Thomas DeMarse of the biomedical engineering department at the University of Florida has developed a “living computational device” from 25,000 neurons extracted from a rat embryo.
Then he taught it to fly a jet fighter. The F-22 to be precise.
The 25,000 neurons were suspended in a specialized liquid to keep them alive and then laid across a grid of 60 electrodes in a small glass dish.
Under the microscope they looked at first like grains of sand, but soon the cells begin to connect to form what scientists are calling a “live computation device” (a brain). The electrodes measure and stimulate neural activity in the network, allowing researchers to study how the brain processes, transforms and stores information.
In the most striking experiment, the brain was linked to the jet simulator. Manipulated by the electrodes and a desktop computer, it was taught to control the flight path, even in mock hurricane-strength winds.
“When we first hooked them up, the plane ‘crashed’ all the time,” Dr DeMarse said. “But over time, the neural network slowly adapts as the brain learns to control the pitch and roll of the aircraft. After a while, it produces a nice straight and level trajectory.”
The article doesn’t say, but DeMarse must have found a way to reward the brain for flying straight (or punish it for crashing) using hormones like serotonin. Otherwise, why would this brain-in-a-dish prefer level flight to crashing?
The implications are profound. DeMarse’ first goal is to study brain function. Until this development, scientists were only able to study a few neurons in a petri dish. Now DeMarse can observe how these neurons work together to compute. Obviously this is important brain research, but it could also be very important computer research. It could also be important to researchers interested in learning how to get a brain to directly communicate with a computer.
Individual neurons are slow by comparison to transistors, but a brain is superior to a contemporary computer in many ways – pattern recognition, redundant fail proofing (the loss of a few neurons doesn’t lead to a crash), self-organizing, and after a crash (a stroke) it can rewire itself. This could lead us to develop computers that are more like a brain.
In the meantime it might lead to hybrids – computers with electronic and biological components.
It could also be another route to greater-than-human intelligence. If this brain-in-a-dish is possible, why couldn’t this, ultimately, be ramped up to a 20 pound brain? Such a brain would not be limited by a size that is practical to be carried around in a human skull. Nor would it have to be concerned with the “mundane” tasks of managing a body.
