Une vieille dame atteinte d'une épilepsie.

This new calculation method could fight epilepsy and here’s how!

Epilepsy is a serious neurological disease, affecting more than 50% of patients from childhood. A recent study revealed that this affection would mainly affect the cerebral network. Discovering an effective treatment would prevent serious long-term consequences on the brain. The construction of epileptic networks would therefore be essential in order to combat the disease.

An old lady with epilepsy.

This is why researchers from the Suzhou Institute of Biomedical Engineering and Technology (SIBET) of the Chinese Academy of Sciences recently proposed a method for calculating the dynamic resting state functional network (DFN) for the whole brain.

This method was based on low-density electroencephalogram (EEG) recordings in the scalp. It would make it possible to better construct the cerebral networks of epilepsy.

Limit of electroencephalogram (EEG)

Children are usually affected by benign centrotemporal spike epilepsy (BECTS). Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) source imaging (ESI) studies have indicated that this type of epilepsy is associated with static impairments of the functional network (SFN) at rest in source space.

EEG is a non-invasive, portable, cost-effective, and child-friendly technique. Moreover, with IMRf, they are currently the most used to build epileptic networks. However, SFN calculations performed in the scalp, performed with routine low-density EEG recordings, do not show the same previous alterations.

LIU Yan and his colleagues from the DAI Yakang group of SIBET subsequently proposed the DFN calculation method. This method is based on the concept of EEG microstates.

“This method makes it possible to better analyze the dynamic properties of the functional states of the whole brain and, on the other hand, to display topologies of the functional sub-networks in each micro-state. »


A method with promising results

DFN revealed significant differences between individuals with BECTS and healthy individuals. Outperforming traditional SFNs, it equalizes traditional fMRI and ESI methods in the source space. She might even be used for other brain diseases.

This new method escapes complex ESI operations. DFN calculations are made directly from low-density routine EEG recordings. It could have clinical applications, especially during ambulatory diagnosis.


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