The Road to Practical Epileptic Seizure Prediction Part - 1

Researchers have been working on models of brain function for over 40 years, and while progress has been made in understanding and predicting the onset of epileptic seizures, a practical system remains elusive. Deconstructed and simplified models of the brain have failed time and again to capture the complex and nonlinear dynamics which arise at the system level during a seizure. Currently, the development and success of machine learning techniques in other fields, proliferation of affordable computing power and storage, and the open sharing of clinical datasets are all combining to attract and engage an interdisciplinary community of interested researchers. If this community pools their resources and talents, applies a rigorous discipline of validating their results, and works to improve the quality and diversity of patient time series data, it is extremely likely they will be able to translate the power of these techniques over to the field of neuroscience, producing breakthroughs in understanding and treating epilepsy and other neurological disorders. Citation: Adam Lichtl and Oleg Tcheremissine. “The Road to Practical Epileptic Seizure Prediction Part-1”. EC Neurology 2.4 (2015): 205-209.