Synchronization in model plastic neuronal networks through synaptic re-organization

Abnormally strong neural synchronization may impair brain function, e.g., in Parkinson's disease and epilepsy. To examine how neuronal activity and synaptic organization shape each other during (de)synchronization, we use networks of excitatory integrate-and-fire neurons with synaptic weight and structural plasticity. We employ spike-timing-dependent plasticity to model synaptic weight changes and a firing rate and synaptic-weight-dependent structural plasticity rule. We show that the random networks of neurons with spike-timing-dependent plasticity alone may settle in partially or completely synchronized states besides desynchronized states. The synaptic re-organization due to structural plasticity enhances synchrony. When weaker contacts are preferentially removed, enhanced synchrony can be achieved with significantly fewer contacts. We show that the numbers of pre- and post-synaptic partners depend on the firing rates of the neurons. The degree-frequency and degree-degree correlations, and a mixture of degree assortativity emerge in synchronized states. We then show that networks evolving with structural plasticity require a higher level of stimulus intensity to transition from synchronized to desynchronized states.