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      DWI and complex brain network analysis predicts vascular cognitive impairment in spontaneous hypertensive rats undergoing executive function tests

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          Abstract

          The identification of biomarkers of vascular cognitive impairment is urgent for its early diagnosis. The aim of this study was to detect and monitor changes in brain structure and connectivity, and to correlate them with the decline in executive function. We examined the feasibility of early diagnostic magnetic resonance imaging (MRI) to predict cognitive impairment before onset in an animal model of chronic hypertension: Spontaneously Hypertensive Rats. Cognitive performance was tested in an operant conditioning paradigm that evaluated learning, memory, and behavioral flexibility skills. Behavioral tests were coupled with longitudinal diffusion weighted imaging acquired with 126 diffusion gradient directions and 0.3 mm 3 isometric resolution at 10, 14, 18, 22, 26, and 40 weeks after birth. Diffusion weighted imaging was analyzed in two different ways, by regional characterization of diffusion tensor imaging (DTI) indices, and by assessing changes in structural brain network organization based on Q-Ball tractography. Already at the first evaluated times, DTI scalar maps revealed significant differences in many regions, suggesting loss of integrity in white and gray matter of spontaneously hypertensive rats when compared to normotensive control rats. In addition, graph theory analysis of the structural brain network demonstrated a significant decrease of hierarchical modularity, global and local efficacy, with predictive value as shown by regional three-fold cross validation study. Moreover, these decreases were significantly correlated with the behavioral performance deficits observed at subsequent time points, suggesting that the diffusion weighted imaging and connectivity studies can unravel neuroimaging alterations even overt signs of cognitive impairment become apparent.

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          Most cited references58

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          Small-world brain networks.

          Many complex networks have a small-world topology characterized by dense local clustering or cliquishness of connections between neighboring nodes yet a short path length between any (distant) pair of nodes due to the existence of relatively few long-range connections. This is an attractive model for the organization of brain anatomical and functional networks because a small-world topology can support both segregated/specialized and distributed/integrated information processing. Moreover, small-world networks are economical, tending to minimize wiring costs while supporting high dynamical complexity. The authors introduce some of the key mathematical concepts in graph theory required for small-world analysis and review how these methods have been applied to quantification of cortical connectivity matrices derived from anatomical tract-tracing studies in the macaque monkey and the cat. The evolution of small-world networks is discussed in terms of a selection pressure to deliver cost-effective information-processing systems. The authors illustrate how these techniques and concepts are increasingly being applied to the analysis of human brain functional networks derived from electroencephalography/magnetoencephalography and fMRI experiments. Finally, the authors consider the relevance of small-world models for understanding the emergence of complex behaviors and the resilience of brain systems to pathological attack by disease or aberrant development. They conclude that small-world models provide a powerful and versatile approach to understanding the structure and function of human brain systems.
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            Fast unfolding of communities in large networks

            We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2.6 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular networks. .
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              Efficient Behavior of Small-World Networks

              We introduce the concept of efficiency of a network, measuring how efficiently it exchanges information. By using this simple measure small-world networks are seen as systems that are both globally and locally efficient. This allows to give a clear physical meaning to the concept of small-world, and also to perform a precise quantitative a nalysis of both weighted and unweighted networks. We study neural networks and man-made communication and transportation systems and we show that the underlying general principle of their construction is in fact a small-world principle of high efficiency.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                23 July 2014
                2014
                : 6
                : 167
                Affiliations
                [1] 1Experimental 7T MRI Unit, IDIBAPS, Institut d'Investigacions Biomèdiques August Pi i Sunyer Barcelona, Spain
                [2] 2Expert Ymaging S.L. Barcelona, Spain
                [3] 3Group of Biomedical Imaging of the University of Barcelona, CIBER de Bioingenieria, Biomateriales y Nanomedicina Barcelona, Spain
                [4] 4Department of Neurochemistry and Neuropharmacology, Institut d'Investigacions Biomèdiques de Barcelona (IIBB-CSIC) Barcelona, Spain
                [5] 5Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), ISCIII Madrid, Spain
                [6] 6Human Anatomy and Embryology Unit, Laboratory of Surgical NeuroAnatomy, Facultat de Medicina, Universitat de Barcelona Barcelona, Spain
                [7] 7Department of Brain Ischemia and Neurodegeneration, Institut d'Investigacions Biomèdiques de Barcelona (IIBB-CSIC) Barcelona, Spain
                [8] 8Department of Experimental Neurology, Center for Stroke Research Berlin Charité, Berlin, Germany
                Author notes

                Edited by: Antonio Camins, University of Barcelona, Spain

                Reviewed by: Marta Vázquez, Universidad de la República, Uruguay; Alessandro Gozzi, Istituto Italiano di Tecnologia, Italy; Nuria Bargallo, Hospital Clínic de Barcelona, Spain

                *Correspondence: Guadalupe Soria, Experimental 7T MRI Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149-153, 08036 Barcelona, Spain e-mail: guadalupe.soria@ 123456idibaps.org

                This article was submitted to the journal Frontiers in Aging Neuroscience.

                Article
                10.3389/fnagi.2014.00167
                4107676
                25100993
                f71a3548-7a13-47c8-913a-dbd27309e12b
                Copyright © 2014 López-Gil, Amat-Roldan, Tudela, Castañé, Prats-Galino, Planas, Farr and Soria.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 10 March 2014
                : 30 June 2014
                Page count
                Figures: 7, Tables: 0, Equations: 1, References: 72, Pages: 13, Words: 10418
                Categories
                Neuroscience
                Original Research Article

                Neurosciences
                dwi,dti,connectomics,executive function,vascular cognitive impairment,animal models,in-vivo mri,hypertension

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