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https://www.readbyqxmd.com/read/29053835/abnormal-intrinsic-brain-functional-network-dynamics-in-parkinson-s-disease
#1
Jinhee Kim, Marion Criaud, Sang Soo Cho, María Díez-Cirarda, Alexander Mihaescu, Sarah Coakeley, Christine Ghadery, Mikaeel Valli, Mark F Jacobs, Sylvain Houle, Antonio P Strafella
Parkinson's disease is a neurodegenerative disorder characterized by nigrostriatal dopamine depletion. Previous studies measuring spontaneous brain activity using resting state functional magnetic resonance imaging have reported abnormal changes in broadly distributed whole-brain networks. Although resting state functional connectivity, estimating temporal correlations between brain regions, is measured with the assumption that intrinsic fluctuations throughout the scan are stable, dynamic changes of functional connectivity have recently been suggested to reflect aspects of functional capacity of neural systems, and thus may serve as biomarkers of disease...
October 5, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/29051730/dynamical-graph-theory-networks-methods-for-the-analysis-of-sparse-functional-connectivity-networks-and-for-determining-pinning-observability-in-brain-networks
#2
Anke Meyer-Bäse, Rodney G Roberts, Ignacio A Illan, Uwe Meyer-Bäse, Marc Lobbes, Andreas Stadlbauer, Katja Pinker-Domenig
Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/29036672/convergence-and-divergence-of-brain-network-dysfunction-in-deficit-and-non-deficit-schizophrenia
#3
Miao Yu, Zhengjia Dai, Xiaowei Tang, Xiang Wang, Xiaobin Zhang, Weiwei Sha, Shuqiao Yao, Ni Shu, Xindi Wang, Jiaying Yang, Xiangyang Zhang, Xiangrong Zhang, Yong He, Zhijun Zhang
Deficit schizophrenia (DS), characterized by primary and enduring negative symptoms, has been considered as a pathophysiologically distinct schizophrenic subgroup. Neuroimaging characteristics of DS, especially functional brain network architecture, remain largely unknown. Resting-state functional magnetic resonance imaging and graph theory approaches were employed to investigate the topological organization of whole-brain functional networks of 114 male participants including 33 DS, 41 non-deficit schizophrenia (NDS) and 40 healthy controls (HCs)...
July 20, 2017: Schizophrenia Bulletin
https://www.readbyqxmd.com/read/29034164/aberrant-brain-functional-connectivity-in-newborns-with-congenital-heart-disease-before-cardiac-surgery
#4
Josepheen De Asis-Cruz, Mary T Donofrio, Gilbert Vezina, Catherine Limperopoulos
Newborns with congenital heart disease (CHD) requiring open heart surgery are at increased risk for neurodevelopmental disabilities. Recent quantitative MRI studies have reported disrupted growth, microstructure, and metabolism in fetuses and newborns with complex CHD. To date, no study has examined whether functional brain connectivity is altered in this high-risk population after birth, before surgery. Our objective was to compare whole-brain functional connectivity of resting state networks in healthy, term newborns (n = 82) and in term neonates with CHD before surgery (n = 30) using graph theory and network-based statistics...
2018: NeuroImage: Clinical
https://www.readbyqxmd.com/read/29028937/abnormal-structural-brain-connectome-in-individuals-with-preclinical-alzheimer-s-disease
#5
Joana B Pereira, Danielle van Westen, Erik Stomrud, Tor Olof Strandberg, Giovanni Volpe, Eric Westman, Oskar Hansson
Alzheimer's disease has a long preclinical phase during which amyloid pathology and neurodegeneration accumulate in the brain without producing overt cognitive deficits. It is currently unclear whether these early disease stages are associated with a progressive disruption in the communication between brain regions that subsequently leads to cognitive decline and dementia. In this study we assessed the organization of structural networks in cognitively normal (CN) individuals harboring amyloid pathology (A+N-), neurodegeneration (A-N+), or both (A+N+) from the prospective and longitudinal Swedish BioFINDER study...
October 3, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28981593/a-new-modular-brain-organization-of-the-bold-signal-during-natural-vision
#6
DoHyun Kim, Kendrick Kay, Gordon L Shulman, Maurizio Corbetta
The resting blood oxygen level-dependent (BOLD) signal is synchronized in large-scale brain networks (resting-state networks, RSNs) defined by interregional temporal correlations (functional connectivity, FC). RSNs are thought to place strong constraints on task-evoked processing since they largely match the networks observed during task performance. However, this result may simply reflect the presence of spontaneous activity during both rest and task. Here, we examined the BOLD network structure of natural vision, as simulated by viewing of movies, using procedures that minimized the contribution of spontaneous activity...
July 13, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28971937/a-complete-characterization-of-all-versus-nothing-arguments-for-stabilizer-states
#7
Samson Abramsky, Rui Soares Barbosa, Giovanni Carù, Simon Perdrix
An important class of contextuality arguments in quantum foundations are the all-versus-nothing (AvN) proofs, generalizing a construction originally due to Mermin. We present a general formulation of AvN arguments and a complete characterization of all such arguments that arise from stabilizer states. We show that every AvN argument for an n-qubit stabilizer state can be reduced to an AvN proof for a three-qubit state that is local Clifford-equivalent to the tripartite Greenberger-Horne-Zeilinger state. This is achieved through a combinatorial characterization of AvN arguments, the AvN triple theorem, whose proof makes use of the theory of graph states...
November 13, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28968248/shortest-path-based-network-analysis-to-characterize-cognitive-load-states-of-human-brain-using-eeg-based-functional%C3%A2-brain-networks
#8
M Thilaga, R Vijayalakshmi, R Nadarajan, D Nandagopal
Understanding and analyzing the dynamic interactions among the millions of spatially distributed and functionally connected regions in the human brain constituting a massively parallel communication system is one of the major challenges in computational neuroscience. Many studies in the recent past have employed graph theory to efficiently model, quantitatively analyze and understand the brain's electrical activity. Since, the human brain is believed to broadcast information with reduced material and metabolic costs, identifying various brain regions in the shortest pathways of information dissemination becomes essential to understand the intricacies of brain functioning...
September 28, 2017: Journal of Integrative Neuroscience
https://www.readbyqxmd.com/read/28954333/-the-altered-topology-of-brain-structural-network-in-patients-with-acute-stress-response-after-traffic-accident
#9
Y F Weng, R F Qi, X D Zhang, L Zhang, J Ke, Y Zhong, F Chen, Q Xu, G M Lu
Objective: To explore the changes of brain activities in traffic accident survivors with acute stress response (ASR) within a week by using complex networks analysis method based on graph-theory, and to find out the alteration of topological properties in structural brain network. Method: From January, 2013 to February, 2016, twenty traffic accidents survivors with acute stress disorders (Acute Stress Disorder Interview, ASDI>3)and twenty healthy controls underwent the 3T diffusion tensor imaging (DTI) magnetic resonance imaging scan in Nanjing General Hospital...
September 19, 2017: Zhonghua Yi Xue za Zhi [Chinese medical journal]
https://www.readbyqxmd.com/read/28949286/altered-intrinsic-functional-brain-architecture-in-female-patients-with-bulimia-nervosa
#10
Li Wang, Qing-Mei Kong, Ke Li, Xue-Ni Li, Ya-Wei Zeng, Chao Chen, Ying Qian, Shi-Jie Feng, Ji-Tao Li, Yun'Ai Su, Christoph U Correll, Philip B Mitchell, Chao-Gan Yan, Da-Rong Zhang, Tian-Mei Si
BACKGROUND: Bulimia nervosa is a severe psychiatric syndrome with uncertain pathogenesis. Neural systems involved in sensorimotor and visual processing, reward and impulsive control may contribute to the binge eating and purging behaviours characterizing bulimia nervosa. However, little is known about the alterations of functional organization of whole brain networks in individuals with this disorder. METHODS: We used resting-state functional MRI and graph theory to characterize functional brain networks of unmedicated women with bulimia nervosa and healthy women...
September 26, 2017: Journal of Psychiatry & Neuroscience: JPN
https://www.readbyqxmd.com/read/28948193/imperial-college-near-infrared-spectroscopy-neuroimaging-analysis-framework
#11
Felipe Orihuela-Espina, Daniel R Leff, David R C James, Ara W Darzi, Guang-Zhong Yang
This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis...
January 2018: Neurophotonics
https://www.readbyqxmd.com/read/28944305/network-organization-is-globally-atypical-in-autism-a-graph-theory-study-of-intrinsic-functional-connectivity
#12
Christopher L Keown, Michael C Datko, Colleen P Chen, José Omar Maximo, Afrooz Jahedi, Ralph-Axel Müller
BACKGROUND: Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). METHODS: We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics...
January 2017: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
https://www.readbyqxmd.com/read/28943732/topographic-regularity-for-tract-filtering-in-brain-connectivity
#13
Junyan Wang, Dogu Baran Aydogan, Rohit Varma, Arthur W Toga, Yonggang Shi
The preservation of the spatial relationships among axonal pathways has long been studied and known to be critical for many functions of the brain. Being a fundamental property of the brain connections, there is an intuitive understanding of topographic regularity in neuroscience but yet to be systematically explored in connectome imaging research. In this work, we propose a general mathematical model for topographic regularity of fiber bundles that is consistent with its neuroanatomical understanding. Our model is based on a novel group spectral graph analysis (GSGA) framework motivated by spectral graph theory and tensor decomposition...
June 2017: Information Processing in Medical Imaging: Proceedings of the ... Conference
https://www.readbyqxmd.com/read/28928648/a-single-session-of-rtms-enhances-small-worldness-in-writer-s-cramp-evidence-from-simultaneous-eeg-fmri-multi-modal-brain-graph
#14
Rose D Bharath, Rajanikant Panda, Venkateswara Reddy Reddam, M V Bhaskar, Suril Gohel, Sujas Bhardwaj, Arvind Prajapati, Pramod Kumar Pal
Background and Purpose: Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method: Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC)...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28918301/mathematical-fundamentals-for-the-noise-immunity-of-the-genetic-code
#15
Elena Fimmel, Lutz Strüngmann
Symmetry is one of the essential and most visible patterns that can be seen in nature. Starting from the left-right symmetry of the human body, all types of symmetry can be found in crystals, plants, animals and nature as a whole. Similarly, principals of symmetry are also some of the fundamental and most useful tools in modern mathematical natural science that play a major role in theory and applications. As a consequence, it is not surprising that the desire to understand the origin of life, based on the genetic code, forces us to involve symmetry as a mathematical concept...
September 13, 2017: Bio Systems
https://www.readbyqxmd.com/read/28914733/metabolic-connectivity-methods-and-applications
#16
Igor Yakushev, Alexander Drzezga, Christian Habeck
PURPOSE OF REVIEW: Metabolic connectivity modelling aims to detect functionally interacting brain regions based on PET recordings with the glucose analogue [F]fluorodeoxyglucose (FDG). Here, we outline the most popular metabolic connectivity methods and summarize recent applications in clinical and basic neuroscience. RECENT FINDINGS: Metabolic connectivity is modelled by various methods including a seed correlation, sparse inverse covariance estimation, independent component analysis and graph theory...
September 13, 2017: Current Opinion in Neurology
https://www.readbyqxmd.com/read/28906364/altered-default-mode-network-configuration-in-posttraumatic-stress-disorder-after-earthquake-a-resting-stage-functional-magnetic-resonance-imaging-study
#17
Xiao-Dong Zhang, Yan Yin, Xiao-Lei Hu, Lian Duan, Rongfeng Qi, Qiang Xu, Guang-Ming Lu, Ling-Jiang Li
The neural substrates of posttraumatic stress disorder (PTSD) are still not fully elucidated. Hence, this study is to explore topological alterations of the default mode network (DMN) in victims with PTSD after a magnitude of 8.0 earthquake using resting-state functional magnetic resonance imaging (rs-fMRI).This study was approved by the local ethical review board, and all participants signed written informed consent. Sixty-two PTSD victims from the 2008 Sichuan earthquake and 62 matched exposed controls underwent rs-fMRI...
September 2017: Medicine (Baltimore)
https://www.readbyqxmd.com/read/28904392/emergent-spectral-properties-of-river-network-topology-an-optimal-channel-network-approach
#18
Armaghan Abed-Elmdoust, Arvind Singh, Zong-Liang Yang
Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix. First, we introduce a graph theory model for river networks and explore the properties of the network through its adjacency matrix. Next, we show that the eigenvalue spectra of such complex networks follow distinct patterns and exhibit striking features including a spectral gap in which no eigenvalue exists as well as a finite number of zero eigenvalues...
September 13, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28898869/disrupted-brain-network-hubs-in-subtype-specific-parkinson-s-disease
#19
Ling-Yan Ma, Xiao-Dan Chen, Yong He, Hui-Zi Ma, Tao Feng
BACKGROUND/AIMS: The topological organization of brain functional networks is impaired in Parkinson's disease (PD). However, the altered patterns of functional network hubs in different subtypes of PD are not completely understood. METHODS: 3T resting-state functional MRI and voxel-based graph-theory analysis were employed to systematically investigate the intrinsic functional connectivity patterns of whole-brain networks. We enrolled 31 patients with PD (12 tremor dominant [TD] and 19 with postural instability/gait difficulty [PIGD]) and 22 matched healthy controls...
2017: European Neurology
https://www.readbyqxmd.com/read/28881417/central-and-non-central-networks-cognition-clinical-symptoms-and-polygenic-risk-scores-in-schizophrenia
#20
Clara Alloza, Mark E Bastin, Simon R Cox, Jude Gibson, Barbara Duff, Scott I Semple, Heather C Whalley, Stephen M Lawrie
Schizophrenia is a complex disorder that may be the result of aberrant connections between specific brain regions rather than focal brain abnormalities. Here, we investigate the relationships between brain structural connectivity as described by network analysis, intelligence, symptoms, and polygenic risk scores (PGRS) for schizophrenia in a group of patients with schizophrenia and a group of healthy controls. Recently, researchers have shown an interest in the role of high centrality networks in the disorder...
September 7, 2017: Human Brain Mapping
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