Seizure Prediction: Science Fiction or Soon to Become Reality?
Current Neurology and Neuroscience Reports, ISSN: 1534-6293, Vol: 15, Issue: 11, Page: 73
2015
- 55Citations
- 118Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations55
- Citation Indexes55
- CrossRef55
- 55
- Captures118
- Readers118
- 118
Review Description
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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84942425878&origin=inward; http://dx.doi.org/10.1007/s11910-015-0596-3; http://www.ncbi.nlm.nih.gov/pubmed/26404726; http://link.springer.com/10.1007/s11910-015-0596-3; https://dx.doi.org/10.1007/s11910-015-0596-3; https://link.springer.com/article/10.1007/s11910-015-0596-3
Springer Science and Business Media LLC
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