Brain waves pattern themselves after rhythms of nature

Cowan organized a session for AAAS on Mathematics and the Brain, which will take place from 8:30 to 10 a.m. EST Saturday, Feb. 16. He also will participate in a news briefing on the topic at 3 p.m. EST Friday, Feb. 15. Joining him at both events will be mathematician Nancy Kopell of Boston University and computational neuroscientist Tomaso Poggio of the Massachusetts Institute of Technology.

At this stage of his research, Cowan said it would be premature and speculative for him to try to relate how phase transitions in the brain might relate to neurological conditions or states of human consciousness. “That’s for the future,” he said.

Another component of his latest research is the close relationship between spontaneous pattern formation in brain circuits and in chemical reaction networks. In this research, he shows how mathematics can help explain visual hallucinations and how the visual cortex obtained its stripes, which are visible to the naked eye when removed from cadavers.

“This line of research on pattern formation can be traced back to Alan Turing, who also founded the modern science of computation,” said Terrence Sejnowski of the Salk Institute for Biological Studies in La Jolla, Calif., who is a leading specialist in computational neurobiology.

Cowan’s quest to understand the brain’s workings using numerical methods spans more than four decades. Along the way he has collaborated with a series of Ph.D. students and colleagues in physics, mathematics, biology and neuroscience.

In 1972, he and postdoctoral fellow Hugh Wilson, now of Canada’s York University, formulated a set of equations that could describe the dynamics of neural networks. Now called “Wilson-Cowan equations,” they became a mainstay of neural network research. “But I always knew that those equations were inadequate, so I kept thinking about them,” Cowan said.

Then in 1985, he ran across an article in a Japanese journal that described a statistical physics approach to chemical reaction networks. “It took me years to understand how to use these tools for biological networks,” he said. “It so happens that there is an analogy between the behavior of chemical reaction networks and neural networks.”

His research career began in 1962, when as a graduate student in electrical engineering, he worked with the founders of neural network theory. These included Norbert Wiener, who died in 1964, before they could work jointly on the problem that Cowan continues to address.

“I didn’t really understand what he was saying to me until I worked it out myself. He was one of the great mathematicians of the 20th century,” Cowan said.