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Bahram Marami, Seyed Sadegh Mohseni Salehi, Onur Afacan, Benoit Scherrer, Caitlin K Rollins, Edward Yang, Judy A Estroff, Simon K Warfield, Ali Gholipour
Diffusion weighted magnetic resonance imaging, or DWI, is one of the most promising tools for the analysis of neural microstructure and the structural connectome of the human brain. The application of DWI to map early development of the human connectome in-utero, however, is challenged by intermittent fetal and maternal motion that disrupts the spatial correspondence of data acquired in the relatively long DWI acquisitions. Fetuses move continuously during DWI scans. Reliable and accurate analysis of the fetal brain structural connectome requires careful compensation of motion effects and robust reconstruction to avoid introducing bias based on the degree of fetal motion...
April 19, 2017: NeuroImage
Nicholas I Woods, Mazen A Kheirbek
How are fear memories organized? In this issue of Neuron, Vetere et al. (2017) take a network-based approach to demonstrate the importance of highly interconnected hub regions in the consolidation of a fear memory. By doing so, they provide an elegant framework for predicting behavior from functional network properties.
April 19, 2017: Neuron
Hada Fong-Ha Ieong, Zhen Yuan
Drug addiction is widely linked to the orbitofrontal cortex (OFC), which is essential for regulating reward-related behaviors, emotional responses, and anxiety. Over the past two decades, neuroimaging has provided significant contributions revealing functional and structural alternations in the brains of drug addicts. However, the underlying neural mechanism in the OFC and its correlates with drug addiction and anxiety still require further elucidation. We first presented a pilot investigation to examine local networks in OFC regions through resting-state functional connectivity (rsFC) using functional near-infrared spectroscopy (fNIRS) from eight abstinent addicts in a heroin-dependent group (HD) and seven subjects in a control group (CG)...
April 19, 2017: Scientific Reports
Shanshan Li
The Griffiths phase has been proposed to induce a stretched critical regime that facilitates self-organizing of brain networks for optimal function. This phase stems from the intrinsic structural heterogeneity of brain networks, i.e., the hierarchical modular structure. In this work, the Griffiths phase is studied in modified hierarchical networks with small-world connections based on the 3-regular Hanoi network. Through extensive simulations, the hierarchical level-dependent inter-module wiring probabilities are identified to determine the emergence of the Griffiths phase...
March 2017: Physical Review. E
Jörg Lehmann, Jakob Bernasconi
The redistribution of electrical currents in resistor networks after single-bond failures is analyzed in terms of current-redistribution factors that are shown to depend only on the topology of the network and on the values of the bond resistances. We investigate the properties of these current-redistribution factors for regular network topologies (e.g., d-dimensional hypercubic lattices) as well as for small-world networks. In particular, we find that the statistics of the current redistribution factors exhibits a fat-tail behavior, which reflects the long-range nature of the current redistribution as determined by Kirchhoff's circuit laws...
March 2017: Physical Review. E
Mehran Ahmadlou, Hojjat Adeli
In recent years complexity of the brain structure in healthy and disordered subjects has been studied increasingly. But to the best of the authors' knowledge, researchers so far have investigated the structural complexity only in the context of two restricted networks known as Small-World and Scale-free networks; whereas other aspects of the structural complexity of brain activities may be affected by aging and neurodegenerative disorders such as the Alzheimer's disease and autism spectrum disorder. In this study, two general complexity metrics of graphs, Graph Index Complexity and Offdiagonal Complexity are proposed as general measures of complexity, not restricted to SWN only...
April 13, 2017: Neuroscience Letters
Michael J Paldino, Zili D Chu, Mary L Chapieski, Farahnaz Golriz, Wei Zhang
OBJECTIVES: To measure the repeatability of metrics that quantify brain network architecture derived from resting-state fMRI (rs-fMRI) in a cohort of pediatric epilepsy patients. METHODS: We identified patients with: 1. epilepsy; 2. brain MRI at 3 Tesla; 3. two identical rs-fMRI acquisitions performed on the same day. Undirected, weighted networks were constructed based on the resting state time series using a range of processing parameters including parcellation size and graph threshold...
April 13, 2017: British Journal of Radiology
Chao Zhao, Jingchi Jiang, Zhiming Xu, Yi Guan
BACKGROUND AND OBJECTIVE: Electronic medical records (EMRs) contain an amount of medical knowledge which can be used for clinical decision support. We attempt to integrate this medical knowledge into a complex network, and then implement a diagnosis model based on this network. METHODS: The dataset of our study contains 992 records which are uniformly sampled from different departments of the hospital. In order to integrate the knowledge of these records, an EMR-based medical knowledge network (EMKN) is constructed...
May 2017: Computer Methods and Programs in Biomedicine
Xuhong Liao, Athanasios V Vasilakos, Yong He
Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance...
April 5, 2017: Neuroscience and Biobehavioral Reviews
Jaroslav Hlinka, David Hartman, Nikola Jajcay, David Tomeček, Jaroslav Tintěra, Milan Paluš
Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established...
March 2017: Chaos
Julio I Chapeton, Sara K Inati, Kareem A Zaghloul
Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing...
March 1, 2017: Brain: a Journal of Neurology
Fabrizio Parente, Marianna Frascarelli, Alessia Mirigliani, Fabio Di Fabio, Massimo Biondi, Alfredo Colosimo
The anticorrelations in fMRI measurements are still not well characterized, but some new evidences point to a possible physiological role. We explored the topology of functional brain networks characterized by negative edgess and their possible alterations in schizophrenia, using functional images of 8 healthy subjects and 8 schizophrenic patients in a resting state condition. In order to minimize the insertion of artifactual negative correlations, the preprocessing of images was carried out by the CompCorr procedure, and the results compared with the Global Signal Regression (GSR) procedure...
March 29, 2017: Brain Imaging and Behavior
Jorge Munilla, Andrés Ortiz, Juan M Górriz, Javier Ramírez
Alzheimer's Disease (AD) is the most common neurodegenerative disease in elderly people, and current drugs, unfortunately, do not represent yet a cure but only slow down its progression. This is explained, at least in part, because the understanding of the neurodegenerative process is still incomplete, being sometimes mistaken, particularly at the first steps of the illness, with the natural aging process. A better identification of how the functional activity deteriorates is thus crucial to develop new and more effective treatments...
2017: Frontiers in Neuroinformatics
Javier Gomez-Pilar, Alba Lubeiro, Jesús Poza, Roberto Hornero, Marta Ayuso, César Valcárcel, Karim Haidar, José A Blanco, Vicente Molina
OBJECTIVE: Higher mental functions depend on global cerebral functional coordination. Our aim was to study fast modulation of functional networks in schizophrenia that has not been previously assessed. METHODS: Graph-theory was used to analyze the electroencephalographic (EEG) activity during an odd-ball task in 57 schizophrenia patients (18 first episode patients, FEPs) and 59 healthy controls. Clustering coefficient (CLC), characteristic path length (PL) and small-worldness (SW) were computed at baseline ([-300 0] ms prior to stimulus delivery) and response ([150 450] ms post-stimulus) windows...
March 20, 2017: Progress in Neuro-psychopharmacology & Biological Psychiatry
Jinping Xu, Jiuquan Zhang, Jinlei Zhang, Yue Wang, Yanling Zhang, Jian Wang, Guanglin Li, Qingmao Hu, Yuanchao Zhang
Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups...
2017: Frontiers in Neuroanatomy
Dongyuan Yu, Xu Xu, Jing Zhou, Eric Li
This study considers a delayed neural network with excitatory and inhibitory shortcuts. The global stability of the trivial equilibrium is investigated based on Lyapunov's direct method and the delay-dependent criteria are obtained. It is shown that both the excitatory and inhibitory shortcuts decrease the stability interval, but a time delay can be employed as a global stabilizer. In addition, we analyze the bounds of the eigenvalues of the adjacent matrix using matrix perturbation theory and then obtain the generalized sufficient conditions for local stability...
May 2017: Neural Networks: the Official Journal of the International Neural Network Society
Manlio De Domenico, Alex Arenas
While the statistical and resilience properties of the Internet are no longer changing significantly across time, the Darknet, a network devoted to keep anonymous its traffic, still experiences rapid changes to improve the security of its users. Here we study the structure of the Darknet and find that its topology is rather peculiar, being characterized by a nonhomogeneous distribution of connections, typical of scale-free networks; very short path lengths and high clustering, typical of small-world networks; and lack of a core of highly connected nodes...
February 2017: Physical Review. E
Aaron E L Warren, A Simon Harvey, David F Abbott, Simon J Vogrin, Catherine Bailey, Andrew Davidson, Graeme D Jackson, John S Archer
We previously observed that adults with Lennox-Gastaut syndrome (LGS) show abnormal functional connectivity among cognitive networks, suggesting that this may contribute to impaired cognition. Herein we report network reorganization following seizure remission in a child with LGS who underwent functional magnetic resonance imaging (fMRI) before and after resection of a cortical dysplasia. Concurrent electroencephalography (EEG) was acquired during presurgical fMRI. Presurgical and postsurgical functional connectivity were compared using (1) graph theoretical analyses of small-world network organization and node-wise strength; and (2) seed-based analyses of connectivity within and between five functional networks...
March 11, 2017: Epilepsia
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
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