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.
机构:
Canterbury Christ Church Univ, Media & Cultural Studies, Canterbury, Kent, EnglandCanterbury Christ Church Univ, Media & Cultural Studies, Canterbury, Kent, England
机构:
Univ Illinois, Coll Med Peoria, Peoria, IL 61605 USA
Univ Illinois, Coll Med Peoria, Dept Gen Surg, Peoria, IL USAUniv Illinois, Coll Med Peoria, Peoria, IL 61605 USA
Evans, Chadrick R.
Medina, Melissa G.
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Univ Illinois, Coll Med Peoria, Peoria, IL 61605 USA
Univ Illinois, Coll Med Peoria, Dept Gen Surg, Peoria, IL USAUniv Illinois, Coll Med Peoria, Peoria, IL 61605 USA
Medina, Melissa G.
Dwyer, Anthony Michael
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Univ Illinois, Coll Med Peoria, Peoria, IL 61605 USAUniv Illinois, Coll Med Peoria, Peoria, IL 61605 USA