Find A PhysicianHome  |  Library  |  myDownstate  |  Newsroom  |  A-Z Guide  |  E-mail  |  Contact Us  |  Directions
curve gif
Photo of William W. Lytton

William W. Lytton

Professor of Physiology and Pharmacology, Neurology, Biomedical Engineering
M.D. (1983, Columbia College of Physicians & Surgeons)
Tel: (718) 270-6789 • e-mail: bill.lytton@downstate.edu


Computational Neuroscience

I use computational neuroscience to try to forge links between disparate findings from normal and abnormal brain function. Primary research areas are modeling electrophysiological processes pertinent to epilepsy and modeling abstract neural networks to understand recovery from stroke and the basis of cognitive processes.

A principal difficulty in trying to understand brain function, and dysfunction, is that the research entails everything from the behavior of molecules up to the behavior of people. Not only must this information be gathered, it must also be linked together to provide explanation and prediction. Computational neuroscience has emerged as a set of concepts and techniques to provide these links for findings and ideas arising from disparate types of investigation.

In many ways, the brain is not much like the computer. Yet, both as a direct model of certain aspects of brain functioning and as a tool for exploring brain function, the computer enjoys many advantages over previous models and metaphors for brain function. New, more precise, concepts of information and memory have grown out of the use of telecommunication and data processing equipment. These concepts are applied to our thinking about the brain. In addition to being a source of new ideas, the computer is itself valuable as a tool. The computer model or simulation, allows hypotheses to be tested explicitly, whether the high-level hypotheses of cognitive neuroscience or the low-level hypotheses of membrane and channel biophysics.

Our research efforts have been directed towards development and application of new conceptual and technical tools of computational neuroscience. Development projects have primarily been aimed at integrating the computer-science-derived top-down techniques of artificial neural networks with neuroscience-derived bottom-up techniques. Application projects have been largely aimed at the problems of understanding neurological disease, particularly epilepsy and stroke


Selected Publications

Migliore, M., Cannia, C., Lytton, W. W., Markram, H., and Hines, M. L. (2006). Parallel network simulations with NEURON. J. Comp. Neurosci. 6, 119-129.

Lytton, W. W., and Omurtag, A. (2007). Tonic-clonic transitions in computer simulation. J. Clin. Neurophys. 24, 175-181.

Lytton, W. W., Orman, R., and Stewart, M. (2008). Broadening of activity with flow across neural structures. Perception 37, 401-407.

Lytton, W. W., Omurtag, A., Neymotin, S. A., and Hines M. L. (2008). Just-in-time connectivity for large spiking networks. Neural Comput. 20, 2745-2756.

Orman, R., Von Gizycki, H., Lytton, W. W., and Stewart, M. (2008). Local axon collaterals of area CA1 support spread of epileptiform discharges within CA1, but propagation is unidirectional. Hippocampus 18, 1021-1033.

Lytton, W .W. (2008). Computer modelling of epilepsy. Nat. Rev. Neurosci. 9, 626-637.

Lytton, W. W., Neymotin, S. A., and Hines, M. L. (2008).The virtual slice setup. J. Neurosci. Meth. 171, 309-315.

Fenton, A. A., Kao, H. Y., Neymotin, S. A., Olypher, A., Vayntrub, Y., Lytton W. W., and Ludvig, N. (2008). Unmasking the CA1 ensemble place code by exposures to small and large environments, more place cells and multiple, irregularly arranged, and expanded place fields in the larger space. J. Neurosci. 28, 11250-11262.

List of Publications (Pub Med)


Service Functions

Program Committee Computation and Neural Systems Meeting
Reviewer for various scientific journals and funding agencies




E-mail: bill.lytton@downstate.edu

Return to Department of Physiology and Pharmacology Home Page

Return to SUNY Brooklyn Home Page