title: Complexity analysis of the magnetoencephalogram background activity in Alzheimer's disease patients.
abstract: The aim of the present study was to analyse the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using the Lempel-Ziv (LZ) complexity. This non-linear method measures the complexity of finite sequences and is related to the number of distinct substrings and the rate of their occurrence along the sequence. The MEGs were recorded with a 148-channel whole-head magnetometer (MAGNES 2500 WH, 4D Neuroimaging) in 21 patients with AD and in 21 age-matched control subjects. Artefact-free epochs were selected for complexity analysis. Results showed that MEG signals from AD patients had lower complexity than control subjects' MEGs and the differences were statistically significant (p<0.01). In order to reduce the dimension of the LZ complexity results, a principal components analysis (PCA) was applied, and only the first principal component was retained. The first component score from PCA was graphically analysed using a box plot and a receiver-operating characteristic (ROC) curve. A specificity of 85.71%, a sensitivity of 80.95% and an area under the ROC curve of 0.9002 were obtained. These preliminary results suggest that cognitive dysfunction in AD is associated with a decreased LZ complexity in the MEG signals.
authors.affiliation: E.T.S. Ingenieros de Telecomunicación, Universidad de Valladolid, Spain. carlos.gomez@tel.uva.es
authors.forename: Carlos
authors.initials: C
authors.lastname: Gómez
authors.forename: Roberto
authors.initials: R
authors.lastname: Hornero
authors.forename: Daniel
authors.initials: D
authors.lastname: Abásolo
authors.forename: Alberto
authors.initials: A
authors.lastname: Fernández
authors.forename: Miguel
authors.initials: M
authors.lastname: López
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology*; D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008875:Middle Aged; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis; D012372:ROC Curve; D012680:Sensitivity and Specificity