Çiftçi, Koray2024-10-292024-10-2920242757-5195https://doi.org/10.28979/jarnas.1140961https://search.trdizin.gov.tr/tr/yayin/detay/1228862https://hdl.handle.net/20.500.11776/13008Synchronization is a property of complex systems that manifests itself as the emergence of collective behavior from local interactions. Neurons are the basic building blocks of the nervous system, and in neuronal networks, the firing times of the neurons get synchronized via the electrical and chemical synapses among them. This property has been observed in both computational models and experimental studies. However, this synchronization's mechanisms have not yet been totally revealed. Here, we investigate the synchronization properties of quadratic integrate and fire (QIF) neurons from a computational modeling perspective. QIF neurons are simple yet effective models in the sense that they have the ability to capture complex behavior observed in neurons. We present analytical results concerning the spiking frequency of the QIF neurons and the relationships between membrane voltage and phase of the neurons. We give simulation results for a simple network of all-to-all coupled QIF neurons, demonstrating the effects of different types of coupling among the network members. We show that electrical and inhibitory chemical synapses play complementary roles in the formation of synchronized behavior in a neuronal network. Our results contribute to our understanding of the brain to produce cognitive abilities and coordinated action.en10.28979/jarnas.1140961info:eu-repo/semantics/openAccessSynchronizationneuronphaseIntegrate and fireArticle10180901228862