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Abstract
Epilepsy is a neurological disorder characterized by seizures, i.e. abnormal synchronous activity of neurons in the brain. During a focal seizure the epileptic activity spreads rapidly from the ictal onset region to neighboring brain areas. ElectroEncephaloGraphy (EEG) is a commonly used technique to diagnose epilepsy. EEG has a high temporal resolution which allows us to investigate the dynamics of the underlying brain activity. Due to the rapid propagation of a seizure, the seizure can originate from a network of brain regions which are simultaneously active before being noticeable on the EEG. In this paper we investigate two state of the art source localization techniques, the Recursive Applied and Projected (RAP) and the pre-correlated and orthogonally projected (POP) multiple signal classification (MUSIC) algorithm, to identify the location of the driver behind the simulated epileptic brain network. Furthermore we investigate the applicability of connectivity analysis to identify the source driving the underlying brain network. We showed that the POP-MUSIC algorithm outperforms the RAP-MUSIC algorithm to identify the locations of the simultaneous brain activity. Furthermore, we showed the feasibility of identifying the driver behind a brain network by POP-MUSIC algorithm followed by connectivity analysis.
Keywords
Electroencephalography, source, localization, epilepsy, connectivity analysis

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Chicago
van Mierlo, Pieter, Victoria Eugenia Montes Restrepo, Hans Hallez, and Steven Staelens. 2011. “Epileptic Brain Network from Scalp EEG: Identifying the Epileptic Driver by Connectivity Analysis on Brain Waveforms.” In Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM), 114–118. Piscataway, NJ, USA: IEEE.
APA
van Mierlo, P., Montes Restrepo, V. E., Hallez, H., & Staelens, S. (2011). Epileptic brain network from scalp EEG: identifying the epileptic driver by connectivity analysis on brain waveforms. Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM) (pp. 114–118). Presented at the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM), Piscataway, NJ, USA: IEEE.
Vancouver
1.
van Mierlo P, Montes Restrepo VE, Hallez H, Staelens S. Epileptic brain network from scalp EEG: identifying the epileptic driver by connectivity analysis on brain waveforms. Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM). Piscataway, NJ, USA: IEEE; 2011. p. 114–8.
MLA
van Mierlo, Pieter, Victoria Eugenia Montes Restrepo, Hans Hallez, et al. “Epileptic Brain Network from Scalp EEG: Identifying the Epileptic Driver by Connectivity Analysis on Brain Waveforms.” Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM). Piscataway, NJ, USA: IEEE, 2011. 114–118. Print.
@inproceedings{3143526,
  abstract     = {Epilepsy is a neurological disorder characterized by seizures, i.e. abnormal synchronous activity of neurons in the brain. During a focal seizure the epileptic activity spreads rapidly from the ictal onset region to neighboring brain areas. ElectroEncephaloGraphy (EEG) is a commonly used technique to diagnose epilepsy. EEG has a high temporal resolution which allows us to investigate the dynamics of the underlying brain activity. Due to the rapid propagation of a seizure, the seizure can originate from a network of brain regions which are simultaneously active before being noticeable on the EEG. In this paper we investigate two state of the art source localization techniques, the Recursive Applied and Projected (RAP) and the pre-correlated and orthogonally projected (POP) multiple signal classification (MUSIC) algorithm, to identify the location of the driver behind the simulated epileptic brain network. Furthermore we investigate the applicability of connectivity analysis to identify the source driving the underlying brain network. We showed that the POP-MUSIC algorithm outperforms the RAP-MUSIC algorithm to identify the locations of the simultaneous brain activity. Furthermore, we showed the feasibility of identifying the driver behind a brain network by POP-MUSIC algorithm followed by connectivity analysis.},
  author       = {van Mierlo, Pieter and Montes Restrepo, Victoria Eugenia and Hallez, Hans and Staelens, Steven},
  booktitle    = {Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM)},
  isbn         = {9781424482825},
  keyword      = {Electroencephalography,source,localization,epilepsy,connectivity analysis},
  language     = {eng},
  location     = {Banff, Canada},
  pages        = {114--118},
  publisher    = {IEEE},
  title        = {Epileptic brain network from scalp EEG: identifying the epileptic driver by connectivity analysis on brain waveforms},
  url          = {http://dx.doi.org/10.1109/NFSI.2011.5936838},
  year         = {2011},
}

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