Ås, Akershus, Norway. Detailed mathematical models have improved analyses of electrical signals in the brain, charting the connections between nerve cells.

Scientists can trace communications from their origin point to an electrode, despite the overlapping sounds from as many as 100,000 nerve cells per cubic millimeter, providing an example of the increased importance of computational neuroscience in modern brain research.


Researchers and doctors have been measuring and interpreting electrical activity generated by brain cells since 1875. Doctors have over the years acquired considerable practical skills in relating signal shapes to different developmental processes and illnesses such as epilepsy. However, doctors have so far had little knowledge on how these signals are formed in the network of nerve cells. The research result is a considerable step forward and has the potential to support reinterpretation of EEG measurements.



Gaute Einevoll, PhD, is a Professor at the Department of Mathematical Sciences and Technology (IMT) at the Norwegian University of Life Sciences (UMB).

"Based on methods from physics, mathematics and informatics, as well as computational power from the Stallo supercomputer in Tromsø, we have developed detailed mathematical models revealing the connection between nerve cell activity and the electrical signal recorded by an electrode."Researchers at the Norwegian University of Life Sciences (UMB) have developed the method and published their findings in the journal Neuron. The problem of interpreting electrical signals measured by electrodes in the brain is similar to that of interpreting sound signals measures by a microphone in a crowd of people. Just like people sometimes all talk at once, nerve cells are also sending signals on top of each other. The electrode records the sounds from the entire population of nerve cells surrounding it.

There are numerous contributors since one cubic millimetre can contain as many as 100,000 nerve cells. The brain can distinguish high and low frequency electrical signals are distinguished in the brain. This project has focused on the bass - the low frequency signals called local field potential (LFP). The scientists found that if nerve cells are babbling randomly on top of each other and out of sync, the electrode's reach is narrow. It can only receive signals from nerve cells less than about 0.3 millimetres away. However, Einevoll says that when nerve cells are speaking simultaneously and in sync, the range can be much wider.

Better understanding of the electrical brain signals may directly influence diagnosing and treatment of illnesses such as epilepsy. "Electrodes are already being used to measure brain cell activity related to seizures in epilepsy patients, as well as planning surgical procedures. In the future, LFP signals measured by implanted electrodes could detect an impending epilepsy seizure and stop it by injecting a suitable electrical current," Einevoll says.

"A similar technique is being used on many Parkinson's patients, who have had electrodes surgically implanted to prevent trembling," researcher Klas Pettersen at the UMB adds. Einevoll and Pettersen also outline treatment of patients paralysed by spinal cord fracture as another potential area where the method can be used.

"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 is thus unable to move arms or legs. 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," Einevoll says.

The UMB Computational Neuroscience Group has established contacts with clinical research groups in the United States and Europe for further research on using the approach in patient treatment.

Name

Email

Website

Title

Comment

smaller | bigger

I have read and agree to the Terms of Usage.

Add Comment