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dc.contributor.authorGómez Peña, Carlos 
dc.contributor.authorRuiz Gómez, Saúl José 
dc.contributor.authorPoza Crespo, Jesús 
dc.contributor.authorMaturana Candelas, Aarón
dc.contributor.authorPinto, Nádia
dc.contributor.authorTola Arribas, Miguel Ángel 
dc.contributor.authorCano, Mónica
dc.contributor.authorHornero Sánchez, Roberto 
dc.date.accessioned2018-09-03T11:25:26Z
dc.date.available2018-09-03T11:25:26Z
dc.date.issued2018
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/31362
dc.descriptionProducción Científicaes
dc.description.abstractMild cognitive impairment (MCI) is a pathology characterized by an abnormal cognitive state. MCI patients are considered to be at high risk for developing dementia. The aim of this study is to characterize the changes that MCI causes in the patterns of brain information flow. For this purpose, spontaneous EEG activity from 41 MCI patients and 37 healthy controls was analyzed by means of an effective connectivity measure: the phase slope index (PSI). Our results showed statistically significant decreases in PSI values mainly at delta and alpha frequency bands for MCI patients, compared to the control group. These abnormal patterns may be due to the structural changes in the brain suffered by patients: decreased hippocampal volume, atrophy of the medial temporal lobe, or loss of gray matter volume. This study suggests the usefulness of PSI to provide further insights into the underlying brain dynamics associated with MCI.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses
dc.titleAssessment of EEG Connectivity Patterns in Mild Cognitive Impairment Using Phase Slope Indexes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.title.event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Societyes
dc.description.projectCompetitividad’ and ‘European Regional Development Fund’ under project TEC2014-53196-R, by ‘European Commission’ and ‘European Regional Development Fund’ under project ‘Análisis y correlación entre el genoma completo y la actividad cerebral para la ayuda en el diagnóstico de la enfermedad de Alzheimer’ (‘Cooperation Programme Interreg V-A Spain- Portugal POCTEP 2014-2020’), and by ‘Consejería de Educación de la Junta de Castilla y León’ under project VA037U16. P. Núñez and S. J. Ruiz are in receipt of predoctoral grants co-financed by the ‘Junta de Castilla y León’ and ESF. N. Pinto’s work is partially financed through the FCT postdoctoral grant SFRH/BPD/97414/2013 and projects POCI-01-0145- FEDER-007274 and UID/MAT/00144/2013. C. Gómez, Saúl J. Ruiz-Gómez, J. Poza, A. Maturana-Candelas, P. Núñez, and R. Hornero are with the Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Paseo Belén 15, 47011 Valladolid, Spain (e-mail: carlos.gomez@tel.uva.es). N. Pinto is with the Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), the Institute for Research and Innovation in Health Sciences, and the Center of Mathematics of University of Porto, Portugal. M. A. Tola is with the Department of Neurology, Hospital Universitario Río Hortega, Valladolid, Spain. M. Cano is with the Department of Clinical Neurophysiology, Hospital Universitario Río Hortega, Valladolid, Spain.es


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