title: Adaptive autoregressive identification with spectral power decomposition for studying movement-related activity in scalp EEG signals and basal ganglia local field potentials.
abstract: We propose a method that combines adaptive autoregressive (AAR) identification and spectral power decomposition for the study of movement-related spectral changes in scalp EEG signals and basal ganglia local field potentials (LFPs). This approach introduces the concept of movement-related poles, allowing one to study not only the classical event-related desynchronizations (ERD) and synchronizations (ERS), which correspond to modulations of power, but also event-related modulations of frequency. We applied the method to analyze movement-related EEG signals and LFPs contemporarily recorded from the sensorimotor cortex, the globus pallidus internus (GPi) and the subthalamic nucleus (STN) in a patient with Parkinson's disease who underwent stereotactic neurosurgery for the implant of deep brain stimulation (DBS) electrodes. In the AAR identification we compared the whale and the exponential forgetting factors, showing that the whale forgetting provides a better disturbance rejection and it is therefore more suitable to investigate movement-related brain activity. Movement-related power modulations were consistent with previous studies. In addition, movement-related frequency modulations were observed from both scalp EEG signals and basal ganglia LFPs. The method therefore represents an effective approach to the study of movement-related brain activity.
authors.affiliation: Department of Biomedical Engineering, Politecnico di Milano, 20133 Milano, Italy. guglielmo.foffani@polimi.it
authors.forename: Guglielmo
authors.initials: G
authors.lastname: Foffani
authors.forename: Anna M
authors.initials: AM
authors.lastname: Bianchi
authors.forename: Alberto
authors.initials: A
authors.lastname: Priori
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Baselli
mesh_terms: D000465:Algorithms; D001479:Basal Ganglia / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor; D005246:Feedback; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D009044:Motor Cortex / Q000503:physiopathology*; D010300:Parkinson Disease / Q000175:diagnosis / Q000503:physiopathology*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013003:Somatosensory Cortex / Q000503:physiopathology*