Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming majority of people with epilepsy regard the unpredictability of seizures as a major issue. More than 30 years of international effort have been devoted to the prediction of seizures, aiming to remove the burden of unpredictability and to couple novel, time-specific treatment to seizure prediction technology. A highly influential review published in 2007 concluded that insufficient evidence indicated that seizures could be predicted. Since then, several advances have been made, including successful prospective seizure prediction using intracranial EEG in a small number of people in a trial of a real-time seizure prediction device. In this Review, we examine advances in the field, including EEG databases, seizure prediction competitions, the prospective trial mentioned and advances in our understanding of the mechanisms of seizures. We argue that these advances, together with statistical evaluations, set the stage for a resurgence in efforts towards the development of seizure prediction methodologies. We propose new avenues of investigation involving a synergy between mechanisms, models, data, devices and algorithms and refine the existing guidelines for the development of seizure prediction technology to instigate development of a solution that removes the burden of the unpredictability of seizures.

Impaired consciousness requires altered cortical function. This can occur either directly from disorders that impair widespread bilateral regions of the cortex or indirectly through effects on subcortical arousal systems. It has therefore long been puzzling why focal temporal lobe seizures so often impair consciousness. Early work suggested that altered consciousness may occur with bilateral or dominant temporal lobe seizure involvement. However, other bilateral temporal lobe disorders do not impair consciousness. More recent work supports a 'network inhibition hypothesis' in which temporal lobe seizures disrupt brainstem-diencephalic arousal systems, leading indirectly to depressed cortical function and impaired consciousness. Indeed, prior studies show subcortical involvement in temporal lobe seizures and bilateral frontoparietal slow wave activity on intracranial electroencephalography. However, the relationships between frontoparietal slow waves and impaired consciousness and between cortical slowing and fast seizure activity have not been directly investigated. We analysed intracranial electroencephalography recordings during 63 partial seizures in 26 patients with surgically confirmed mesial temporal lobe epilepsy. Behavioural responsiveness was determined based on blinded review of video during seizures and classified as impaired (complex-partial seizures) or unimpaired (simple-partial seizures). We observed significantly increased delta-range 1-2 Hz slow wave activity in the bilateral frontal and parietal neocortices during complex-partial compared with simple-partial seizures. In addition, we confirmed prior work suggesting that propagation of unilateral mesial temporal fast seizure activity to the bilateral temporal lobes was significantly greater in complex-partial than in simple-partial seizures. Interestingly, we found that the signal power of frontoparietal slow wave activity was significantly correlated with the temporal lobe fast seizure activity in each hemisphere. Finally, we observed that complex-partial seizures were somewhat more common with onset in the language-dominant temporal lobe. These findings provide direct evidence for cortical dysfunction in the form of bilateral frontoparietal slow waves associated with impaired consciousness in temporal lobe seizures. We hypothesize that bilateral temporal lobe seizures may exert a powerful inhibitory effect on subcortical arousal systems. Further investigations will be needed to fully determine the role of cortical-subcortical networks in ictal neocortical dysfunction and may reveal treatments to prevent this important negative consequence of temporal lobe epilepsy.

Electrocorticograms (ECoG's) from 16 of 68 chronically implanted subdural electrodes, placed over the right temporal cortex in a patient with a right medial temporal focus, were analyzed using methods from nonlinear dynamics. A time series provides information about a large number of pertinent variables, which may be used to explore and characterize the system's dynamics. These variables and their evolution in time produce the phase portrait of the system. The phase spaces for each of 16 electrodes were constructed and from these the largest average Lyapunov exponents (L's), measures of chaoticity of the system (the larger the L, the more chaotic the system is), were estimated over time for every electrode before, in and after the epileptic seizure for three seizures of the same patient. The start of the seizure corresponds to a simultaneous drop in L values obtained at the electrodes nearest the focus. L values for the rest of the electrodes follow. The mean values of L for all electrodes in the postictal state are larger than the ones in the preictal state, denoting a more chaotic state postictally. The lowest values of L occur during the seizure but they are still positive denoting the presence of a chaotic attractor. Based on the procedure for the estimation of L we were able to develop a methodology for detecting prominent spikes in the ECoG. These measures (L*) calculated over a period of time (10 minutes before to 10 minutes after the seizure outburst) revealed a remarkable coherence of the abrupt transient drops of L* for the electrodes that showed the initial ictal onset. The L* values for the electrodes away from the focus exhibited less abrupt transient drops. These results indicate that the largest average Lyapunov exponent L can be useful in seizure detection as well as a discriminatory factor for focus localization in multielectrode analysis.

Studies of working memory load effects on human EEG power have indicated divergent effects in different frequency bands. Although gamma power typically increases with load, the load dependency of the lower frequency theta and alpha bands is uncertain. We obtained intracranial electroencephalography measurements from 1453 electrode sites in 14 epilepsy patients performing a Sternberg task, in order to characterize the anatomical distribution of load-related changes across the frequency spectrum. Gamma power increases occurred throughout the brain, but were most common in the occipital lobe. In the theta and alpha bands, both increases and decreases were observed, but with different anatomical distributions. Increases in theta and alpha power were most prevalent in frontal midline cortex. Decreases were most commonly observed in occipital cortex, colocalized with increases in the gamma range, but were also detected in lateral frontal and parietal regions. Spatial overlap with group functional magnetic resonance imaging results was minimal except in the precentral gyrus. These findings suggest that power in any given frequency band is not a unitary phenomenon; rather, reactivity in the same frequency band varies in different brain regions, and may relate to the engagement or inhibition of a given area in a cognitive task.

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Seizure occurrence in partial epilepsy is not random. Endogenous circadian rhythms and rhythmic exogenous factors likely play substantial roles in seizure occurrence. These roles vary considerably according to brain region. Frontal and parietal lobe seizures seem most likely to occur nocturnally, whereas occipital and temporal lobe seizures seem to have strong afternoon preferences.

An excess of extracellular glutamate in the hippocampus has been linked to the generation of recurrent seizures and brain pathology in patients with medically intractable mesial temporal lobe epilepsy (MTLE). However, the mechanism which results in glutamate excess in MTLE remains unknown. We recently reported that the glutamate-metabolizing enzyme glutamine synthetase is deficient in the hippocampus in patients with MTLE, and we postulated that this deficiency is critically involved in the pathophysiology of the disease. To further explore the role of glutamine synthetase in MTLE we created a novel animal model of hippocampal glutamine synthetase deficiency by continuous (approximately 28 days) microinfusion of methionine sulfoximine (MSO: 0.625 to 2.5 microg/h) unilaterally into the hippocampus in rats. This treatment led to a deficiency in hippocampal glutamine synthetase activity by 82-97% versus saline. The majority (>95%) of the MSO-treated animals exhibited recurrent seizures that continued for several weeks. Some of the MSO-treated animals exhibited neuropathological features that were similar to mesial temporal sclerosis, such as hippocampal atrophy and patterned loss of hippocampal neurons. However, many MSO-treated animals displayed only minimal injury to the hippocampus, with no clear evidence of mesial temporal sclerosis. These findings support the hypothesis that a deficiency in hippocampal glutamine synthetase causes recurrent seizures, even in the absence of classical mesial temporal sclerosis, and that restoration of glutamine synthetase may represent a novel approach to therapeutic intervention in this disease.

SUMMARYPurpose: Because of the large and continuous energetic requirements of brain function, neurometabolic dysfunction is a key pathophysiologic aspect of the epileptic brain. Additionally, neurometabolic dysfunction has many self-propagating features that are typical of epileptogenic processes, that is, where each occurrence makes the likelihood of further mitochondrial and energetic injury more probable. Thus abnormal neurometabolism may be not only a chronic accompaniment of the epileptic brain, but also a direct contributor to epileptogenesis. Methods: We examine the evidence for neurometabolic dysfunction in epilepsy, integrating human studies of metabolic imaging, electrophysiology, microdialysis, as well as intracranial EEG and neuropathology. Results: As an approach of noninvasive functional imaging, quantitative magnetic resonance spectroscopic imaging (MRSI) measured abnormalities of mitochondrial and energetic dysfunction (via 1H or 31P spectroscopy) are related to several pathophysiologic indices of epileptic dysfunction. With patients undergoing hippocampal resection, intraoperative 13C-glucose turnover studies show a profound decrease in neurotransmitter (glutamate-glutamine) cycling relative to oxidation in the sclerotic hippocampus. Increased extracellular glutamate (which has long been associated with increased seizure likelihood) is significantly linked with declining energetics as measured by 31P MR, as well as with increased EEG measures of Teager energy, further arguing for a direct role of glutamate with hyperexcitability. Discussion: Given the important contribution that metabolic performance makes toward excitability in brain, it is not surprising that numerous aspects of mitochondrial and energetic state link significantly with electrophysiologic and microdialysis measures in human epilepsy. This may be of particular relevance with the self-propagating nature of mitochondrial injury, but may also help define the conditions for which interventions may be developed.