This site allows you to explore computer models of neural computation at levels ranging from simple linear filters to large-scale networks of spiking units. Some of the models are highly simplified and execute rapidly, whereas others involve connections among thousands of neurons and require hours to run. The initial focus is on models of the visual system, from retina to visual cortex; however, the elements and principles developed here can apply to other neural systems.

The goals of this site are of three types:

Scientific: To advance the understanding of computation in neural networks by allowing users to test models easily and thoroughly. This means being able to vary the model parameters, submit a wide variety of stimuli to the models, execute the models quickly, and explore the model outputs conveniently.

Educational: To allow students to learn what is known at a functional level about complex neural systems, such as the visual system, by directly experimenting with classical and state-of-the-art models that emulate the experience of studying the system in experimental labs.

Historical: To facilitate comparisons between classic models from the literature and more recent formulations. This can reveal how the style and sophistication of models are evolving with our understanding of the brain.

While browsing through content on this site, you will have access to the following user interface tools: The site is under active development - not all features are currently available. For more information, contact us.