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Changes in connectivity patterns in the kainate model of epilepsy

Pieter van Mierlo (UGent), Sara Assecondi (UGent), Steven Staelens (UGent), Paul Boon (UGent) and Ignace Lemahieu (UGent)
(2009) IFMBE Proceedings. 22(1-3). p.360-363
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Abstract
Epilepsy is a neurological disorder characterized by seizures, i.e. excessive and hyper synchronous activity of neurons in the brain. ElectroEncephaloGram (EEG) is the recording of brain activity in time through electrodes placed on the scalp and is one of the most used techniques to monitor brain activity. In order to identify pattern of propagation across brain areas that are specific to epilepsy, connectivity measures such as the Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC) have been developed. These measures reveal connections between different areas by exploiting statistical dependencies within multichannel EEG recordings. This work proposes a framework to identify and compare interdependencies between EEG signals in different brain states. We considered an animal model of epilepsy characterized by spontaneous recurrent seizures. In three rats we identified a normal healthy baseline state and an epileptic state for which we estimated interdependencies between EEG channels using DTF and PDC and extracted significant differences between both states. We showed the feasibility of detection of connectivity patterns in a simple animal model of epilepsy. We found common patterns of propagation in the brain of the three rats during the baseline state. After the kainic acid injection, the connectivity pattern of interictal period is significantly altered compared to the baseline situation. Inter-rat variations are observed, but the intra-rat pattern alterations are consistent in time, revealing that the kainic acid permanently changes the brain connectivity.
Keywords
Animal model of epilepsy, connectivity, electroencephalogram

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Chicago
van Mierlo, Pieter, Sara Assecondi, Steven Staelens, Paul Boon, and Ignace Lemahieu. 2009. “Changes in Connectivity Patterns in the Kainate Model of Epilepsy.” In IFMBE Proceedings, ed. J Vander Sloten, Pascal Verdonck, M Nyssen, and J Haueisen, 22:360–363. New York, NY, USA: Springer.
APA
van Mierlo, P., Assecondi, S., Staelens, S., Boon, P., & Lemahieu, I. (2009). Changes in connectivity patterns in the kainate model of epilepsy. In J Vander Sloten, P. Verdonck, M. Nyssen, & J. Haueisen (Eds.), IFMBE Proceedings (Vol. 22, pp. 360–363). Presented at the 4th European conference of the International Federation for Medical and Biological Engineering, New York, NY, USA: Springer.
Vancouver
1.
van Mierlo P, Assecondi S, Staelens S, Boon P, Lemahieu I. Changes in connectivity patterns in the kainate model of epilepsy. In: Vander Sloten J, Verdonck P, Nyssen M, Haueisen J, editors. IFMBE Proceedings. New York, NY, USA: Springer; 2009. p. 360–3.
MLA
van Mierlo, Pieter, Sara Assecondi, Steven Staelens, et al. “Changes in Connectivity Patterns in the Kainate Model of Epilepsy.” IFMBE Proceedings. Ed. J Vander Sloten et al. Vol. 22. New York, NY, USA: Springer, 2009. 360–363. Print.
@inproceedings{677838,
  abstract     = {Epilepsy is a neurological disorder characterized by seizures, i.e. excessive and hyper synchronous activity of neurons in the brain. ElectroEncephaloGram (EEG) is the recording of brain activity in time through electrodes placed on the scalp and is one of the most used techniques to monitor brain activity. In order to identify pattern of propagation across brain areas that are specific to epilepsy, connectivity measures such as the Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC) have been developed. These measures reveal connections between different areas by exploiting statistical dependencies within multichannel EEG recordings. This work proposes a framework to identify and compare interdependencies between EEG signals in different brain states. We considered an animal model of epilepsy characterized by spontaneous recurrent seizures. In three rats we identified a normal healthy baseline state and an epileptic state for which we estimated interdependencies between EEG channels using DTF and PDC and extracted significant differences between both states. We showed the feasibility of detection of connectivity patterns in a simple animal model of epilepsy. We found common patterns of propagation in the brain of the three rats during the baseline state. After the kainic acid injection, the connectivity pattern of interictal period is significantly altered compared to the baseline situation. Inter-rat variations are observed, but the intra-rat pattern alterations are consistent in time, revealing that the kainic acid permanently changes the brain connectivity.},
  author       = {van Mierlo, Pieter and Assecondi, Sara and Staelens, Steven and Boon, Paul and Lemahieu, Ignace},
  booktitle    = {IFMBE Proceedings},
  editor       = {Vander Sloten, J and Verdonck, Pascal and Nyssen, M and Haueisen, J},
  isbn         = {9783540892083},
  issn         = {1680-0737},
  keyword      = {Animal model of epilepsy,connectivity,electroencephalogram},
  language     = {eng},
  location     = {Antwerp, Belgium},
  number       = {1-3},
  pages        = {360--363},
  publisher    = {Springer},
  title        = {Changes in connectivity patterns in the kainate model of epilepsy},
  url          = {http://dx.doi.org/10.1007/978-3-540-89208-3\_85},
  volume       = {22},
  year         = {2009},
}

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