This course emphasizes practical issues that are key to the most productive use of NEURON, an advanced simulation environment for realistic modeling of biological neurons and neural circuits. Through lectures and live computer demonstrations, we will address topics that include the following:
- Efficient design and implementation of models of neurons and networks.
- Constructing and managing models with NEURON’s GUI, hoc, and Python.
- Using the built-in variable-order variable-timestep integrator for improved speed and accuracy.
- Parallelizing models of cells and networks to take advantage of multicore PCs and Macs, workstation clusters, and parallel supercomputers.
- Expanding NEURON’s repertoire of biophysical mechanisms.
- Implementing models that involve reactive diffusion.
- Databases for empirically-based modeling.
Each registrant will receive a comprehensive set of notes. Coffee breaks and lunch are provided.
- Examine an introductory lecture from the 1997 SFN course. This tutorial should help you get started creating your own models and using NEURON's graphical interface.
Check the Documentation page for a link to the CellBuilder tutorial, which is based on a lesson presented at the 1999 SFN course.
Learn how to use the Network Builder to create network models that contain artificial neural elements and biophysically-based neural models. These tutorials are based on a presentation from the 2000 SFN course.