Conductance-Based Adaptive Exponential Integrate-and-Fire Model

The intrinsic electrophysiological properties of single neurons can be described by a broad spectrum models, from realistic Hodgkin-Huxley-type models with numerous detailed mechanisms to the phenomenological models. adaptive exponential integrate-and-fire (AdEx) model has emerged as convenient middle-ground model. With low computational cost but keeping biophysical interpretation parameters, it been extensively used for simulations large neural networks. However, because its current-based adaptation, generate unrealistic behaviors. We show limitations AdEx model, and avoid them, we introduce conductance-based (CAdEx). give an analysis dynamics CAdEx variety firing patterns produce. propose richer alternative perform network simplified reproducing neuronal properties.