Alexander Khramov
Newswise — Scientists at Immanuel Kant BFU have developed a mathematical model that describes human brain condition in epilepsy. The system reproduced changes in brain activity during a seizure, as well as taking into account multiple interactions among neurons and other brain cells. The developed model will broaden the understanding of progression of an epileptic seizure and help in the treatment of the disease. The study is published in Physical Review magazine.
During ordinary brain function, excitatory and inhibitory inputs that are transmitted between neurons counterbalance each other. However, in disorders such as epilepsy strong excitatory impulses are formed in certain parts of the brain. As a consequence, an entire region of a brain is being seized by excessive stimulation, and the person has convulsions. Due to the fact that a large number of brain cells is involved during an epileptic seizure, scientists have failed to fully describe the development of the state. As a result, the development of an effective treatment is falling back.
Scientists at Immanuel Kant Baltic Federal University (Kaliningrad), the Indian Statistical Institute (Kolkata, India) and the Catholic University of Leuven (Leuven, Belgium) have developed a model that replicates brain activity during an epileptic seizure. Its feature is that compared to other programs that describe the process of transmission of nerve impulses in human brain and take only individual pair wise interactions between cells into account, it describes multiple connections, including interactions between neurons and supporting brain cells — glial cells. It is crucial to take them into account because the disruption of neuron-glial interaction is considered a key contributor to the development of epilepsy.
As a result, the researchers have obtained a model whose components form a net resembling a human brain’s neural and glial cells network. With that, the scientists have set up connections between elements so that the signals would spread spontaneously and in sync. Such a model of behaviour reflected hypersynchronous activity during an epileptic seizure and is very similar to processes that occurred during an epileptic attack.
«Later on, we are planning to enhance our model by considering a more realistic approach to modeling brain nerve cells. We are also interested in the issue of considering the most accurate interactions between different brain cells for the best understanding of processes in an epileptic brain. It is likely that our model may be interesting for testing the effects of different anti-epileptic drugs on our brain» — says Alexander Khramov, Doctor of Physics and Mathematics, chief scientific officer of The Baltic centre for neurotechnologies and Artificial Intelligence at BFU named after Immanuel Kant.
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