Synaptic Role in Facilitating Synchronous Theta Oscillations in a Hybrid Hippocampal Neuronal Network

Theta rhythms (4–12 Hz) in the hippocampus are thought to be associated with cognitive functions such as memory processing and spatial navigation. Rhythmic oscillations in the neural system can be induced by synchronization of neural populations, while physiological mechanisms for the emergence, modulation, and regulation of such rhythms are not fully understood. Conceptual reduced models are promising in promoting current understandings toward neural synchronization because of high computational efficiency, while they appear less straightforward in biological relevance. In this study, we use a hybrid E-I network as a conceptual model of the hippocampus to investigate the dynamics of synchronous theta oscillations. Specifically, experimentally constrained Izhikevich neurons and preferential connections among neural groups specific to hippocampal CA1 are incorporated to enhance the biological relevance of the model network. Based on such a model, synaptic factors related to the balance of network excitation and inhibition are the main focus of present study. By careful parameter exploration, the distinct role of synaptic connections in theta rhythm generation, facilitation of synchronization, and induction of burst activities are clarified. It is revealed that theta rhythms can be present with AMPA mediated weak E-I couplings, or with strong NMDA current. Moreover, counter-inhibition, namely inhibition of inhibition, is found effective in modulating the degree of network synchronization, while has little effect on regulating network frequency in both regimes. Under pathological considerations where the effect of pyramidal sprouting is simulated, synchronized burst patterns are observed to be induced by elevated recurrent excitation among pyramidal cells. In the final part, we additionally perform a test on the robustness of our results under heterogeneous parameters. Our simulation results may provide insights into understanding how brain rhythms are generated and modulated, and the proposed model may serve as a useful template in probing mechanisms of hippocampal-related dynamics.