Nonlinear techniques and neural activity: emergent trends in MEG data

Nonlinear spatio-temporal analysis was performed on neural activity recorded with 148-channel whole-head magnetoencephalography (MEG). The analysis consists of two phases: artifact removal and nonlinear feature evaluation. Known artifacts, produced by cardiac and eye movement, and unknown artifacts have been isolated from neural activity by using two adaptive filters in a cascade configuration. Secondly, phase space reconstruction of multivariate MEG measurements were performed using both temporal and spatial embedding. Indices of nonlinear dynamics are defined and evaluated showing invariant features both in time and space.