Theoretical and computational approaches are playing an increasingly important role in the study of brain and behavior, helping to bridge the wide gap between our understanding of neural mechanisms and cognitive phenomena. There are a significant number of NACS faculty working on high-level computational models of brain function as well as artificial systems drawing on principles of neural computing. Research often involves collaborative efforts between individuals who are in the biological/cognitive departments and/or in the computer science and engineering departments, and is part of the more general effort in Theory and Computational Modeling within the NACS program.

Computational researchers are scattered throughout the program, but are most prominent within the sensorimotor integration and neuromorphic engineering, speech and language, and auditory neuroscience groups within NACS.

Prospective students should visit individual faculty, laboratory and departmental web sites for further information on individual research projects, course offerings, facilities, etc.

Faculty Members

Aloimonos, Yiannis, Computer Science

The research of Professor Aloimonos is devoted to the principles governing the design and analysis of real-time systems that possess perceptual capabilities, for the purpose of both explaining animal vision and designing seeing machines.

Anderson, Michael, Computer Science

Butts, Daniel A., Biology

The NeuroTheory Lab at University of Maryland operates at the interface of neuroscience experiment and theory, using experiments performed by collaborators to ground and validate conceptual frameworks and analytical methodology, and theory to guide experiment design and analysis. Our projects are largely focused on the visual system, where we are studying visual computation in the context of simulated "natural vision" experiments across multiple visual areas (retina, LGN, cortex). There are also projects in other areas including the auditory system, as well as studying synaptic plasticity and brain development. A key component of these projects is the study of how the computations performed by neurons explicitly use time: for example in the temporal patterns of spikes, the relationship to brain rhythms, and particular patterns of activity across neurons.

Chen, Shuo, Public & Community Health

Statistical modeling for neuroimaging data; machine learning; Bayesian methods; spatial temporal modeling; connectivity analysis.

De Claris, Nicholas, Divison of Medical Information, Elec. & Computer Eng

Dr. DeClaris' research interests are in the areas of system science, computer engineering, and medical science and practice.

Depireux, Didier, Institute for Systems Research

With grant support from DoD, we measure the changes, at the level of the activity of single neurons over many weeks, correlated with the induction of tinnitus (ringing in the ears) following noise trauma. Specifically, the research uses behavioral measures to verify the emergence of tinnitus post-trauma, chronic electrode arrays to measure and compare the activity of large populations of single neurons before and after induction of tinnitus, and post-mortem immunocytochemical methods to uncover permanent changes in the brain. The Ear Lab wants to explore new drug delivery or stimulation methods that might prevent the induction of, or provide relief from, tinnitus, a common affliction that has received very little scientific attention until recently.

Gentili, Rodolphe, Kinesiology

Dr. Gentili's research focuses on the neural and computational principles underlying (overt, covert) sensorimotor performance and learning in Human, allowing then, a future implementation of similar principles for adaptive control of anthropomorphic robotic systems.

Horiuchi, Timothy, Elec. & Computer Eng

Dr. Horiuchi's research program is centered on the development of neural models of sensorimotor behavior and their implementation in VLSI for use in robotic demonstration systems. The laboratory is currently focused on bat echolocation and other auditory and visual projects.

Jacobs, David, Computer Science

My research has spanned a range of topics in vision. My primary focus has been on the problem of how to recognize objects in images. This is a central problem in vision that I find particularly fascinating because it lies between concrete, lower-level vision problems and central cognitive systems that attempt to tie semantics to the world. It is also a critical problem in many applications in multimedia and robotics. I have also done quite a bit of work in the computational and psychological study of perceptual organization. This is the lower level problem of how to identify the surfaces of potential objects before recognizing them. I see perceptual organization as integral to the recognition process, and in part my work attempts to show how these two problems can be unified.

McDonald, Craig, Assistant Professor, George Mason University ,

One line of research involves the study of the effects of adolescent nicotine exposure on neurocognitive functioning. I am specifically interested in evaluating whether executive control is compromised in individuals who smoke. I am also interested in understanding the neural processes linked to perceptual decision-making. Specifically, I am investigating how attentional processes enable appropriate behavioral control when perceptual discrimination is difficult. My research takes advantage of electroencephalographic (EEG) recording techniques to characterize the neural underpinnings of neurocognitive function and visual perception.

Reggia, James, Computer Science

Research interests: computational models of hemispheric specialization and lateralization, recovery following brain damage, evolution of neural networks, adaptation, and emergent communication.

Zaghloul, Kareem, National Institutes of Health

Research in our lab focuses on understanding the neural correlates of human cognitive function using intracranial recordings captured during epilepsy surgery and deep brain stimulation surgery. In both cases, our lab seeks to record single unit spike activity and local field potential activity directly from the human brain of neurosurgical patients as these patients participate in different cognitive tasks, and to use computational techniques to establish how these signals correlate with different human behaviors. The larger goal of this work centers around understanding the neural code mediating such cognitive processes as memory, decision, and attention. By exploring these questions, we hope to not only gain an understanding of how the human brain processes and relays information, but to potentially open up new possibilities to directly communicate with the brain's complex networks.