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Fabrizio Vecchio, Riccardo Di Iorio, Francesca Miraglia, Giuseppe Granata, Roberto Romanello, Placido Bramanti, Paolo Maria Rossini
Transcranial direct current stimulation (tDCS) is a non-invasive technique able to modulate cortical excitability in a polarity-dependent way. At present, only few studies investigated the effects of tDCS on the modulation of functional connectivity between remote cortical areas. The aim of this study was to investigate-through graph theory analysis-how bipolar tDCS modulate cortical networks high-density EEG recordings were acquired before and after bipolar cathodal, anodal and sham tDCS involving the primary motor and pre-motor cortices of the dominant hemispherein 14 healthy subjects...
February 13, 2018: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
Chris G Antonopoulos, Yilun Shang
We study opinion dynamics over multiplex networks where agents interact with bounded confidence. Namely, two neighbouring individuals exchange opinions and compromise if their opinions do not differ by more than a given threshold. In literature, agents are generally assumed to have a homogeneous confidence bound. Here, we study analytically and numerically opinion evolution over structured networks characterised by multiple layers with respective confidence thresholds and general initial opinion distributions...
February 12, 2018: Scientific Reports
Yan Zhu, Dongqing Wang, Zhe Liu, Yuefeng Li
BACKGROUND: Neuroimaging studies have shown that major depressive disorder is associated with altered activity patterns of the default-mode network (DMN). In this study, we sought to investigate the topological organization of the DMN in patients with remitted geriatric depression (RGD) and whether RGD patients would be more likely to show disrupted topological configuration of the DMN during the resting-state. METHODS: Thirty-three RGD patients and thirty-one healthy control participants underwent clinical and cognitive evaluations as well as resting-state functional magnetic resonance imaging scans...
February 12, 2018: International Psychogeriatrics
Yong Kheng Goh, Haslifah M Hasim, Chris G Antonopoulos
In this paper, we study data from financial markets, using the normalised Mutual Information Rate. We show how to use it to infer the underlying network structure of interrelations in the foreign currency exchange rates and stock indices of 15 currency areas. We first present the mathematical method and discuss its computational aspects, and apply it to artificial data from chaotic dynamics and to correlated normal-variates data. We then apply the method to infer the structure of the financial system from the time-series of currency exchange rates and stock indices...
2018: PloS One
Haixiao Du, Mingrui Xia, Kang Zhao, Xuhong Liao, Huazhong Yang, Yu Wang, Yong He
The recent collection of unprecedented quantities of neuroimaging data with high spatial resolution has led to brain network big data. However, a toolkit for fast and scalable computational solutions is still lacking. Here, we developed the PArallel Graph-theoretical ANalysIs (PAGANI) Toolkit based on a hybrid central processing unit-graphics processing unit (CPU-GPU) framework with a graphical user interface to facilitate the mapping and characterization of high-resolution brain networks. Specifically, the toolkit provides flexible parameters for users to customize computations of graph metrics in brain network analyses...
February 7, 2018: Human Brain Mapping
Anusha Mohan, Sandra Jovanovic Alexandra, Cliff V Johnson, Dirk De Ridder, Sven Vanneste
Distress is a domain-general behavioral symptom whose neural correlates have been under investigation for a long time now. Although some studies suggest that distress is encoded by changes in alpha activity and functional connectivity between specific brain regions, no study that we know has delved into the whole brain temporal dynamics of the distress component. In the current study, we compare the changes in the mean and variance of functional connectivity and small-worldness parameter over 3 min of resting state EEG to analyze the fluctuation in transient stable states, and network structure...
February 1, 2018: Progress in Neuro-psychopharmacology & Biological Psychiatry
Stefan Koelsch, Stavros Skouras, Gabriele Lohmann
Sound is a potent elicitor of emotions. Auditory core, belt and parabelt regions have anatomical connections to a large array of limbic and paralimbic structures which are involved in the generation of affective activity. However, little is known about the functional role of auditory cortical regions in emotion processing. Using functional magnetic resonance imaging and music stimuli that evoke joy or fear, our study reveals that anterior and posterior regions of auditory association cortex have emotion-characteristic functional connectivity with limbic/paralimbic (insula, cingulate cortex, and striatum), somatosensory, visual, motor-related, and attentional structures...
2018: PloS One
Alireza Saeedi, Mostafa Jannesari, Shahriar Gharibzadeh, Fatemeh Bakouie
Self-organized criticality (SOC) and stochastic oscillations (SOs) are two theoretically contradictory phenomena that are suggested to coexist in the brain. Recently it has been shown that an accumulation-release process like sandpile dynamics can generate SOC and SOs simultaneously. We considered the effect of the network structure on this coexistence and showed that the sandpile dynamics on a small-world network can produce two power law regimes along with two groups of SOs-two peaks in the power spectrum of the generated signal simultaneously...
January 30, 2018: Neural Computation
Tiancheng Xu, Shiyuan Li, Xianhong Xu, Mengye Lu, Jingxin Zhang, Wenyuan Sun, Hongxin Zhang, Siyuan Song, Jiyu Gu, Jianhua Sun
Meridian theory plays an important role in the guidance of clinical practice of acupuncture and moxibustion. Since the publication of Zhenjiu Jiayi Jing (A-B Classic of Acupuncture and Moxibustion), the meridian theory has been developed. In the paper, in view of complex science, the topological properties of acupoint-symptom network were analyzed quantitatively by taking acupoint as node and indication as the connection, such as high clustering coefficient and the small world effect. It was the first time to give the abstraction for the topological proof of the high efficiency information transmission property of acupoint-symptom network meridian system at different times...
November 12, 2017: Zhongguo Zhen Jiu, Chinese Acupuncture & Moxibustion
Jeong-Hyeon Shin, Yu Hyun Um, Chang Uk Lee, Hyun Kook Lim, Joon-Kyung Seong
BACKGROUND: Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. METHODS: In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients...
January 5, 2018: Journal of Affective Disorders
Jonas Grimm, Maxim Dolgushev
We investigate the dynamics of fractals and other networks in a viscoelastic and active environment. The viscoelastic dynamics is modeled based on the generalized Langevin equation, where the activity is introduced to it by means of the exponentially correlated noise. The intramolecular interactions are taken into account by the bead-spring picture. The microscopic connectivity (studied in the form of Vicsek fractals, of dual Sierpiński gaskets, of NTD trees, and of a family of deterministic small-world networks) reveals itself in the multiscale monomeric dynamics, which shows vastly different behaviors in the active and passive baths...
January 19, 2018: Soft Matter
Bryan Iotti, Alberto Antonioni, Seth Bullock, Christian Darabos, Marco Tomassini, Mario Giacobini
The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks...
November 2017: Physical Review. E
Srilena Kundu, Soumen Majhi, Sourav Kumar Sasmal, Dibakar Ghosh, Biswambhar Rakshit
A metapopulation structure in landscape ecology comprises a group of interacting spatially separated subpopulations or patches of the same species that may experience several local extinctions. This makes the investigation of survivability (in the form of global oscillation) of a metapopulation on top of diverse dispersal topologies extremely crucial. However, among various dispersal topologies in ecological networks, which one can provide higher metapopulation survivability under local extinction is still not well explored...
December 2017: Physical Review. E
R C Budzinski, B R R Boaretto, T L Prado, S R Lopes
We study the stability of asymptotic states displayed by a complex neural network. We focus on the loss of stability of a stationary state of networks using recurrence quantifiers as tools to diagnose local and global stabilities as well as the multistability of a coupled neural network. Numerical simulations of a neural network composed of 1024 neurons in a small-world connection scheme are performed using the model of Braun et al. [Int. J. Bifurcation Chaos 08, 881 (1998)IJBEE40218-127410.1142/S0218127498000681], which is a modified model from the Hodgkin-Huxley model [J...
July 2017: Physical Review. E
Chanania Steinbock, Ofer Biham, Eytan Katzav
We present analytical results for the distribution of shortest path lengths (DSPL) in a network growth model which evolves by node duplication (ND). The model captures essential properties of the structure and growth dynamics of social networks, acquaintance networks, and scientific citation networks, where duplication mechanisms play a major role. Starting from an initial seed network, at each time step a random node, referred to as a mother node, is selected for duplication. Its daughter node is added to the network, forming a link to the mother node, and with probability p to each one of its neighbors...
September 2017: Physical Review. E
K M Park, B I Lee, K J Shin, S Y Ha, J Park, T H Kim, C W Mun, S E Kim
OBJECTIVE: Increasing evidence has suggested that epilepsy is a network disease. Graph theory is a mathematical tool that allows for the analysis and quantification of the brain network. We aimed to evaluate the influences of duration of epilepsy on the topological organization of brain network in focal epilepsy patients with normal MRI using the graph theoretical analysis based on diffusion tenor imaging. METHODS: We prospectively enrolled 66 patients with focal epilepsy (18/66 patients were newly diagnosed) and 84 healthy subjects...
January 17, 2018: Acta Neurologica Scandinavica
Jiehui Jiang, Hucheng Zhou, Huoqiang Duan, Xin Liu, Chuantao Zuo, Zhemin Huang, Zhihua Yu, Zhuangzhi Yan
Mapping the human brain is one of the great scientific challenges of the 21st century. Brain network analysis is an effective technique based on graph theory that is widely used to investigate network patterns in the human brain. Currently, mapping an individual brain network using a single image has been a hotspot in the field of brain science; techniques, such as the Kullback-Leibler (KL) method, have applications in structural Magnetic Resonance (MR) imaging. However, maintaining an image's intensity, shape, texture and gradient information during feature extraction is very challenging...
December 2017: Heliyon
Qianqian Meng, Yu Han, Gang Ji, Guanya Li, Yang Hu, Li Liu, Qingchao Jin, Karen M von Deneen, Jizheng Zhao, Guangbin Cui, Huaning Wang, Dardo Tomasi, Nora D Volkow, Jixin Liu, Yongzhan Nie, Yi Zhang, Gene-Jack Wang
Neuroimaging studies have revealed brain functional abnormalities in frontal-mesolimbic regions in obesity. However, the effects of obesity on brain network topology remains largely unknown. In the current study, we employed resting-state functional magnetic resonance imaging and graph theory methods to investigate obesity-related changes in brain network topology in 26 obese patients and 28 normal weight subjects. Results revealed that the whole-brain networks of the two groups exhibited typical features of small-world topology...
January 9, 2018: Brain Imaging and Behavior
Virginia E Glazier, Damian J Krysan
Complex biological processes are frequently regulated through networks comprised of multiple signaling pathways, transcription factors, and effector molecules. The identity of specific genes carrying out these functions is usually determined by single mutant genetic analysis. However, to understand how the individual genes/gene products function, it is necessary to determine how they interact with other components of the larger network; one approach to this is to use genetic interaction analysis. The human fungal pathogen Candida albicans regulates biofilm formation through an interconnected set of transcription factor hubs and is, therefore, an example of this type of complex network...
January 9, 2018: Current Genetics
Wei Wang, Li Huang, Xuedong Liang
This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks' statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example...
January 6, 2018: International Journal of Environmental Research and Public Health
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