Norwegian and German scientists have developed a method to better interpret brain cell signals in a forest of neurons.
Researchers hope their method could lead to considerable steps forward in terms of interpreting EEG measurements, making diagnoses and treatment of various brain illnesses.
The problem of interpreting electrical signals measured by electrodes in the brain is similar to that of interpreting sounds signals picked up by a microphone in a crowd – many things happen all at once.
“Based on methods from physics, mathematics and informatics, as well as computational power from the Sallo supercomputer in Tromosø, we have developed detailed mathematical models revealing the connection between nerve cell activity and the electrical signal recorded by an electrode,” said Professor Gaute Einevoll, from the Department of Mathematical Sciences and Technology (IMT) at the Norwegian University of Life Sciences (UMB).
The project focussed on bass and low frequency signals called local field potential of LFP.
“We have found that if nerve cells are babbling randomly on top of each other and out of sync, the electrode’s reach is so narrow that it can only receive signals from nerve cells less than 0.3mm away,” said Einevoll. “However, when nerve cells are speaking simultaneously and in sync, the range can be much wider.”
Better understanding of the electrical brain signals may influence the diagnosis and treatment of illnesses such as epilepsy. Einevoli says LFP signals measured by implanted electrodes could detect an impending epilepsy seizure and stop it by injecting a suitable electrical current.
“A similar technique is being used on many Parkinson’s patients, who have had electrodes surgically implanted to prevent trembling,” said UMB researcher Klas Petterson.
The treatment may also be used in patients paralysed by spinal cord fracture, the researchers believe. When a patient is paralysed, nerve cells in the cerebral cortex continue to send out signals, but the signals do not reach the muscles and the patient cannot move.
“By monitoring the right nerve cells and forwarding these signals to for example a robot arm, the patient may be able to steer by his or her thoughts alone,” said Einevoll.
The work has been published in Neuron.