Drug Effect on EEG Connectivity Assessed by Linear and Nonlinear Couplings
Quantitative analysis of human electroencephalogram (EEG) is a valuable method for evaluating psychopharmacological agents. Although the effects of different drug classes on EEG spectra are already known, interactions between brain locations remain unclear. In this work, cross mutual information fun...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2010 |
| País: | España |
| Institución: | Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau) |
| Repositorio: | r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau |
| OAI Identifier: | oai:iibsantpau.fundanetsuite.com:p12828 |
| Acceso en línea: | https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=12828 https://europepmc.org/articles/pmc6870649 |
| Access Level: | acceso abierto |
| Palabra clave: | alprazolam benzodiazepine drug effect EEG mutual information |
| Sumario: | Quantitative analysis of human electroencephalogram (EEG) is a valuable method for evaluating psychopharmacological agents. Although the effects of different drug classes on EEG spectra are already known, interactions between brain locations remain unclear. In this work, cross mutual information function and appropriate surrogate data were applied to assess linear and nonlinear couplings between EEG signals. The main goal was to evaluate the pharmacological effects of alprazolam on brain connectivity during wakefulness in healthy volunteers using a cross-over, placebo-controlled design. Eighty-five pairs of EEG leads were selected for the analysis, and connectivity was evaluated inside anterior, central, and posterior zones of the scalp. Connectivity between these zones and interhemispheric connectivity were also measured. Results showed that alprazolam induced significant changes in EEG connectivity in terms of information transfer in comparison with placebo. Trends were opposite depending on the statistical characteristics: decreases in linear connectivity and increases in nonlinear couplings. These effects were generally, spread over the entire scalp. Linear changes were negatively correlated, and nonlinear changes were positively correlated with drug plasma concentrations; the latter showed higher correlation coefficients. The use of both linear and nonlinear approaches revealed the importance of assessing changes in EEG connectivity as this can provide interesting information about psychopharmacological effects. Hum Brain Mapp 31:487-497, 2010. (C) 2009 Wiley-Liss, hic. |
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