William W. Lytton, MD
Physiology and Pharmacology
Neurology, Biomedical Engineering
The Neurosimulation Laboratory uses computational neuroscience to forge links between disparate findings from brain function with applications to brain disease: epilepsy, stroke, schizophrenia, dystonia, Parkinson's, Alzheimer's, and others.
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 and at disparate spatial and temporal scales.
The extraordinary success of artificial neural networks and computer learning seems to demonstrate that the very recent accomplishments of the human mind -- eg playing chess, go or Jeopardy -- are not the things that are really hard to do. They are also, of course, largely not the things that evolution as pressured brains to be able to do. Instead, it's the seemingly simple things that we share with many other animals -- acute visual and auditory perception under multiple conditions, control of locomotion across uneven terrain at different speeds -- that really bring into play the complex processing for which brain coding is optimized. Lack of perceptual and motor skills have been major impediments to the development of useful robots. We have been trying to develop biomimetic models that can communicate with brains and also control a robot arm.Service Functions
Program Committee Computation and Neural Systems Meeting
Reviewer for various scientific journals and funding agencies
- 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.