Introduction to NeuroML

NeuroML is (as of this writing) the most extensive data format to describe models of spiking neural networks (SNN’s) (and generally dynamic neural networks), outside the context of a specific simulation system. NeuroML version 2 (i.e. the latest one) relies on the LEMS language for defining new (ODE and event-based) dynamics for the various parts that constitute a neural network. EDEN runs models that are described in this NeuroML-v.2 (plus LEMS) data format.

This part introduces the basic concepts of NeuroML (in its second version) and LEMS, and how these can be applied to construct full-featured models of dynamic neural networks.

• Quickstart
  • Get EDEN
  • Get a NeuroML model
  • Run the NeuroML model with EDEN
  • Show the results
  • Done!
• NeuroML basics
  • Creating a simulation
  • Adding a neuron and recording output
  • Adding stimuli
  • Adding more neurons and synapses
  • Adding more cell types and spike sources
  • Adding graded interactions
  • NeuroML file structure conventions
• Detailed cells with NeuroML
  • Putting together a cell type
  • Peeking at the neuron model’s structure
  • The morphology of the cell
  • The biophysics of the cell
  • Example: Modelling and simulating a stretch of neural cable
  • More resources on spatially-detailed modelling
  • Next steps
• LEMS basics
  • What is a LEMS component?
  • What is a LEMS ComponentType?
  • How can LEMS components be used in NeuroML models?