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.
Highlights
Epilepsy is a brain disease that causes seizures and sometimes loss of consciousness (Chen et al, 2014, 2015)
Wang et al (2017) presented results where synchronization transition occurs as a result of small changes in the topology of the network, whereas here, we study transitions caused due to changes in the inhibitory synaptic strength and the emergence of a bistable regime
We studied the influence of inhibitory synapses on the appearance of synchronized and desynchronized fire patterns in a random network with adaptive exponential integrate-andfire neural dynamics
Summary
Epilepsy is a brain disease that causes seizures and sometimes loss of consciousness (Chen et al, 2014, 2015). Epileptic seizures are associated with excessively high synchronous activities (Li et al, 2007; Jiruska et al, 2013; Wu et al, 2015) of neocortex regions or other neural populations (Fisher et al, 2005; Sierra-Paredes and Sierra-Marcuño, 2007; Engel et al, 2013; Geier and Lehnertz, 2017; Falco-Walter et al, 2018). Traub and Wong (1982) showed that synchronized bursts that appear in epileptic seizures depend on neural dynamics The reduction of excitatory and the increase of inhibitory influence have been effective in suppressing and preventing synchronized behaviors (Traub et al, 1993; Schindler et al, 2008). Traub and Wong (1982) showed that synchronized bursts that appear in epileptic seizures depend on neural dynamics
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
