eLIF and mAdExp: energy-based integrate-and-fire neurons (Fardet and Levina 2020)

The eLIF and mAdExp neurons respectively extend the leaky integrate-and-fire and adaptive exponential (AdExp) neuron models. They include a new variable modelling the availability of energy substrate and model constraints that energy availability may have on the subthreshold and spiking dynamics. In the paper, we show how these models can reproduce complex dynamics and prove especially useful to model metabolic disruption, for instance in large-scale models of epilepsy or other diseases with metabolic components, such as Alzheimer, or Parkinson. Git repository: https://git.sr.ht/~tfardet/elif-madexp

Model Type: Neuron or other electrically excitable cell

Cell Type(s): Abstract integrate-and-fire adaptive exponential (AdEx) neuron; Abstract integrate-and-fire leaky neuron; Abstract integrate-and-fire neuron

Model Concept(s): Depolarization block; Anoxic depolarization; Energy consumption; Rebound firing; Simplified Models; Spike Frequency Adaptation

Simulation Environment: Brian 2; NEST; NEURON


Fardet T, Levina A. (2020). Simple Models Including Energy and Spike Constraints Reproduce Complex Activity Patterns and Metabolic Disruptions PLoS computational biology. 16 [PubMed]

This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.