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December 19, 2020 Saturday 08:01:41 AM IST

Technique to Predict Seizures in Epilepsy

Scientists at University of Geneva and the University Hospital of Bern have developed a technique that can predict epileptic seizures between one and several days in advance. This is possible by recording neuronal activity over at least six months using a device implanted directly in the brain. The device enables detection of individual cycles of epileptic activity and provide information about the probability of a future seizure. In the absence of ways by which we can predict seizures, patients are forced to take regular medication. It also prevents them from taking part in sports. The drugs may reduce neuronal excitability but they with numerous potential side effects. 

The scientists implanted devices for long-term in epileptic patients to understand the neuronal activity. 

 

An epileptic brain can switch suddenly from a physiological state to a pathological state, characterised by a disturbance of neuronal activity which can cause, inter alia, convulsions typical of an epileptic seizure. How and why the brain swaps one state for another is still poorly understood, with the result that the onset of a seizure is difficult, if not impossible, to predict. "Specialists worldwide have been trying for over 50 years to predict seizures a few minutes in advance, but with limited success," explains Timothée Proix, a researcher in the Department of Fundamental Neurosciences in UNIGE’s Faculty of Medicine.


 Seizures do not appear to be preceded by any obvious warning signs that would make prediction easier. The frequency, depending on the individual, varies from once a year to once a day. 

 After confirming that there were indeed cycles of cerebral epileptic activity, the scientists turned their attention to statistical analysis.

This approach helped highlight a phenomenon known as the "proictal state» where the probability of the onset of a seizure is high. "As with weather disturbances, there are several time scales in epileptic brain activity," points out Dr Baud. "The weather is influenced by the cycle of the seasons or day and night. On an intermediate scale, when a weather front approaches, the probability that it will rain increases for several days and is, therefore, better predictable. These three scales of cyclic regulation also exist for epilepsy."

 The electrical activity in the brain is a reflection of the cellular activity of its neurons, more precisely their action potentials, electrical signals propagating along the neural network to transmit information. Action potentials are well known to neuroscientists, and their probability can be modelled using mathematical laws. «We adapted these mathematical models to the epileptic discharges to find out whether they heralded or inhibited a seizure», explains Dr Proix. To boost the predictive reliability, recordings of brain activity over very long periods were required. Using this approach, fronts with a high probability of seizure lasting several days could be determined for a majority of patients, making it possible to predict seizures several days in advance in some. 


With brain activity data collected over periods of at least six months, seizure prediction is informative for two-thirds of patients.

The analytical approach is sufficiently ‘light’ to allow the transmission of data in real time on a server or directly on a microprocessor with a device small enough to be implanted in the skull. The researchers are now working in collaboration with the Wyss Center for Bio and Neuroengineering, based at Campus Biotech in Geneva, to develop a minimally invasive brain monitoring device to record the long-term data needed to forecast seizures. The device, which slips under the skin of the scalp, could give people with epilepsy the power to plan their lives according to the likelihood of having a seizure.

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