Neurophysiological correlates in Mild Cognitive Impairment detected using group Independent Component Analysis.
Annu Int Conf IEEE Eng Med Biol Soc
; 2015: 7442-5, 2015.
Article
en En
| MEDLINE
| ID: mdl-26738012
ABSTRACT
Alzheimer's disease is the most prevalent cause of dementia. Mild Cognitive Impairment (MCI) is defined as a grey area between intact cognitive functioning and clinical dementia. Electroencephalography (EEG) has been used to identify biomarkers in dementia. Currently, there is a great interest in translating the study from raw signals to signal generators, trying to keep the relationship with neurophysiology. In the current study, EEG recordings during an encoding task were acquired in MCI subjects and healthy controls. Data was decomposed using group Independent Component Analysis (gICA) and the most neuronal components were analyzed using Phase Intertrial Coherence (PIC) and Phase shift Intertrial Coherence (PsIC). MCI subjects exhibited an increase of PIC in the theta band, while controls showed increase in PsIC in the alpha band. Correlation between PIC and PsIC and clinical scales were also found. Those findings indicate that the methodology proposed based in gICA can help to extract information from EEG recordings with neurophysiological meaning.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Análisis de Componente Principal
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Enfermedad de Alzheimer
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Disfunción Cognitiva
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Neurofisiología
Tipo de estudio:
Observational_studies
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Prognostic_studies
Límite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2015
Tipo del documento:
Article