Computational Neuroscience combines elements of neuroscience, mathematics, and computer technology to examine the operational algorithms underlying neural networks. Both a fundamental and an applied discipline, Computational Neuroscience seeks to understand information processing in the brain and to address challenges in artificial intelligence, machine learning, and medical devices like neural prosthetics and brain implants.
With some additional mathematics courses, Neuroscience students with strong quantitative skills can participate in research at labs across the Pitt and CMU campuses that specialize in Computational Neuroscience. Exceptional students may also qualify for fellowship support in the Program in Neural Computation (PNC).
Interested students are encouraged to contact Dr. Brent Doiron (brent.doiron@gmail.com) in the Department of Mathematics at Pitt or Dr. Nathan Urban (nurban@cmu.edu) in the Department of Biology at CMU.
Recommended Coursework:
- MATH 0220 Calculus 1
- MATH 0230 Calculus 2
- MATH 0290 Applied Differential Equations
- MATH 1800 Introduction to Mathematical Neuroscience
Fellowship in Computational Neuroscience
Faculty with Computational Neuroscience Research:
*faculty with primary or secondary appointments in the Department of Neuroscience
Center for Neuroscience at the University of Pittsburgh - CNUP
German Barrionuevo* - Synaptic physiology in hippocampus and prefrontal cortex
Aaron Batista - Sensory-motor integration and neural prosthetics
G. Bard Ermentrout - Computational and theoretical models of neural and muscle physiology
Neeraj Gandhi* - Neural control of coordinated oculomotor and skeletomotor movements
John Horn - Synaptic integration in sympathetic ganglia and in midbrain dopamine neurons
Jon Johnson* - Biophysics, pharmacology, and regulation of glutamate receptors
Robert Kass* - Bayesian statistics and statistical analysis of neuronal data
Paul Munro - Abstract mathematical and computational principles underlying learning at the synaptic, neuronal, and systems levels
Tai Sing Lee* - Computational and electrophysiological study of visual perception, perceptual organization, neural plasticity and neural coding; computer vision
Steven A. Prescott - Computational neuroscience, neuronal excitability, and central mechanisms of pain
Erik. D. Reichle - Computational models of eye-movement control during reading; the neural systems mediating the "eye-mind" link
Jonathan Rubin - Theoretical and computational modeling of dynamics in neuronal networks
Walter Schneider - Cognitive neuroscience, semantic representation, skill acquisition, connectionist/hybrid modeling, brain imaging
Andrew Schwartz - Cerebral basis for volitional movement and cortical neural prosthetics
Joel Stiles -Spatially realistic simulations of neurotransmitter release, synaptic transmission and plasticity
Robert Turner -Neurophysiology of basal ganglia-cortical networks in health and disease
Nathaniel N. Urban* - Physiology imaging and computation in the olfactory system
Additional faculty can be found on the website for the: