Excerpts from three papers abstracts: "Brain neurons exhibit complex electroresponsive properties – including intrinsic subthreshold oscillations and pacemaking, resonance and phase-reset – which are thought to play a critical role in controlling neural network dynamics. Although these properties emerge from detailed representations of molecular-level mechanisms in “realistic” models, they cannot usually be generated by simplified neuronal models (although these may show spike-frequency adaptation and bursting). We report here that this whole set of properties can be generated by the extended generalized leaky integrate-and-fire (E-GLIF) neuron model. ..." "... In order to reproduce these properties in single-point neuron models, we have optimized the Extended-Generalized Leaky Integrate and Fire (E-GLIF) neuron through a multi-objective gradient-based algorithm targeting the desired input–output relationships. ..." " ... In order to investigate how single neuron dynamics and geometrical modular connectivity affect cerebellar processing, we have built an olivocerebellar Spiking Neural Network (SNN) based on a novel simplification algorithm for single point models (Extended Generalized Leaky Integrate and Fire, EGLIF) capturing essential non-linear neuronal dynamics (e.g., pacemaking, bursting, adaptation, oscillation and resonance). ..."
Region(s) or Organism(s): Cerebellum
Cell Type(s): Abstract integrate-and-fire leaky neuron
Simulation Environment: NEST
Geminiani A, Casellato C, D'Angelo E, Pedrocchi A. (2019). Complex Electroresponsive Dynamics in Olivocerebellar Neurons Represented With Extended-Generalized Leaky Integrate and Fire Models. Frontiers in computational neuroscience. 13 [PubMed]
Geminiani A, Pedrocchi A, D'Angelo E, Casellato C. (2019). Response Dynamics in an Olivocerebellar Spiking Neural Network With Non-linear Neuron Properties. Frontiers in computational neuroscience. 13 [PubMed]