When DeMarse first puts the neurons in the dish, they look like little more than grains of sand sprinkled in water. However, individual neurons soon begin to extend microscopic lines toward each other, making connections that represent neural processes. “You see one extend a process, pull it back, extend it out ? and it may do that a couple of times, just sampling who’s next to it, until over time the connectivity starts to establish itself,” he said. “(The brain is) getting its network to the point where it’s a live computation device.”

Although the brain currently is able to control the pitch and roll of the simulated aircraft in weather conditions ranging from blue skies to stormy, hurricane-force winds, the underlying goal is a more fundamental understanding of how neurons interact as a network, DeMarse said.

“We’re interested in studying how brains compute,” said. “If you think about your brain, and learning and the memory process, I can ask you questions about when you were 5 years old and you can retrieve information. That’s a tremendous capacity for memory. In fact, you perform fairly simple tasks that you would think a computer would easily be able to accomplish, but in fact it can’t.”

While computers are very fast at processing some kinds of information, they can’t approach the flexibility of the human brain, DeMarse said. In particular, brains can easily make certain kinds of computations – such as recognizing an unfamiliar piece of furniture as a table or a lamp – that are very difficult to program into today’s computers.

“There’s a lot of data out there that will tell you that the computation that’s going on here isn’t based on just one neuron. The computational property is actually an emergent property of hundreds or thousands of neurons cooperating to produce the amazing processing power of the brain.”

With Jose Principe, a UF distinguished professor of electrical engineering and director of UF’s Computational NeuroEngineering Laboratory, DeMarse has a $500,000 National Science Foundation grant to create a mathematical model that reproduces how the neurons compute.

These living neural networks are being used to pursue a variety of engineering and neurobiology research goals, said Steven Potter, an assistant professor in the Georgia Tech/Emory Department of Biomedical Engineering who uses cultured brain cells to study learning and memory. DeMarse was a postdoctoral researcher in Potter’s laboratory at Georgia Tech before he arrived at UF.

“A lot of people have been interested in what changes in the brains of animals and people when they are learning things,” Potter said. “We’re interested in getting down into the network and cellular mechanisms, which is hard to do in living animals. And the engineering goal would be to get ideas from this system about how brains compute and process information.”

Though the “brain” can successfully control a flight simulation program, more elaborate applications are a long way off, DeMarse said. “We’re just starting out. But using this model will help us understand the crucial bit of information between inputs and the stuff that comes out,” he said. “And you can imagine the more you learn about that, the more you can harness the computation of these neurons into a wide range of applications.”