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New approaches for exploring anatomical and functional connectivity in the human brain. Biological Psychiatry, 56(9), 613-619

Centre for Functional Magnetic Resonance Imaging of the Brain, Department of Clinical Neurology, University of Oxford, Headley Way, Oxford OX3 9DU, United Kingdom.
Biological Psychiatry (Impact Factor: 10.25). 12/2004; 56(9):613-9. DOI: 10.1016/j.biopsych.2004.02.004
Source: PubMed

ABSTRACT Information processing in the primate brain is based on the complementary principles of modular and distributed information processing. The former emphasizes the specialization of functions within different brain areas. The latter emphasizes the massively parallel nature of brain networks and the fact that function also emerges from the flow of information between brain areas. The localization of function to specific brain areas ("functional segregation") is the commonest approach to investigating function; however, an emerging, complementary approach ("functional integration") describes function in terms of the information flow across networks of areas. Here, we highlight recent advances in neuroimaging methodology that have made it possible to investigate the anatomical architecture of networks in the living human brain with diffusion tensor imaging (DTI). We also highlight recent thinking on the ways in which functional imaging can be used to characterize information transmission across networks in the human brain (functional and effective connectivity).

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Available from: Narender Ramnani, Aug 29, 2015
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    • "Существует несколько способов моделироваа ния или оценки возникающих эффективных связей, такие, как моделирование с помощью структурных уравнений (SEM), причинность по Грейнджеру (Granger Causality), перенос энтропии (Transfer Entropy) или динамичее ское моделирование причинности (Dynamic Causal Modelling, DCM). DCM – это моделирование взаимодейй ствий между областями коры больших полуу шарий, позволяющее делать выводы как о паа раметрах этих взаимодействий, так и о влияя нии факторов эксперимента на параметры [Ramnani, 2004]. В рамках DCM мозг расс сматривается как детерминированная нелии нейная динамическая система, которая полуу чает входные данные и производит выходные [Friston, 2003]. "
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    Pavlov journal of higher nervous activity 01/2014; 64(6):627-638. DOI:10.7868/S0044467714060100
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    • "The comparison of temporal profiles recorded from different regions of interest might yield information on functional synchronicity of different brain areas in relation to the stimulus (Ramnani et al., 2004; Rogers et al., 2007). Connectivity analyses have been performed in both human and animal studies by use of electroencephalogram (EEG) recordings as well as by positron emission tomography (PET) techniques (Gerstein and Perkel, 1969; Horwitz et al., 1984). "
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    NeuroImage 02/2013; DOI:10.1016/j.neuroimage.2013.02.031 · 6.36 Impact Factor
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    • "On the other hand, it is very important to master the anatomy of the white matter fiber, especially the sectional anatomy of the fiber, with the purpose of identifying the fiber on FA and color FA maps, and placing the ROI accurately. Another remaining problem for fibre tracking is the limited resolution of the imaging scanner and the incapacity of a tensor to model properly multiple fibre tracts in one voxel [13] [18]. Current deterministic streamlining algorithms follow the main eigenvector of the diffusion tensor, reducing the available information. "
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