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eNeuro. 2019 Aug 12;6(4). pii: ENEURO.0059-19.2019. doi: 10.1523/ENEURO.0059-19.2019. Print 2019 Jul/Aug.

Background EEG Connectivity Captures the Time-Course of Epileptogenesis in a Mouse Model of Epilepsy.

Author information

1
College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, United Kingdom p.m.slowinski@exeter.ac.uk.
2
Translational Research Exchange @ Exeter (TREE), University of Exeter, Exeter, EX4 4QD, United Kingdom.
3
Functional Brain Mapping Lab, Department of Fundamental Neuroscience, Campus Biotech, University of Geneva, Geneva, 1202, Switzerland.
4
Centre for Biomedical Imaging (CIBM), Lausanne and Geneva, Lausanne, 1015, Switzerland.
5
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, United Kingdom.
6
Department of Fundamental Neuroscience, Faculty of Medicine, Geneva, 1206, Switzerland.
7
College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, United Kingdom.
8
Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, EX4 4QD, United Kingdom.
9
EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, EX4 4QD, United Kingdom.

Abstract

Large-scale brain networks are increasingly recognized as important for the generation of seizures in epilepsy. However, how a network evolves from a healthy state through the process of epileptogenesis remains unclear. To address this question, here, we study longitudinal epicranial background EEG recordings (30 electrodes, EEG free from epileptiform activity) of a mouse model of mesial temporal lobe epilepsy. We analyze functional connectivity networks and observe that over the time course of epileptogenesis the networks become increasingly asymmetric. Furthermore, computational modelling reveals that a set of nodes, located outside of the region of initial insult, emerges as particularly important for the network dynamics. These findings are consistent with experimental observations, thus demonstrating that ictogenic mechanisms can be revealed on the EEG, that computational models can be used to monitor unfolding epileptogenesis and that both the primary focus and epileptic network play a role in epileptogenesis.

KEYWORDS:

background EEG; epilepsy; epileptogenesis; functional networks; model

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