Salk Institute
Terrence J. Sejnowski
Professor and Laboratory Head
Computational Neurobiology Laboratory
Howard Hughes Medical Institute Investigator
Francis Crick Chair
Terrence J. Sejnowski

Professor and Laboratory Head
Computational Neurobiology Laboratory
Howard Hughes Medical Institute Investigator
Francis Crick Chair


Research

Terrence J. Sejnowski, professor and head of the Computational Neurobiology Laboratory, is a pioneer in the field of computational neuroscience.

Among other things, Sejnowski is interested in the hippocampus, believed to play a major role in learning and memory; and the cerebral cortex, which holds our knowledge of the world and how to interact with it. In his lab, Sejnowski's team uses sophisticated electrical and chemical monitoring techniques to measure changes that occur in the connections among nerve cells in the hippocampus during a simple form of learning. They use the results of these studies to instruct large-scale computers to mimic how these nerve cells work. By studying how the resulting computer simulations can perform operations that resemble the activities of the hippocampus, Sejnowski hopes to gain new knowledge of how the human brain is capable of learning and storing memories. This knowledge ultimately may provide medical specialists with critical clues to combating Alzheimer's disease and other disorders that rob people of the critical ability to remember faces, names, places and events.

"My goal is to discover the principles linking brain mechanisms and behavior. My laboratory uses both experimental and modeling techniques to study the biophysical properties of neurons and synapses, the sites at which neurons connect with each other, as well as the population dynamics of large networks of neurons."

Multiple sclerosis affects an estimated 400,000 Americans and more than 2.5 million people worldwide. A chronic, often disabling disease that attacks the central nervous system, it is characterized by a baffling range of neurological symptoms, including numbness, tingling, motor weakness, paralysis and vision loss. It is thought to result when the immune system attacks the myelin sheath that insulates axons, the nerve fibers that conduct electrical impulses to and from the brain and between neurons within the brain. Ordinarily, the myelin speeds up the signals the axons transmit, but when axons lose their insulation, either signal conduction fails because the demyelinated axons are unable to generate an impulse, or the axons become hyperexcitable and overcompensate by firing even in the absence of an input.

The first computer model of axonal transmission, developed in the 1950s for the giant axon of the squid, which lacks myelin, tracked positively charged sodium and potassium ions, whose movements across the neuronal membrane generate the necessary electrical signals. Building on that model, Sejnowski and his team included myelin in their own model, then demyelinated one of the sections and incorporated all the changes known to take place as a result. Most prior studies had focused on the sodium channel because it is responsible for initiating the electrical signal. But to everyone's surprise, Sejnowski's group found that it was the ratio of densities between the sodium channel and a previously ignored but ubiquitous voltageinsensitive potassium current, called the leak current, that determines whether neurons can fire properly.

If the sodium level drops, an accompanying drop in the leak current will maintain the signal, whereas if the sodium drops but the leak current doesn't, signal transmission may fail. Conversely, if the sodium level is too high and the leak current doesn't increase, a patient may experience twitching. Sejnowski's model not only offers an explanation for many of the bizarre symptoms that multiple sclerosis patients experience but could also provide a new target for drugs that increase or decrease the potassium leak current to maintain a constant ratio and offer relief.

Lab Photo

Back row, left to right: Claudia Lainscek, Jorge Aldana, Andrew Schulman, Clare Puddifoot, Romain Veltz, Cian O'Donnell, Elan Ohayon, Bryan Nielsen, Marga Behrens, Terry Sejnowski, Lee Campbell, Tom Bartol, Samat Moldakarimov, Saeed Saremi, Jay Coggan, Eran Mukamel, Dave Peterson, Krishnan Padmanabhan, Hosam Yousif

Front row, left to right: Ben Regner, Aaron Kappe, Trygve Solstad, Monika Jadi, Ramona Marchand, Chris Hiestand, Ben Huh, Mary Ellen Perry, Xin Wang, Suhita Nadkarni, Don Spencer, Bob Kuczewski, Collins Assisi

Selected Publications

Sejnowski, T. J. and Rosenberg, C. R., Parallel networks that learn to pronounce English text, Complex Systems 1, 145-168 (1987).

Steriade, M., McCormick, D. A., Sejnowski, T. J., Thalamocortical oscillations in the sleeping and aroused brain, Science 262, 679-685 (1993).

Bell, A. J. and Sejnowski, T. J., An information-maximization approach to blind separation and blind deconvolution, Neural Computation 7, 1129-1159 (1995).

Mainen, Z. F. and Sejnowski, T. J., Reliability of spike timing in neocortical neurons, Science 268, 1503-1506 (1995).

Laughlin, S. B., and Sejnowski, T. J., Communication in neuronal networks, Science 301, 1870-1874 (2003).

Coggan, J. S., Bartol, T. M., Esquenazi, E., Stiles, J. R., Lamont, S., Martone, M. E., Berg, D. K., Ellisman, M. H., and Sejnowski, T. J., Evidence for ectopic neurotransmission at a neuronal synapse, Science, 39, 446-451 (2005).

Tiesinga, P.; Sejnowski, T. J.; Cortical enlightenment: Are gamma oscillations driven by ING or PING? Neuron, 63: 727-732 (2009).

Meltzoff, A. N., Kuhl, P. K., Movellan, J., Sejnowski, T. J., Foundations for a new science of learning, Science 325: 284-288 (2009).

Wang, H.P., Spencer, D., Fellous, J.-M., Sejnowski, T. J., Synchrony of Thalamocortical Inputs Maximizes Cortical Reliability, Science, 328: 106-109 (2010).

Lister, R., Mukamel, E. A., Nery, J. R., Urich, M., Puddifoot, C. A., Johnson, N. D., Lucero, J., Huang, y., Dwork, A., Schultz, M. D., Tonti-Filippini, J., Yu, M.; Heyn, H.; Hu, S.; Wu, J. C.; Rao, A.; Esteller, M.; He, C.; Haghighi, F. G., Sejnowski, T. J., Behrens, M. M., Ecker, J. R., Global epigenomic reconfiguration during mammalian brain development, Science, 341, 629, (2013).

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