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      Functional and structural brain connectivity of young binge drinkers: a follow-up study

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          Abstract

          Adolescence is a period of ongoing brain maturation characterized by hierarchical changes in the functional and structural networks. For this reason, the young brain is particularly vulnerable to the toxic effects of alcohol. Nowadays, binge drinking is a pattern of alcohol consumption increasingly prevalent among adolescents. The aim of the present study is to evaluate the evolution of the functional and anatomical connectivity of the Default Mode Network (DMN) in young binge drinkers along two years. Magnetoencephalography signal during eyes closed resting state as well as Diffusion Tensor Imaging (DTI) were acquired twice within a 2-year interval from 39 undergraduate students (22 controls, 17 binge drinkers) with neither personal nor family history of alcoholism. The group comparison showed that, after maintaining a binge drinking pattern along at least two years, binge drinkers displayed an increased brain connectivity of the DMN in comparison with the control group. On the other hand, the structural connectivity did not show significant differences neither between groups nor over the time. These findings point out that a continued pattern of binge drinking leads to functional alterations in the normal brain maturation process, even before anatomical changes can be detected.

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          Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements.

          Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.
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            The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors.

            The equation for the magnetic lead field for a given magnetoencephalography (MEG) channel is well known for arbitrary frequencies omega but is not directly applicable to MEG in the quasi-static approximation. In this paper we derive an equation for omega = 0 starting from the very definition of the lead field instead of using Helmholtz's reciprocity theorems. The results are (a) the transpose of the conductivity times the lead field is divergence-free, and (b) the lead field differs from the one in any other volume conductor by a gradient of a scalar function. Consequently, for a piecewise homogeneous and isotropic volume conductor, the lead field is always tangential at the outermost surface. Based on this theoretical result, we formulated a simple and fast method for the MEG forward calculation for one shell of arbitrary shape: we correct the corresponding lead field for a spherical volume conductor by a superposition of basis functions, gradients of harmonic functions constructed here from spherical harmonics, with coefficients fitted to the boundary conditions. The algorithm was tested for a prolate spheroid of realistic shape for which the analytical solution is known. For high order in the expansion, we found the solutions to be essentially exact and for reasonable accuracies much fewer multiplications are needed than in typical implementations of the boundary element methods. The generalization to more shells is straightforward.
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              Adolescent cortical development: a critical period of vulnerability for addiction.

              Cortical growth and remodeling continues from birth through youth and adolescence to stable adult levels changing slowly into senescence. There are critical periods of cortical development when specific experiences drive major synaptic rearrangements and learning that only occur during the critical period. For example, visual cortex is characterized by a critical period of plasticity involved in establishing visual acuity. Adolescence is defined by characteristic behaviors that include high levels of risk taking, exploration, novelty and sensation seeking, social interaction and play behaviors. In addition, adolescence is the final period of development of the adult during which talents, reasoning and complex adult behaviors mature. This maturation of behaviors corresponds with periods of marked changes in neurogenesis, cortical synaptic remodeling, neurotransmitter receptors and transporters, as well as major changes in hormones. Frontal cortical development is later in adolescence and likely contributes to refinement of reasoning, goal and priority setting, impulse control and evaluating long and short term rewards. Adolescent humans have high levels of binge drinking and experimentation with other drugs. This review presents findings supporting adolescence as a critical period of cortical development important for establishing life long adult characteristics that are disrupted by alcohol and drug use.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                10 August 2016
                2016
                : 6
                : 31293
                Affiliations
                [1 ]Laboratory of Cognitive and Computational Neuroscience, Centre of Biomedical Technology (CTB) , 28223, Madrid, Spain
                [2 ]Neuropsychophysiology Lab, Research Center on Psychology (CIPsi), School of Psychology, 4710, University of Minho , Braga, Portugal
                [3 ]Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela , 15782, Santiago de Compostela, Spain
                [4 ]Department of Psychobiology, Complutense University Madrid , 28040, Madrid, Spain
                Author notes
                Article
                srep31293
                10.1038/srep31293
                4978962
                27506835
                ac0526f3-3de8-4290-af39-c4e58fbd17af
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 03 May 2016
                : 15 July 2016
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