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Mathematical model of brain during seizure created

24 February, 2005

Researchers have
created a mathematical model of the electrical activity that occurs in
the brain during a seizure, which they say may help neurologists better
understand epilepsy.

To
model this behaviour, the researchers adapted complex equations to
describe the architecture of the brain (the same type of equations used
to spot trends in the stock market, weather or other complex systems
that could be affected by random events). They simulated the excitation
of neurons in a portion of the brain and found that the stimulus
produced travelling waves of electrical activity.

To test the accuracy of their model, the researchers, from University of California (UC) in Berkeley,
worked with Dr Heidi Kirsch, assistant professor of neurology at UC San
Francisco's Epilepsy Center. Dr Kirsch was treating a 49-year-old with
epilepsy who had been diagnosed with mesial temporal sclerosis and
whose seizures were not reliably controlled by medication.

Electrodes
were implanted into the patient's brain for a week. The researchers
were thus able to obtain data from six of the patient's seizures to
compare with the mathematical model they had created.

During
a seizure, it was noted a strong pattern of electrical signals suddenly
emerged from the random fluctuations that characterised normal brain
activity. The strong waves moving across the cortex may cause the
sudden, unpredictable sensations or uncontrollable movements that may
occur during a seizure.

Lead author Mark Kramer said:

"The
wave signals from both the model and the observational data were
similar in shape, frequency and speed of propagation. That suggests
that our model is pretty accurate.

"Electrodes
reveal the consequence of the abnormal brain activity, but they don't
get at the cause. If we understand why and how these strong coherent
waves progress over the surface of the brain, then we have a hope of
doing something to change the situation by disrupting the signal."

The
researchers say this is an early step in creating a model that can
provide far more detail about the inner workings of the brain than is
possible with electrodes alone.