A fast model of voltage-dependent NMDA receptors.

NMDA receptors are among the crucial elements of central nervous system models. Recent studies show that both conductance and kinetics of these receptors are changing voltage-dependently in some parts of the brain. Therefore, several models have been introduced to simulate their current. However, on the one hand, kinetic models-which are able to simulate these voltage-dependent phenomena-are computationally expensive for modeling of large neural networks. On the other hand, classic exponential models, which are computationally less expensive, are not able to simulate the voltage-dependency of these receptors, accurately. In this study, we have modified these classic models to endow them with the voltage-dependent conductance and time constants. Temperature sensitivity and desensitization of these receptors are also taken into account. We show that, it is possible to simulate the most important physiological aspects of NMDA receptor's behavior using only three to four differential equations, which is significantly smaller than the previous kinetic models. Consequently, it seems that our model is both fast and physiologically plausible and therefore is a suitable candidate for the modeling of large neural networks.