Acquired epilepsy (i.e., after an insult to the brain) is often considered to be a progressive disorder, and the nature of this hypothetical progression remains controversial. Antiepileptic drug treatment necessarily confounds analyses of progressive changes in human patients with acquired epilepsy. Here, we describe experiments testing the hypothesis that development of acquired epilepsy begins as a continuous process of increased seizure frequency (i.e., proportional to probability of a spontaneous seizure) that ultimately plateaus. Using nearly continuous surface cortical and bilateral hippocampal recordings with radiotelemetry and semiautomated seizure detection, the frequency of electrographically recorded seizures (both convulsive and nonconvulsive) was analyzed quantitatively for ϳ100 d after kainate-induced status epilepticus in adult rats. The frequency of spontaneous recurrent seizures was not a step function of time (as implied by the "latent period"); rather, seizure frequency increased as a sigmoid function of time. The distribution of interseizure intervals was nonrandom, suggesting that seizure clusters (i.e., short interseizure intervals) obscured the early stages of progression, and may have contributed to the increase in seizure frequency. These data suggest that (1) the latent period is the first of many long interseizure intervals and a poor measure of the time frame of epileptogenesis, (2) epileptogenesis is a continuous process that extends much beyond the first spontaneous recurrent seizure, (3) uneven seizure clustering contributes to the variability in occurrence of epileptic seizures, and (4) the window for antiepileptogenic therapies aimed at suppressing acquired epilepsy probably extends well past the first clinical seizure.
Synaptic reorganization of the dentate gyrus inner molecular layer (IML) is a pathophysiological process that may facilitate seizures in patients with temporal-lobe epilepsy. Two subtypes of IML neurons were originally described by Ramón y Cajal (1995), but have not been thoroughly studied. We used two-photon imaging, infrared-differential interference contrast microscopy and patch clamp recordings from rat hippocampal slices to define the intrinsic physiology and synaptic targets of spiny, granule-like neurons in the IML, termed semilunar granule cells (SGCs). These neurons resembled dentate granule cells but had axon collaterals in the molecular layer, significantly larger dendritic arborization in the molecular layer, and a more triangular cell body than granule cells. Unlike granule cells, SGCs fired throughout long-duration depolarizing steps and had ramp-like depolarizations during interspike periods. Paired recordings demonstrated that SGCs are glutamatergic and monosynaptically excite both hilar interneurons and mossy cells. Semilunar granule cells appear to represent a distinct excitatory neuron population in the dentate gyrus that may be an important target for mossy fiber sprouting in patients and rodent models of temporal lobe epilepsy.
SUMMARYPurpose: Chronic epilepsy frequently develops after brain injury, but prediction of which individual patient will develop spontaneous recurrent seizures (i.e., epilepsy) is not currently possible. Here, we use continuous radiotelemetric electroencephalography (EEG) and video monitoring along with automated computer detection of EEG spikes and seizures to test the hypothesis that EEG spikes precede and are correlated with subsequent spontaneous recurrent seizures. Methods: The presence and pattern of EEG spikes was studied during long recording epochs between the end of status epilepticus (SE) induced by three different doses of kainate and the onset of chronic epilepsy. Results: The presence of spikes, and later spike clusters, over several days after SE before the first spontaneous seizure, was consistently associated with the development of chronic epilepsy. The rate of development of epilepsy (i.e., increase in seizure frequency) was strongly correlated with the frequency of EEG spikes and the cumulative number of EEG spikes after SE. Conclusions: The temporal features of EEG spikes (i.e., their presence, frequency, and pattern [clusters]) when analyzed over prolonged periods, may be a predictive biomarker for the development of chronic epilepsy after brain injury. Future clinical trials using prolonged EEG recordings may reveal the diagnostic utility of EEG spikes as predictors of subsequent epilepsy in brain-injured humans.
These data suggest that animal models with spontaneous seizures, such as kainate- and pilocarpine-treated rats, can be used efficiently for rapid testing of AEDs with a repeated-measures, crossover protocol. Furthermore, the results indicate that this design allows both dose-effect and time-course-of-recovery studies.
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