Saturday, March 6, 2010, LSE Room 104, Arizona State University
8:30 - 12:30 Tutorials on Software for Multiscale Modeling in Neuroscience and Beyond

Details and links for software are below. Note that continental breakfast will be available mid-morning. Participants are encouraged to bring their laptops with relevant software pre-installed. See the websites below for download and installation instructions.
Registration fees: $50 students, $75 postdocs, $100 faculty
Register here.


Tutorial slides or information:
NEURON Slides
PSICS Slides
NeuronVisio slides
Whole Brain Catalog Information

Tutorial Schedule:

8:15 Registration Open

8:30 Whole Brain Catalog, Stephen Larson, University of California San Diego

8:50 NeuroTools & Sumatra, Andrew Davison, Centre National de la Recherche Scientifique

9:10 NeuronVisio, Michele Mattioni, European Bioinformatics Institute, UK

9:30 neuroConstruct & NeuroML, Padraig Gleeson, University College London

9:50 Coffee and Continental Breakfast

10:15-11:15 Parallel Sessions

NEURON, Ted Carnevale, Yale University PyNN, Andrew Davison, Centre National de la Recherche Scientifique SBML, Michael Hucka, Caltech

11:30-12:30 Parallel Sessions

neuroConstruct, Padraig Gleeson, University College London PSICS, Robert Cannon, Textensor


Whole Brain Catalog, http://wholebraincatalog.org
Make new connections with the Whole Brain Catalog, an open source, downloadable, multiscale, virtual catalog of the mouse brain and its cellular constituents.

NeuroTools, http://neuralensemble.org/trac/NeuroTools/
NeuroTools is a collection of tools to support all tasks associated with a neural simulation project, which are not handled by the simulation engine. It provides modules to facilitate simulation setup, parameterization, data management, analysis and visualization.

NeuronVisio, http://mattions.github.com/neuronvisio/
NeuronVisio provides a graphical user interface for the NEURON simulation environment that allows for 3-D visualization of the model, the creation of vectors to record any of the variables, Pylab integration to plot directly simulation results, and the exploration of any variable using a color coded scale.

neuroConstruct, http://neuroconstruct.org
neuroConstruct provides support for developing neuronal network models in 3-D, generating simulation scripts for use in existing simulator environments such as NEURON, GENESIS, MOOSE, PyNN, and PSICS, and automatically generates code to record simulation results for visualization in neuroConstruct.

NeuroML, http://neuroml.org
NeuroML is a collaborative effort to create a description language for complex models of neurons and neuronal networks. The goals of NeuroML are to facilitate the exchange of complex neural models, allow for greater transparency and accessibility of models, enhance interoperability between simulators and other tools, and support the development of new software and databases.

NEURON, http://www.neuron.yale.edu/neuron
NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties.

PyNN, http://neuralensemble.org/trac/PyNN
PyNN is a Python-based, simulator independent language for building neuronal network models. In other words, you can write the code for a model once, using the PyNN API and the Python programming language, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian).

SBML, http://sbml.org
The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biological processes that is applicable to simulations of metabolism, cell signaling, biochemical reactions, gene regulatory networks, and many other topics.

PSICS, http://www.psics.org
PSICS models the behavior of neurons taking account of the stochastic nature of ion channel gating and the detailed positions of the channels themselves. PSICS is intended to be complementary to existing tools. With its focus on kinetic scheme channel models, stochastic behavior, and detailed geometry, it lives in the space between stochastic diffusion models of small sections of neurons (MCell, STEPS) and deterministic whole cell models (Neuron, Genesis).


Participating Units:
School of Mathematical and Statistical Sciences
School of Biological and Health Systems Engineering
School of Life Sciences
Interdisciplinary Graduate Program in Neuroscience


Supported in part by R01 MH081905 from the National Institutes of Health (NIMH),
PI: Sharon Crook, Arizona State University

Additional support: MRC, Wellcome Trust