Abstract
Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures.
Original language | English |
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Article number | 19 |
Number of pages | 8 |
Journal | Frontiers in Computational Neuroscience |
Volume | 13 |
DOIs | |
Publication status | Published - 5 Apr 2019 |
Bibliographical note
FUNDINGThis study was possible by partial financial support from
the following Brazilian government agencies: Fundação
Araucária, CNPq (433782/2016-1, 310124/2017-4, and
428388/2018-3), CAPES, and FAPESP (2015/50122-0,
2015/07311-7, 2016/16148-5, 2016/23398-8, 2017/13502-5,
2017/18977-1, 2018/03211-6).
ACKNOWLEDGMENTS
We also wish to thank the Newton Fund, COFAP, and
International Visiting Fellowships Scheme of the University of
Essex. We also thank IRTG 1740 for support.
Keywords
- Adaptive exponential integrate-and-fire neural model
- Bistable regime
- Epilepsy
- Network
- Neural dynamics
- Synchronization