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Using Brain Control Interfaces as Rehabilitation Therapy

Top: Activity around the ECoG array from the first trials, in which ~50% accuracy was achieved.

Bottom: Activity around the ECoG array on the same task, after 10 minutes of training.

ECoG or electrocorticography is a relatively young means of reading the brain. It is essentially an EEG grid placed under the skull, on the surface of the brain itself. Thus the electrical dampening effects of the cranium can be mitigated, and far weaker brainwaves detected in great fidelity.

Thus it is almost natural that it should be the technology used to discover that the theory of increased use of a neuroprosthetic training the brain, is not theory at all, and such an interface method can be used much like training a muscle.

The study was led by researchers at the University of Washington, whose use of what has become a standard test of BCI interfaces - using pure thought to control a cursor - produced a rather more interesting result.

"Bodybuilders get muscles that are larger than normal by lifting weights," said lead author Kai Miller, a UW doctoral student in physics, neuroscience and medicine. "We get brain activity that's larger than normal by interacting with brain-computer interfaces. By using these interfaces, patients create super-active populations of brain cells."

Eight volunteers were tested, all of which were epilepsy patients awaiting surgery at two Seattle hospitals. As has become usual in such cases, the electrode arrays were implanted during necessary surgery to treat the epilepsy, when the brain would be opened up anyway. The volunteers each had electrodes attached to the surface of their brains during the week leading up to the surgery and agreed to participate in research that would look at connecting brains to a computer.

The researchers first recorded brain patterns when human subjects clenched and unclenched a fist, stuck out a tongue, shrugged their shoulders or said the word "move."

Next, the scientists recorded brain patterns when subjects imagined performing the same actions. These patterns were similar to the patterns for actual action but much weaker, as expected from previous studies.

Finally, the researchers looked at signals when subjects imagined performing the action and those brain signals were used to move a cursor toward a target on a computer screen. After less than 10 minutes of practice, brain signals from imagined movement became significantly stronger than when actually performing the physical motion.

In two cases, within the ten minutes, two of the volunteers independently reported that they no-longer had to consciously think about moving the body-part, they just willed the cursor to move, and it did. The brain had made all the necessary internal connections to the subconscious in just that short span of time. Whilst the testing sessions were only ten minutes in length, it is reasonable to extrapolate that had they progressed further, most if not all of the volunteers would have been able to adapt likewise, within a very short span of time.

As an additional aside, the experiment has also enriched our understanding of which frequencies to tap. Researchers compared the patterns in low-frequency signals, usually used to control external devices, and high-frequency signals, typically dismissed as noise. They discovered that the high-frequency signals are more specific to each type of movement. Because each one occupies a smaller portion of the brain, several high-frequency signals could be tapped simultaneously to control more sophisticated devices.

References

Brain-controlled cursor doubles as a neural workout

Cortical activity during motor execution, motor imagery, and imagery-based online feedback

Staff Comments

 


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