Computational neuroscience uses mathematical models, computer simulations, and statistical analyses to understand the workings of the brain, nervous system, and behavior. Researchers in this field come with diverse backgrounds ranging from biology and psychology to physics, mathematics, statistics, computer science, and engineering.
For example, questions addressed by our computational neuroscientists include:
- How do sensory neurons transmit information about the outside world?
- How do neural circuits of the brain produce, and learn to produce, coordinated motor outputs?
- How are memories stored and recalled by the brain?
- How are appropriate decisions made from unreliable evidence?
- How can we decode the brain’s motor intentions and use this to control prosthetic devices?
- How can we use data to statistically infer which neurons are communicating with each other?
- How does the shape of the brain change with age, vascular disease and dementia?
- How do the biophysical properties of individual neurons and synapses contribute to the function of whole networks?
- How do the information processing strategies used by the brain differ from those used by computers?
Faculty studying computation
- Evan Antzoulatos, PhD
- Kenneth Britten, PhD
- Marie Burns, PhD
- William DeBello, PhD
- Charles DeCarli, MD
- Jochen Ditterich, PhD
- Mark Goldman, PhD
- Tim Hanks, PhD
- Alex Nord, PhD
- Gregg Recanzone, PhD
- Mitchell Sutter, PhD
- W. Martin Usrey, PhD