Rat Brain Cells, in a Dish, Flying a Plane
Posted on November 26, 2008 Comments (2)
|Adaptive Flight Control With Living Neuronal Networks on Microelectrode Arrays (open access paper) by Thomas B. DeMarse and Karl P. Dockendorf Department of Biomedical Engineering, University of Florida
investigating the ability of living neurons to act as a set of neuronal weights which were used to control the flight of a simulated aircraft. These weights were manipulated via high frequency stimulation inputs to produce a system in which a living neuronal network would “learn” to control an aircraft for straight and level flight.
A system was created in which a network of living rat cortical neurons were slowly adapted to control an aircraft’s flight trajectory. This was accomplished by using high frequency stimulation pulses delivered to two independent channels, one for pitch, and one for roll. This relatively simple system was able to control the pitch and roll of a simulated aircraft.
When Dr. Thomas 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.”
To control the simulated aircraft, the neurons first receive information from the computer about flight conditions: whether the plane is flying straight and level or is tilted to the left or to the right. The neurons then analyze the data and respond by sending signals to the plane’s controls. Those signals alter the flight path and new information is sent to the neurons, creating a feedback system.
“Initially when we hook up this brain to a flight simulator, it doesn’t know how to control the aircraft,” DeMarse said. “So you hook it up and the aircraft simply drifts randomly. And as the data come in, it slowly modifies the (neural) network so over time, the network gradually learns to fly the aircraft.”
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.
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