title: Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients.
abstract: The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using a nonlinear forecasting measure. It is a nonparametric method to quantify the predictability of time series. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 elderly control subjects. Stationary epochs of 5 seconds (848 points, sample frequency of 169.55 Hz) were selected. Our results showed that AD patients' MEGs were more predictable than controls' recordings. Additionally, an accuracy of 76.7% (80.0% sensitivity; 73.3% specificity) was reached using a receiver operating characteristic curve. These preliminary results suggest the usefulness of nonlinear forecasting to gain a better understanding of dynamical processes underlying the MEG recording.
authors.affiliation: Department of Signal Theory and Communications, University of Valladolid, Campus Miguel Delibes, 47011, Spain. cargom@tel.uva.es
authors.forename: Carlos
authors.initials: C
authors.lastname: Gomez
authors.forename: Roberto
authors.initials: R
authors.lastname: Hornero
authors.forename: Angela
authors.initials: A
authors.lastname: Mediavilla
authors.forename: Alberto
authors.initials: A
authors.lastname: Fernandez
authors.forename: Daniel
authors.initials: D
authors.lastname: Abasolo
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D005544:Forecasting; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D011237:Predictive Value of Tests; D012372:ROC Curve