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Graph Theory

Michael F Regner, Naomi Saenz, Keeran Maharajh, Dorothy J Yamamoto, Brianne Mohl, Korey Wylie, Jason Tregellas, Jody Tanabe
OBJECTIVE: We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. METHODS: 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI...
2016: PloS One
Luca Santini, Santiago Saura, Carlo Rondinini
One of the biggest challenges in large-scale conservation is quantifying connectivity at broad geographic scales and for a large set of species. Because connectivity analyses can be computationally intensive, and the planning process quite complex when multiple taxa are involved, assessing connectivity at large spatial extents for many species turns to be often intractable. Such limitation results in that conducted assessments are often partial by focusing on a few key species only, or are generic by considering a range of dispersal distances and a fixed set of areas to connect that are not directly linked to the actual spatial distribution or mobility of particular species...
2016: PloS One
Chinglin Wu, Suyu Zhong, Hsuehchih Chen
Remote association is a core ability that influences creative output. In contrast to close association, remote association is commonly agreed to be connected with more original and unique concepts. However, although existing studies have discovered that creativity is closely related to the white-matter structure of the brain, there are no studies that examine the relevance between the connectivity efficiencies and creativity of the brain regions from the perspective of networks. Consequently, this study constructed a brain white matter network structure that consisted of cerebral tissues and nerve fibers and used graph theory to analyze the connection efficiencies among the network nodes, further illuminating the differences between remote and close association in relation to the connectivity of the brain network...
2016: PloS One
Annerine Roos, Jean-Paul Fouche, Dan J Stein
Evidence suggests that women who suffer from intimate partner violence (IPV) and posttraumatic stress disorder (PTSD) have structural and functional alterations in specific brain regions. Yet, little is known about how brain connectivity may be altered in individuals with IPV, but without PTSD. Women exposed to IPV (n = 18) and healthy controls (n = 18) underwent structural brain imaging using a Siemens 3T MRI. Global and regional brain network connectivity measures were determined, using graph theory analyses...
October 18, 2016: Brain Imaging and Behavior
Lin Li, Mary Cazzell, Olajide Babawale, Hanli Liu
Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain...
October 2016: Neurophotonics
Wenqing Fu, Sharon R Browning, Brian L Browning, Joshua M Akey
Identifying and characterizing genomic regions that are shared identical by descent (IBD) among individuals can yield insight into population history, facilitate the identification of adaptively evolving loci, and be an important tool in disease gene mapping. Although increasingly large collections of exome sequences have been generated, it is challenging to detect IBD segments in exomes, precluding many potentially informative downstream analyses. Here, we describe an approach, ExIBD, to robustly detect IBD segments in exome-sequencing data, rigorously evaluate its performance, and apply this method to high-coverage exomes from 6,515 European and African Americans...
October 6, 2016: American Journal of Human Genetics
Michelle N Servaas, Linda Geerligs, Jojanneke A Bastiaansen, Remco J Renken, Jan-Bernard C Marsman, Ilja M Nolte, Johan Ormel, André Aleman, Harriëtte Riese
Neuroticism and genetic variation in the serotonin-transporter (SLC6A4) and catechol-O-methyltransferase (COMT) gene are risk factors for psychopathology. Alterations in the functional integration and segregation of neural circuits have recently been found in individuals scoring higher on neuroticism. The aim of the current study was to investigate how genetic risk factors impact functional network organization and whether genetic risk factors moderate the association between neuroticism and functional network organization...
October 14, 2016: Brain Imaging and Behavior
Bethany Lusch, Pedro D Maia, J Nathan Kutz
Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure...
September 2016: Physical Review. E
Yang Yang, Filippo Radicchi
We consider the observability model in networks with arbitrary topologies. We introduce a system of coupled nonlinear equations, valid under the locally treelike ansatz, to describe the size of the largest observable cluster as a function of the fraction of directly observable nodes present in the network. We perform a systematic analysis on 95 real-world graphs and compare our theoretical predictions with numerical simulations of the observability model. Our method provides almost perfect predictions in the majority of the cases, even for networks with very large values of the clustering coefficient...
September 2016: Physical Review. E
Sophie Lèbre, Olivier Gascuel
Overlapping genes exist in all domains of life and are much more abundant than expected upon their first discovery in the late 1970s. Assuming that the reference gene is read in frame +0, an overlapping gene can be encoded in two reading frames in the sense strand, denoted by +1 and +2, and in three reading frames in the opposite strand, denoted by -0, -1, and -2. This motivated numerous researchers to study the constraints induced by the genetic code on the various overlapping frames, mostly based on information theory...
October 10, 2016: Journal of Theoretical Biology
Jeffrey R Wozniak, Bryon A Mueller, Sarah N Mattson, Claire D Coles, Julie A Kable, Kenneth L Jones, Christopher J Boys, Kelvin O Lim, Edward P Riley, Elizabeth R Sowell
: Consistent with well-documented structural and microstructural abnormalities in prenatal alcohol exposure (PAE), recent studies suggest that functional connectivity (FC) may also be disrupted. We evaluated whole-brain FC in a large multi-site sample, examined its cognitive correlates, and explored its potential to objectively identify neurodevelopmental abnormality in individuals without definitive dysmorphic features. Included were 75 children with PAE and 68 controls from four sites...
October 12, 2016: Brain Imaging and Behavior
Qingbao Yu, Lei Wu, David A Bridwell, Erik B Erhardt, Yuhui Du, Hao He, Jiayu Chen, Peng Liu, Jing Sui, Godfrey Pearlson, Vince D Calhoun
The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA)...
2016: Frontiers in Human Neuroscience
Johannes Textor, Judith N Mandl, Rob J de Boer
Lymph nodes are meeting points for circulating immune cells. A network of reticular cells that ensheathe a mesh of collagen fibers crisscrosses the tissue in each lymph node. This reticular cell network distributes key molecules and provides a structure for immune cells to move around on. During infections, the network can suffer damage. A new study has now investigated the network's structure in detail, using methods from graph theory. The study showed that the network is remarkably robust to damage: it can still support immune responses even when half of the reticular cells are destroyed...
October 2016: PLoS Biology
Yutaka Shimada, Yoshito Hirata, Tohru Ikeguchi, Kazuyuki Aihara
Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems...
October 11, 2016: Scientific Reports
Octavian V Lie, Pieter van Mierlo
The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (<60)...
October 8, 2016: Brain Topography
Weihong Yuan, Artur Meller, Joshua S Shimony, Tiffany Nash, Blaise V Jones, Scott K Holland, Mekibib Altaye, Holly Barnard, Jannel Phillips, Stephanie Powell, Robert C McKinstry, David D Limbrick, Akila Rajagopal, Francesco T Mangano
Neuroimaging research in surgically treated pediatric hydrocephalus patients remains challenging due to the artifact caused by programmable shunt. Our previous study has demonstrated significant alterations in the whole brain white matter structural connectivity based on diffusion tensor imaging (DTI) and graph theoretical analysis in children with hydrocephalus prior to surgery or in surgically treated children without programmable shunts. This study seeks to investigate the impact of brain injury on the topological features in the left hemisphere, contratelateral to the shunt placement, which will avoid the influence of shunt artifacts and makes further group comparisons feasible for children with programmable shunt valves...
2016: NeuroImage: Clinical
Elijah Mak, Sean J Colloby, Alan Thomas, John T O'Brien
Late-life depression (LLD) has been associated with both generalized and focal neuroanatomical changes including gray matter atrophy and white matter abnormalities. However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks remains to be established. In this multimodal study, we first examined cortical thickness, and applied graph theory to investigate structural covariance networks in LLD. Thirty-three subjects with LLD and 25 controls underwent T1-weighted, fluid-attenuated inversion recovery and clinical assessments...
August 24, 2016: Neurobiology of Aging
John P Hegarty, Bradley J Ferguson, Rachel M Zamzow, Landon J Rohowetz, Jeffrey D Johnson, Shawn E Christ, David Q Beversdorf
The beta-adrenergic antagonist propranolol benefits some social and communication domains affected in autism spectrum disorder (ASD), and these benefits appear to be associated with increased functional connectivity (FC) in the brain during task performance. FC is implicated in ASD, with the majority of studies suggesting long distance hypo-connectivity combined with regionally specific local hyper-connectivity. The objective in the current investigation was to examine the effect of propranolol on FC at rest and determine whether ASD-specific effects exist...
October 6, 2016: Brain Imaging and Behavior
Yuval Kalish, Gil Luria
Research into leadership emergence typically focuses on the attributes of the emergent leader. By considering also the attributes of perceivers and the passage of time, we develop a more complete theory of leadership emergence in short-lived groups. Using expectation states theory as an overarching theoretical framework, and integrating it with the surface- and deep-level diversity literature and with theories of self-serving biases, we examine the predictors of leadership emergence in short timeframes. We conduct a field study in a military assessment boot camp (a pilot study, n = 60; and a main study, n = 89)...
October 2016: Journal of Applied Psychology
Nurit Haspel, Filip Jagodzinski
In proteins, certain amino acids may play a critical role in determining their structure and function. Examples include flexible regions, which allow domain motions, and highly conserved residues on functional interfaces, which play a role in binding and interaction with other proteins. Detecting these regions facilitates the analysis and simulation of protein rigidity and conformational changes, and aids in characterizing protein-protein binding. We present a protocol that combines graph-theory rigidity analysis and machine-learning-based methods for predicting critical residues in proteins...
2017: Methods in Molecular Biology
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