of these new and modified metrics with an age-structured metapopulation model for a real-world marine reserve network case study, and we evaluate the robustness of our findings by systematically varying particular features of that network...
July 2017: Ecology Letters
https://www.readbyqxmd.com/read/28607055/brain-circuit-gene-expression-relationships-and-neuroplasticity-of-multisensory-cortices-in-blind-children
#17
Laura Ortiz-Terán, Ibai Diez, Tomás Ortiz, David L Perez, Jose Ignacio Aragón, Victor Costumero, Alvaro Pascual-Leone, Georges El Fakhri, Jorge Sepulcre
Sensory deprivation reorganizes neurocircuits in the human brain. The biological basis of such neuroplastic adaptations remains elusive. In this study, we applied two complementary graph theory-based functional connectivity analyses, one to evaluate whole-brain functional connectivity relationships and the second to specifically delineate distributed network connectivity profiles downstream of primary sensory cortices, to investigate neural reorganization in blind children compared with sighted controls. We also examined the relationship between connectivity changes and neuroplasticity-related gene expression profiles in the cerebral cortex...
June 27, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28602817/on-memories-neural-ensembles-and-mental-flexibility
#18
Dimitris A Pinotsis, Scott L Brincat, Earl K Miller
Memories are assumed to be represented by groups of co-activated neurons, called neural ensembles. Describing ensembles is a challenge: complexity of the underlying micro-circuitry is immense. Current approaches use a piecemeal fashion, focusing on single neurons and employing local measures like pairwise correlations. We introduce an alternative approach that identifies ensembles and describes the effective connectivity between them in a holistic fashion. It also links the oscillatory frequencies observed in ensembles with the spatial scales at which activity is expressed...
June 9, 2017: NeuroImage
https://www.readbyqxmd.com/read/28575716/structural-network-connectivity-impairment-and-depressive-symptoms-in-cerebral-small-vessel-disease
#19
Xiaofeng Xie, Yulu Shi, Junjian Zhang
BACKGROUND: Cerebral small vessel disease (SVD) can disrupt mood regulation circuits and cause depressive symptoms which may occur prior to onset of other symptoms. However, the topological network alterations in SVD with depressive symptoms remained unclear. We aim to investigate how these changes in structural network were related to depressive symptoms in SVD. METHODS: We recruited 20 SVD with depressive symptoms (SVD+D), 20 SVD without depressive symptoms (SVD-D) and 16 healthy control (HC) individuals...
October 1, 2017: Journal of Affective Disorders
https://www.readbyqxmd.com/read/28573962/anatomical-integration-and-rich-club-connectivity-in-euthymic-bipolar-disorder
#20
S O'Donoghue, L Kilmartin, D O'Hora, L Emsell, C Langan, S McInerney, N J Forde, A Leemans, B Jeurissen, G J Barker, P McCarthy, D M Cannon, C McDonald
BACKGROUND: Although repeatedly associated with white matter microstructural alterations, bipolar disorder (BD) has been relatively unexplored using complex network analysis. This method combines structural and diffusion magnetic resonance imaging (MRI) to model the brain as a network and evaluate its topological properties. A group of highly interconnected high-density structures, termed the 'rich-club', represents an important network for integration of brain functioning. This study aimed to assess structural and rich-club connectivity properties in BD through graph theory analyses...
July 2017: Psychological Medicine
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