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Cited by 20Epilepsy research and treatmentEEG and Brain-Computer InterfacesNeural dynamics and brain function

Seizure probability in animal models of acquired epilepsy: a perspective on the concept of the preictal state

Dudek, F. Edward, Staley, Kevin J.·2011·Epilepsy Research
DOI 10.1016/j.eplepsyres.2011.10.017
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Abstract

The concept of a preictal state is based on the belief that it may be possible to predict seizures before they occur. The preictal state is viewed as a time period when a seizure is practically inevitable, or at least a period of greatly increased seizure probability. Changes in seizure frequency may provide insight into how seizure probability increases after brain injury. Here, time-dependent changes in the frequency of spontaneous recurrent seizures after brain injury are summarized from published, nearly continuous, electrographic (EEG) recordings of kainate-treated rats and neonatal rats subjected to hypoxia-ischemia. For these animal models, seizure frequency - and thus seizure probability - was a sigmoid function of time after the brain injury. This observation differs from the traditional view, where the development of epilepsy after brain injury is a step-function of time, and the latent period is the time between a brain injury and the first spontaneous seizure. Based on backward extrapolation of the plots of seizure frequency versus time, these data suggest that seizure probability increases continuously during the latent period. Also, spontaneous recurrent seizures frequently occurred in clusters, suggesting that the intra-cluster seizure intervals are periods of high seizure probability. Thus, seizure probability progressively increases as a function of time after an epileptogenic brain injury, and is particularly high between seizures within a cluster, as compared to the time between clusters. These data suggest that the detectors of the preictal state need to be accurate (and tested) over a very wide range of seizure probabilities, and that studies on the physiological events that occur during seizure clusters may provide insight on the properties of the preictal state.

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  • Limbic epileptogenesis involves a partially-understood molecular cascade that results in aberrant neuronal connectivity and chronic recurrent spontaneous seizures.

    “Development of TLE or limbic epileptogenesis [4, 5] involves a partially-understood molecular cascade [6] that results in aberrant neuronal connectivity [7, 8] from a multi-architecture neuronal network of the limbic system connected to hippocampal formation [9] that contributes to a systemic process in the brain that leads to chronic recurrent spontaneous seizures [10].”

    From Hippocampal neuro-networks and dendritic spine perturbations in epileptogenesis are attenuated by neuroprotectin D1 (2015) · cites this paper as [4]

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Authors
Dudek, F. E., & Staley, K. J.
Affiliations
  • University of Utah (US)
  • Massachusetts General Hospital (US)
Corresponding author
Dudek, F. Edward
ORCID
Venue
Epilepsy Research
Publisher
Elsevier BV
Published
2011-12
Volume
97
Issue
3
Pages
324-331
ISSN
0920-1211 (ISSN-L)
DOI
10.1016/j.eplepsyres.2011.10.017
OpenAlex
W2054858102
Cited by
20
References
39
Citations by year
2025: 2 · 2024: 1 · 2022: 3 · 2019: 2 · 2018: 1 · 2017: 2 · 2016: 1 · 2015: 3 · 2014: 1 · 2013: 2 · 2012: 2
FWCI
1.09
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Epilepsy Research (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • NINDS
  • American Heart Association
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Epilepsy research and treatment
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
preictal state, acquired epilepsy, epileptogenesis, brain injury, kainate-induced seizures, hypoxia-ischemia, neonatal rats, seizure frequency, seizure clusters, latency, EEG recording, seizure prediction
MeSH terms
Animals, Disease Models, Animal, Epilepsy, Humans, Predictive Value of Tests, Probability, Seizures, Rats

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