title: Complementary methods for interpreting brain signals: linear versus nonlinear techniques.
abstract: Magnetoencephalography (MEG) brain signals are characterized using both linear and nonlinear dynamical methods. The linear approach employs the power analysis in a spatial visualization. The nonlinear approach estimates the value of d(infinity) to characterize the system's asymptotic chaotic behavior using a computationally less onerous method than the conventional one for d(infinity). Both methods are applied here to study a female patient with obsessive compulsive disorder and an age-sex matched normal subject. MEG time series were obtained using dual 37-channel bio-magnetometers (4-D Neuroimaging, San Diego, CA).
authors.affiliation: Dipartimento di Ingegneria Elettrica, Elettronica e dei Sistemi, Università degli Studi di Catania, V le A, Doria 6, 95125, Catania, Italy. mbucolo@diees.unict.it
authors.forename: Maide
authors.initials: M
authors.lastname: Bucolo
authors.forename: Federica
authors.initials: F
authors.lastname: Di Grazia
authors.forename: Luigi
authors.initials: L
authors.lastname: Fortuna
authors.forename: Mattia
authors.initials: M
authors.lastname: Frasca
authors.forename: Francesca
authors.initials: F
authors.lastname: Sapuppo
authors.forename: David
authors.initials: D
authors.lastname: Shannahoff-Khalsa
mesh_terms: D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000295:instrumentation; D004867:Equipment Design; D005260:Female; D006801:Humans; D016014:Linear Models; D015225:Magnetoencephalography / Q000295:instrumentation* / Q000379:methods; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D009771:Obsessive-Compulsive Disorder / Q000175:diagnosis* / Q000473:pathology; D012815:Signal Processing, Computer-Assisted