Neural mass models provide a useful framework for modelling mesoscopic neural dynamics. We briefly introduce a generalized form of neural mass models, which turn out to be stochastic functional differential equations (SFDEs) with distributed memory terms. We solve these equations numerically with a Theta-Maruyama scheme.
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