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 Research

The Computational Neuroscience research area is focused on understanding neural systems using computational analyses and biologically plausible modeling approaches. This approach can be used to test specific hypotheses concerning a range of neural computations, from membrane dynamics to large-scale cortical systems.

 Affiliated Faculty

Distinguished Professor
Psychological & Brain Sciences
Professor Ashby is interested in the basic cognitive and neural mechanisms that mediate human learning. His approach combines experimental psychology, cognitive neuroscience, and mathematical modeling.
Assistant Professor
Computer Science
Psychological & Brain Sciences
Computational Vision, Computational Neuroscience, Neuroengineering, Human-Computer Interaction.
Professor
Department of Physics
Cognitive neuroscience, learning, memory, categorization, decision processes in perception and cognition.
Assistant Professor
Mechanical Engineering
Neural & cardiovascular tissue engineering/regenerative medicine. Stem cells, mechanobiology, molecular control systems.
Professor
Psychological & Brain Sciences
Dr. Eckstein is interested in how biological organisms and artificial intelligent agents visually sense the world and make decisions. He uses computational modeling, cognitive neuroscience and behavioral measurement techniques.
Associate Professor
Psychological & Brain Sciences
Molecular, Cellular and Developmental Biology
The Goard lab focuses on how the mammalian neocortex processes and stores incoming sensory information.
Professor
Psychological & Brain Sciences
Spatial and temporal organization of stochastic axon systems in the brain.
Assistant Professor
Molecular, Cellular, and Developmental Biology
Neural circuit dynamics and behavior; navigation in a visual environment; neural mechanisms of object selection and decision-making.
Associate Professor
Molecular, Cellular, and Developmental Biology
Combining theory and experimentation to understand how navigational decisions come about in terms of neural-circuit computation.
Professor
Statistics and Applied Probability
Statistical Methods and Data Analyses, Including For Brain Imaging and Other Neuroscience Data; Statistical Methods for Analyzing Spatial and Temporal Processes; Computational Statistics and Machine Learning; Uncertainty Quantification.
Professor
Department of Mechanical Engineering
Dynamics and control of neural populations for treatment of Parkinson's disease, coupled oscillators, synchronization, decision making, biological dynamics, machine learning.
Distinguished Professor
Mechanical Engineering
Computer Science
Computational methods, mathematical modeling, and machine learning, with application to a wide range of problems from systems biology, neuroscience and engineering.
Professor
Computer Science
Data-centric modeling of systems and he focuses on the development of new methods that can be applied to real-world applications.
Associate Professor
Electrical and Computer Engineering
Exploring neural circuitry and illuminating its function, using new neurotechnology.
Assistant Professor
Psychological & Brain Sciences
In the Perception, Cognition, and Action Lab (PCA Lab), we seek to understand how the brain encodes and transforms neural representations of sensory information in service of dynamic behavioral demands.
Assistant Professor
Department of Physics
We use ideas and concepts from physics, computer science, and mathematics to ask how embryos get in shape, and how organs function.
Professor
Electrical & Computer Engineering
Novel reporters for neural activity, CMOS image sensors and circuits for neurotechnology.
Professor
Department of Communication
In the Media Neuroscience Lab (MNL) we study attention disorders and media-multitasking, aggressive conduct disorders and media violence, moral conflict and narrative performance, and the neural mechanisms of persuasion, flow experiences, and general cognitive control.