The Society for Neuroscience (SfN) Neuroscience Database Gateway (NDG) provides extensive access to experimental data databases, knowledge bases, software tools for neuroscience, bioinformatics resources, providers of research materials, and
all neuroscience databases.¹

Databases

1. SenseLab

   The SenseLab Project (hosted by Yale University) is a long term effort to build integrated, multidisciplinary models of neurons and neural systems, using the olfactory pathway as a model. This is one of a number of projects funded as part of the Human Brain Project whose aim is to develop neuroinformatics tools in support of neuroscience research. The project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, and providing for efficient interoperability with other neuroscience databases.

2. ModelDB

   ModelDB (a component of SenseLab) provides an accessible location for storing and efficiently retrieving computational neuroscience models. ModelDB is tightly coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. Click here for help on how to download and/or run models from Senselab’s Model Database.

Neural Simulators

The following guide provides a synopsis provides a summary of some known open-source neural simulators.²

1. DSTOOL

   by John Guckenheimer, Cornell Univ., dynamical systems on Unix machines

2. GENESIS

   by Jim Bower, Cal. Tech., general purpose simulator for neural systems on Unix machines

3. NBC

   by Jean-Francois Vibert, Fac. de Med. St-Antoine, Paris, Network simulation and analysis on Unix and VMS machines

4. NEMOSYS

   by John Tromp, Univ. Cal., Berkeley, complex single neurons on Unix machines

5. NEUROGRAPH

   by Peter Wilke, Univ. Erlangen, Germany, Simulation of artificial neural networks on Unix, DOS, VMS machines

6. NEURON

   by Michael Hines, Duke Univ., Simulations of biologically realistic single neurons and small networks on PCs and Unix machine

   NEURON is a simulation environment for developing and exercising models of neurons and networks of neurons. It is particularly well-suited to problems where cable properties of cells play an important role, possibly including extracellular potential close to the membrane), and where cell membrane properties are complex, involving many ion-specific channels, ion accumulation, and second messengers.³

   For more information NIL’s use of NEURON see our NEURON Simulator Programming Guide.

7. NEURONC

   by Rob Smith, Univ. Penn., compartmental simulations of large neural circuits on Unix machines

8. NODUS

   by Eric De Schutter, Univ. Antwerp, Belgium, simulation of small networks of neurons on Macintosh machines

9. NSL

   by Alfredo Weitzenfeld, Univ. Sou. Cal., simulation of large networks on Unix machines

10. SNNAP

    by John Byrne, Univ. Texas, Houston, Simulator for neural networks on Unix machines

11. SWIM

    by Orjan Ekeberg, Royal Inst. Tech., Stockholm, simulation of network of few compartment model neurons on Unix machines

Tool Sets

Blue Brain Project

“In July 2005, EPFL and IBM announced an exciting new research initiative – a project to create a biologically accurate, functional model of the brain using IBM’s Blue Gene supercomputer. Analogous in scope to the Genome Project, the Blue Brain will provide a huge leap in our understanding of brain function and dysfunction and help us explore solutions to intractable problems in mental health and neurological disease.”

• Markram, H. (2006). The blue brain project.. Nat Rev Neurosci, 7, 153-60.
• Migliore, M., Cannia, C., Lytton, W. W., Markram, H. & Hines, M.L. (2006). Parallel network simulations with NEURON.. J Comput Neurosci, 21, 119-29.

Neuronal Time Series Analysis (NTSA) Workbench

A Database System for Neuronal Pattern Analysis

“Biologically-detailed neural simulations of the type supported by software packages such as GENESIS (developed in Jim Bower’s laboratory at Cal Tech) and NEURON (developed by Michael Hines and John Moore at Duke) are typically used to generate time-series data of the same general form as data collected in neurophysiological experiments. The volume of time-series data produced in a typical simulation study is often comparable to, or in some cases much greater than, the amount of data yielded in physiological experiments. The uniform interface that NTSA Workbench presents to both experimental and simulated data greatly facilitates comparison of modeling results with experimental data.”⁴ The status of this project is unknown as all links to the actual project are dead.

References

1. Society for Neuroscience (SfN) Neuroscience Database Gateway (NDG), http://ndg.sfn.org/ [↩]
2. Moore, J. & Hines, M., http://neuron.duke.edu/, (1994 [↩]
3. Society for Neuroscience (SfN) Neuroscience Database Gateway (NDG), http://ndg.sfn.org/ [↩]
4. http://www.nimh.nih.gov/neuroinformatics/mgabriel.cfm [↩]