Seizure Prediction: Science Fiction or Soon to Become Reality?

Abstract

This review highlights recent developments in the field of epileptic seizure prediction. We argue that seizure prediction is possible; however, most previous attempts have used data with an insufficient amount of information to solve the problem. The review discusses four methods for gaining more information above standard clinical electrophysiological recordings. We first discuss developments in obtaining long-term data that enables better characterisation of signal features and trends. Then, we discuss the usage of electrical stimulation to probe neural circuits to obtain robust information regarding excitability. Following this, we present a review of developments in high-resolution micro-electrode technologies that enable neuroimaging across spatial scales. Finally, we present recent results from data-driven model-based analyses, which enable imaging of seizure generating mechanisms from clinical electrophysiological measurements. It is foreseeable that the field of seizure prediction will shift focus to a more probabilistic forecasting approach leading to improvements in the quality of life for the millions of people who suffer uncontrolled seizures. However, a missing piece of the puzzle is devices to acquire long-term high-quality data. When this void is filled, seizure prediction will become a reality.

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Acknowledgments

The authors acknowledge the support from the Australian National Health and Medical Research Council Project Grant (APP1065638). Dr Freestone acknowledges the support of the Australian-American Fulbright Commission and would also like to thank Professor Liam Paninski for his support. The authors would also like to thank Associate Professor Bruce Gluckmann for insightful discussions and pointing out that sometimes you have to look backward to go forward.

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Conflict of Interest

Dean R. Freestone, Philippa J. Karoly, Andre D. H. Peterson, Levin Kuhlmann, Alan Lai, and Farhad Goodarzy declare that they have no conflict of interest. Mark J. Cook was lead investigator in the NeuroVista study cited in the publication. However, Dr. Cook had no financial relationship with the sponsors.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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Correspondence to Dean R. Freestone or Mark J. Cook.

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This article is part of the Topical Collection on Epilepsy

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Freestone, D.R., Karoly, P.J., Peterson, A.D.H. et al. Seizure Prediction: Science Fiction or Soon to Become Reality?. Curr Neurol Neurosci Rep 15, 73 (2015). https://doi.org/10.1007/s11910-015-0596-3

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Keywords

  • Epileptic seizure prediction
  • Electrophysiology
  • Computational neuroscience
  • Active EEG
  • Ambulatory EEG
  • Micro-electrode
  • Review