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A novel method for the identification of synchronization effects in multichannel ECoG with an application to epilepsy
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 t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661083/ https://www.ncbi.nlm.nih.gov/pubmed/23435583 http://dx.doi.org/10.1007/s00422-013-0552-8 |
Sumario: | 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. |
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