Linear inverse filtering improves spatial separation of nonlinear brain dynamics: a simulation study

We examined topographic variations in nonlinear measures based on scalp vol tages, which were generated by two simulated current dipoles each placed in a different hemisphere of a spherical volume conductor (three-shell model) . Dipole dynamics were that of a three-torus and the x-component of the Lor enz-system and scalp voltage were calculated for a configuration of 29 elec trode positions. Although estimates for correlation dimension D2 and Lyapun ov exponent L1 were close to the theoretical values for the original time s eries, the simulated scalp voltage data showed almost no topographic resolu tion of dipole positions. In order to enhance topographic differentiation, we constructed linear inverse filters, to focus on brain activity from a sp ecified brain region. II turned out that the nonlinear measures for the inv ersely filtered time series were much closer to the expected values (with r espect to the location of the dipoles used in the simulation) than when usi ng unfiltered data. Our preliminary results indicate that inverse filtering can improve the topographic resolution of nonlinear scalp EEG estimates. ( C) 2000 Elsevier Science B.V. All rights reserved.