Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures


Autoria(s): Bruña Fernandez, Ricardo; Poza Crespo, Jesús; Gómez Peña, Carlos; García Gadañón, María; Fernández Lucas, Alberto; Hornero, Roberto
Data(s)

01/06/2012

Resumo

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.

Formato

application/pdf

Identificador

http://oa.upm.es/21240/

Idioma(s)

eng

Relação

http://oa.upm.es/21240/1/INVE_MEM_2012_98974.pdf

http://iopscience.iop.org/1741-2552/9/3/036007/article

info:eu-repo/semantics/altIdentifier/doi/10.1088/1741-2560/9/3/036007

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

Journal of Neural Engineering, ISSN 1741-2560, 2012-06, Vol. 9, No. 3

Palavras-Chave #Psicología #Electrónica
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed