New method developed for diagnosing epilepsy from resting state data

Posted Dec 19 2014 in Brain science; genetics

Scientists from the University of Exeter have created a convenient diagnostic method that could potentially revolutionise global diagnostic procedures for idiopathic generalised epilepsies.

The team has been able to create a means of using mathematical modelling to assess susceptibility to this common form of epilepsy by analysing electrical activity of the brain while the patient is in a resting state.

In the first of their studies on the subject, published in the journal Frontiers in Neurology, electroencephalography techniques were used to assess how different regions of the brain were connected, based on the level of synchrony between them.

Mathematical tools were then used to characterise these networks, finding that in epilepsy patients these networks were relatively over-connected when compared to healthy controls. The same was true of first-degree relatives of patients, suggesting potential hereditary causes.

Meanwhile, a second study looked at how these brain network changes can make people more vulnerable to recurrent seizures. It was found that the level of communication between regions that would lead to synchronous activity was lower in the brain networks of people with idiopathic generalised epilepsy, suggesting this is a possible mechanism of seizure initiation.

Additionally, altering the activity in specific left frontal brain regions of the computational model helped to synchronise activity through the whole network, highlighting a potential treatment approach.

Idiopathic epilepsy is a term given to forms of the condition where no apparent causal abnormalities in the brain can be found. They are believed to have genetic causes, making them hard to treat.

Current diagnostic approaches involve observing electrical activity associated with seizures in a clinical environment, but this new method is likely to be safer and faster, since only a few minutes of resting state data would need to be collected from each patient.

The university’s project leader Professor John Terry said: “Our research offers the fascinating possibility of a revolution in diagnosis for people with epilepsy.

“It would move us from diagnosis based on a qualitative assessment of easily observable features, to one based on quantitative features extracted from routine clinical recordings.”

Posted by Bob Jones

Original publication: http://journal.frontiersin.org/Journal/10.3389/fneur.2014.00261/full

In 2012 Epilepsy Research UK awarded Professor Terry and colleagues a grant to carry out a related project entitled Developing computer models to improve the predictive value of routine clinical EEG.  You can read more about this here.

 

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