Person:
Jurado Barba, Rosa

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First Name
Rosa
Last Name
Jurado Barba
URI
https://hdl.handle.net/20.500.14352/82050
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
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Area
Psicología Básica
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Author: Bruña Fernández, Ricardo × Start date: 2020 ×

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    Resting-state connectivity and network parameter analysis in alcohol-dependent males. A simultaneous EEG-MEG study
    (Journal of Neuroscience Research, 2020) Sion, Ana Mª Alexandra; Bruña Fernández, Ricardo; Martínez Maldonado, Andrés; Domínguez Centeno, Isabel; Torrado-Carvajal, Ángel; Rubio Valladolid, Gabriel; Pereda, Ernesto; Jurado Barba, Rosa
    There is supporting evidence of alcohol negative effects on the brain: neuroimaging and psychophysiological studies finding anatomical and functional connectivity (FC) changes associated with the dependence process. Thus, the aim of this work was to evaluate brain FC and network characteristics of alcohol-dependent individuals in resting state. For this study, we included males diagnosed with alcohol dependence (N = 25) and a group of healthy individuals (N = 23). Simultaneous EEG-MEG (electroencephalographic and magnetoencephalographic) activity was recorded in 5 min of eyes-closed resting state. EEG-MEG activity was preprocessed and FC was computed through the leakage-corrected version of phase locking value (ciPLV). Additionally, local (degree, efficiency, clustering) and global (efficiency, characteristic path length) network parameters were computed. Connectivity analysis showed an increase in phase-lagged synchronization, mainly between frontal and frontotemporal regions, in high beta band, and a decrease in interhemispheric gamma, for alcohol-dependent individuals. Network analysis revealed intergroup differences at the local level for high beta, indicating higher degree, clustering, and efficiency, mostly at frontal nodes, together with a decrease in these measures at more posterior sites for patients’ group. The hyper-synchronization in beta, next to the hypo-synchronization in gamma, could indicate an alteration in communication between hemispheres, but also a possible functional compensation mechanism in neural circuits. This could be also supported by network characteristic data, where local alterations in communication are observed.