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A small change in neuronal network topology can induce explosive synchronization transition and activity propagation in the entire network.


ABSTRACT: We here study explosive synchronization transitions and network activity propagation in networks of coupled neurons to provide a new understanding of the relationship between network topology and explosive dynamical transitions as in epileptic seizures and their propagations in the brain. We model local network motifs and configurations of coupled neurons and analyze the activity propagations between a group of active neurons to their inactive neuron neighbors in a variety of network configurations. We find that neuronal activity propagation is limited to local regions when network is highly clustered with modular structures as in the normal brain networks. When the network cluster structure is slightly changed, the activity propagates to the entire network, which is reminiscent of epileptic seizure propagation in the brain. Finally, we analyze intracranial electroencephalography (IEEG) recordings of a seizure episode from a epilepsy patient and uncover that explosive synchronization-like transition occurs around the clinically defined onset of seizure. These findings may provide a possible mechanism for the recurrence of epileptic seizures, which are known to be the results of aberrant neuronal network structure and/or function in the brain.

SUBMITTER: Wang Z 

PROVIDER: S-EPMC5428839 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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A small change in neuronal network topology can induce explosive synchronization transition and activity propagation in the entire network.

Wang Zhenhua Z   Tian Changhai C   Dhamala Mukesh M   Liu Zonghua Z  

Scientific reports 20170403 1


We here study explosive synchronization transitions and network activity propagation in networks of coupled neurons to provide a new understanding of the relationship between network topology and explosive dynamical transitions as in epileptic seizures and their propagations in the brain. We model local network motifs and configurations of coupled neurons and analyze the activity propagations between a group of active neurons to their inactive neuron neighbors in a variety of network configurati  ...[more]

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