archives@tulane.edu / The thalamocortical network generates rhythmic oscillations of various frequencies that underlie different brain states. Importantly, the transition from a faster frequency of firing, spindle, to slower oscillations, spike and wave discharges, is indicative of the pathological epileptic seizure development. Previous investigations have shown that the complex interactions between neurons in the thalamocortical network based on intrinsic and synaptic properties give rise to the observed frequency changes. However, the exact mechanism of how perturbations in this circuit disrupt the oscillations is not known. In this project, we used a well-established thalamocortical network computational model to perform receptor conductance changes to see how the oscillatory activity in the thalamocortical network changes. Computational methods can be used to provide some mathematical explanations regarding the mechanism of oscillations. Therefore, we generated several phase resetting curves by perturbing neurons during its oscillating period. Our results showed that the frequency reduction under the pathological state in the thalamocortical network might be caused by hyper-synchronization of neuronal activities in this circuit mediated by glutamatergic AMPA receptors. Notably, thalamic reticular neurons are capable of firing at a faster or slower frequency depending on the timing of the input that they receive from other neurons. Overall, our results provided evidence to support the hypothesis that thalamic reticular neurons might be the ultimate pacemakers in the thalamocortical network. / 1 / Hanyun Wang