NineML - Network Interchange format for Neuroscience

• Well-defined and flexible syntax
• Easy to extend
• Basis for specific implementations covering a wide range of modeling scales
• Focusses on describing a growing area of computational neuroscience, networks of single compartment neurons
• Provides abstract representation of nonlinear dynamics

This language is based on a layered approach: an abstraction layer allows a full mathematical description of the models, including events and state transitions, while the user layer contains parameter values for specific models.

A major challenge in modeling is the absence of widely adopted standards for model description, which hampers reproduction of simulation results, compatible programs, innovative software development and benchmarking of existing simulators.

The INCF therefore appointed a Task Force that developed a markup language for model description, with a well-defined and flexible syntax that will be easy to extend and that forms the basis for specific implementations covering a wide range of modeling scales. The initial effort focuses on describing a growing area of computational neuroscience, spiking networks.

Visualization of the dynamics block for an example NineML component