Computational Modelling of Human Epilepsy: from Single Neurons to Pathology

Опубликовано 1 октября 2018, 19:28

The mission of Allen Institute is to accelerate the understanding of how the human brain works in health and disease. Epilepsy is the fourth most common neurological disorder and is responsible for significant total global burden of disease, affecting more than 50 million people worldwide. Despite considerable advances in the treatment and diagnosis of seizure disorders, about 40% of patients do not respond to pharmacological treatment. To determine the mechanisms underlying epileptogenesis in the human brain we analyzed in vitro data to study the excitability of neurons in tissue obtained from human hippocampus. Using random forest classifiers and pairwise comparisons we found that spiking properties are significantly correlated with the degree of sclerosis, while the majority of morphological properties are not. To test the implications of the observed differences we developed novel computational models of single neurons and neural networks using combinatorial optimization techniques. Using these models we explored relevant pathophysiological scenarios associated with hippocampal sclerosis and its implications for neural dynamics. This approach in the future may allow us to formulate specific predictions for genomic RNA-Seq data to characterize particular mutations associated with human epilepsy.

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