Modeling population network activity using lfpsim, spiking neurons and neural mass models

Local Field Potentials arising (LFP) from neural circuits are crucial to understand neural ensemble activity and can act as a link between molecular, cellular and circuit neuroscience. Additionally, mathematical estimations of LFPs allow the study of circuit functions and dysfunctions. In this study, we used mathematical reconstructions of LFP in rat cerebellum Crus IIa using spiking neuronal models and mass models based on lumped parameters to reconstruct the averaged ensemble activity. Comparing experimentally validated reconstructions of evoked LFPs using detailed multi-compartmental models, spiking neurons and lumped mass models suggest variations at the translational levels of biophysical mechanisms in granular layer. With the focus of reconnecting multiple information roles, our simulations studies indicate multi-compartmental detailed models allow estimations on the role of transmembrane currents, spiking neuron models suggest contributions of action potentials while mass models reveal averaged activity behaviour underlying Crus IIa evoked LFPs.