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

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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
1 . Fardet T, Levina A (2020) Simple Models Including Energy and Spike Constraints Reproduce Complex Activity Patterns and Metabolic Disruptions PLOS Computational Biology 16:e1008503 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Abstract integrate-and-fire adaptive exponential (AdEx) neuron; Abstract integrate-and-fire leaky neuron; Abstract integrate-and-fire neuron;
Gap Junctions:
Simulation Environment: Brian 2; NEST; NEURON;
Model Concept(s): Depolarization block; Anoxic depolarization; Energy consumption; Rebound firing; Simplified Models; Spike Frequency Adaptation;
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