University of Pittsburgh

Department of Neuroscience

Computational Neuroscience

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 ( in the Department of Mathematics at Pitt or Dr. Nathan Urban ( 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:

Center for the Neural Basis of Cognition - CNBC