A forest of neurons Photo: Hermann CuntZ |
Researchers
at the Norwegian University of Life Sciences (UMB) and
Forschungszentrum Jülich in Germany have developed a new method for
detailed analyses of electrical activity in the brain. The method,
recently published in Neuron,
can help doctors and researchers to better interpret brain cell
signals. In turn, this may lead to considerable steps forward in terms
of interpreting for example EEG measurements, making diagnoses and
treatment of various brain illnesses.
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 brain illnesses such as epilepsy. However, doctors have so far
had little knowledge on how these signals are formed in the network of
nerve cells.
“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,”
says Professor Gaute Einevoll at the Department of Mathematical
Sciences and Technology (IMT) at UMB.
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 whole orchestra of nerve cells
surrounding it and there are numerous contributors. One cubic millimeter
can contain as many as 100,000 nerve cells.
Similar to bass and treble in a soundtrack, 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” or simply 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 narrow so that it can only receive signals from nerve cells
less than about 0.3 mm away. However, when nerve cells are speaking
simultaneously and in sync, the range can be much wider,” Einevoll says.
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 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
Computational Neuroscience Group at UMB has already established
contacts with clinical research groups in the USA and Europe for further
research on using the approach in patient treatment.
