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.