Homeostatic dopamine release is essential for the proper function of the brain, and the disruption of the dopaminergic system leads to neurological disorders. Currently, there is a lack of efficient and integrated models that allow linking in one model the molecular and neuronal circuit levels of the dopaminergic system. Here, the researchers try to develop a realistic computational model that efficiently represents a dopaminergic pre-synaptic terminal. Starting from an already established computational model, it was possible to simplify it and reduce it to two time-scale models. Moreover, both the original and the reduced model have similar dynamics, while the reduced version is more computationally efficient and can be used to investigate underlying key mechanisms. Finally, this reduced model was combined with a spiking neuronal model, with a later inclusion of an autoreceptor-mediated inhibitory current, to realistically simulate dopaminergic neuronal behaviour. In conclusion, a new integrated computational model is developed and represents the first steps towards an efficient computational platform to simulate the dopaminergic system, which could have great potential in drug discovery and development.
Integrated dopaminergic neuronal model with reduced intracellular processes and inhibitory autoreceptors
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