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The dominant modeling framework for understanding cortical computations areheuristic firing rate models. Despite their success, these models fall short tocapture spike synchronization effects, to link to biophysical parameters and todescribe finite-size fluctuations. In this opinion article, we propose that therefractory density method (RDM), also known as age-structured populationdynamics or quasi-renewal theory, yields a powerful theoretical framework tobuild rate-based models for mesoscopic neural populations from realistic neurondynamics at the microscopic level. We review recent advances achieved by theRDM to obtain efficient population density equations for networks ofgeneralized integrate-and-fire (GIF) neurons -- a class of neuron models thathas been successfully fitted to various cell types. The theory not onlypredicts the nonstationary dynamics of large populations of neurons but alsopermits an extension to finite-size populations and a systematic reduction tolow-dimensional rate dynamics. The new types of rate models will allow are-examination of models of cortical computations under biological constraints.

Mind the Last Spike -- Firing Rate Models for Mesoscopic Populations of Spiking Neurons