title: Methods for parameter identification in oscillatory networks and application to cortical and thalamic 600 Hz activity.
abstract: Directed information transfer in the human brain occurs presumably by oscillations. As of yet, most approaches for the analysis of these oscillations are based on time-frequency or coherence analysis. The present work concerns the modeling of cortical 600 Hz oscillations, localized within the Brodmann Areas 3b and 1 after stimulation of the nervus medianus, by means of coupled differential equations. This approach leads to the so-called parameter identification problem, where based on a given data set, a set of unknown parameters of a system of ordinary differential equations is determined by special optimization procedures. Some suitable algorithms for this task are presented in this paper. Finally an oscillatory network model is optimally fitted to the data taken from ten volunteers.
authors.affiliation: Institute of Medical Statistics, Computer Sciences and Documentation, Friedrich Schiller University Jena, Bachstr. 18, D-07740 Jena, Germany. i6lelu@imsid.uni-jena.de
authors.forename: L
authors.initials: L
authors.lastname: Leistritz
authors.forename: T
authors.initials: T
authors.lastname: Suesse
authors.forename: J
authors.initials: J
authors.lastname: Haueisen
authors.forename: B
authors.initials: B
authors.lastname: Hilgenfeld
authors.forename: H
authors.initials: H
authors.lastname: Witte
mesh_terms: D002540:Cerebral Cortex / Q000502:physiology*; D004558:Electric Stimulation; D004574:Electromagnetic Fields; D005073:Evoked Potentials, Somatosensory / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D013788:Thalamus / Q000502:physiology*