Decoding brain signals

Scientist looking at model of brain

10/12/2016 |

Researchers have taken an important step toward deciphering the brain’s neuroelectric system that could underlie sleep disorders and conditions such as Alzheimer’s, epilepsy, and schizophrenia. The complex communication network connects groups of neurons that can be identified and studied by imaging the brain while a person rests using functional magnetic resonance imaging (fMRI). Because the brain’s resting state is not biased by any particular task, the approach provides a way to study its “intrinsic functional organization,” says Zhongming Liu, an assistant professor of biomedical engineering and electrical and computer engineering.

“The rationale behind this is that when the brain is not doing anything it is not literally quiet but remains very active, providing many kinds of signals,” he says. Researchers are working to interpret data from fMRI, which monitors blood-flow changes in the brain.

“Data related to blood flow are different from the language used by the neurons themselves,” says Liu. “The neurons use electrical signals to talk to each other, and these electrical signals happen much faster than blood flow. So we are translating those slow blood-flow signals into the fast signals the neurons use.”

The researchers used brain data from three methods: electrocorticography, which uses sensors on the cortex to record electrical signals; magnetoencephalography, which measures magnetic fields generated by the brain; and electroencephalography, which measures electrical signals on the scalp while a person is also scanned with fMRI.

It is thought that neurons talk to each other by using oscillations at the same frequency. While regions communicate with each other in well-defined rhythmic oscillations, researchers are also probing a “scale-free” form of communication that lacks well-defined rhythmic features.

“These featureless signals are often discarded by neuroscientists because they are considered noise or something unimportant,” Liu says. “We took these signals out of the trash can and found that they are actually very important because they are synchronized among nearly all groups of neurons in the brain.”

– Emil Venere, http://bit.ly/2ewAaTT

Above: Illustration by Taylor Callery