title: A novel method for the identification of synchronization effects in multichannel ECoG with an application to epilepsy.
abstract: In this paper, we present a novel method for the identification of synchronization effects in multichannel electrocorticograms (ECoG). Based on autoregressive modeling, we define a dependency measure termed extrinsic-to-intrinsic power ratio (EIPR) which quantifies directed coupling effects in the time domain. Hereby, a dynamic input channel selection algorithm assures the estimation of the model parameters despite the strong spatial correlation among the high number of involved ECoG channels. We compare EIPR to the partial directed coherence, show its ability to indicate Granger causality and successfully validate a signal model. Applying EIPR to ictal ECoG data of patients suffering from temporal lobe epilepsy allows us to identify the electrodes of the seizure onset zone. The results obtained by the proposed method are in good accordance with the clinical findings.
authors: Institute for Mathematical Methods in Economics, Vienna University of Technology, Vienna, Austria. andreas.graef@tuwien.ac.at
authors: A
authors: A
authors: Graef
authors: M
authors: M
authors: Hartmann
authors: C
authors: C
authors: Flamm
authors: C
authors: C
authors: Baumgartner
authors: M
authors: M
authors: Deistler
authors: T
authors: T
authors: Kluge
mesh_terms: D000465:Algorithms; D001931:Brain Mapping; D004569:Electroencephalography; D058407:Electroencephalography Phase Synchronization / Q000502:physiology*; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology*; D006801:Humans; D008954:Models, Biological; D017711:Nonlinear Dynamics; D012044:Regression Analysis