Focal seizures unfold variably over time.

This scientific commentary refers to 'Chronic intracranial EEG recordings and interictal spike rate reveal multiscale temporal modulations in seizure states' by Schroeder et al. (https://doi.org/10.1093/braincomms/fcad205)

Passive and active markers of cortical excitability in epilepsy

Electroencephalography (EEG) has been the primary diagnostic tool in clinical epilepsy for nearly a century. Its review is performed using qualitative clinical methods that have changed little over time. However, the intersection of higher resolution digital EEG and analytical tools developed in the past decade invites a re-exploration of relevant methodology. In addition to the established spatial and temporal markers of spikes and high-frequency oscillations, novel markers involving advanced postprocessing and active probing of the interictal EEG are gaining ground. This review provides an overview of the EEG-based passive and active markers of cortical excitability in epilepsy and of the techniques developed to facilitate their identification. Several different emerging tools are discussed in the context of specific EEG applications and the barriers we must overcome to translate these tools into clinical practice

Intrinsic neural timescales in the temporal lobe support an auditory processing hierarchy

During rest, intrinsic neural dynamics manifest at multiple timescales, which progressively increase along visual and somatosensory hierarchies. Theoretically, intrinsic timescales are thought to facilitate processing of external stimuli at multiple stages. However, direct links between timescales at rest and sensory processing, as well as translation to the auditory system are lacking. Here, we measured intracranial electroencephalography in 11 human patients with epilepsy (4 women), while listening to pure tones. We show that in the auditory network, intrinsic neural timescales progressively increase, while the spectral exponent flattens, from temporal to entorhinal cortex, hippocampus, and amygdala. Within the neocortex, intrinsic timescales exhibit spatial gradients that follow the temporal lobe anatomy. Crucially, intrinsic timescales at baseline can explain the latency of auditory responses: as intrinsic timescales increase, so do the single-electrode response onset and peak latencies. Our results suggest that the human auditory network exhibits a repertoire of intrinsic neural dynamics, which manifest in cortical gradients with millimeter resolution and may provide a variety of temporal windows to support auditory processing.SIGNIFICANCE STATEMENT:Endogenous neural dynamics are often characterized by their intrinsic timescales. These are thought to facilitate processing of external stimuli. However, a direct link between intrinsic timing at rest and sensory processing is missing. Here, with intracranial electroencephalography (iEEG), we show that intrinsic timescales progressively increase from temporal to entorhinal cortex, hippocampus, and amygdala. Intrinsic timescales at baseline can explain the variability in the timing of iEEG responses to sounds: cortical electrodes with fast timescales also show fast and short-lasting responses to auditory stimuli, which progressively increase in the hippocampus and amygdala. Our results suggest that a hierarchy of neural dynamics in the temporal lobe manifests across cortical and limbic structures and can explain the temporal richness of auditory responses

The Impact of Sleep Fragmentation on Sleep Homeostasis, Brain and Peripheral Energy Metabolism and Spatial Learning

The quality of sleep has recently come to the forefront of public health concerns in industrialized nations. Indeed, voluntary sleep curtailment is widespread, sleep disorders are increasingly recognized and both correlate with the current epidemiology of diabetes and obesity (Van Cauter and Knutson, 2008). Sleep fragmentation (SF) is a periodic disruption found in highly prevalent sleep-related breathing and movement disorders, where the sleeper might be aroused several hundred times per night. By roughly summing the prevalence of obstructive sleep apnea (OSA) syndromes and periodic limb movement disorders, two of the most common sleep disorders, we predict a total prevalence for SF of nearly 15% in the European active population. Overlooked cases and insufficient concern for the problematic bear a major socioeconomic burden because of the broad impact of excessive daytime sleepiness on productivity (Hossain and Shapiro, 2002), motor vehicle accidents (Aldrich, 1989) and medical complications (Spiegel et al., 2009). Recurrent interference with the natural architecture of sleep leads to sleepiness, difficulty in concentration and cognitive impairments such as decreased reaction times and poor working memory equivalent to a full night of sleep deprivation in severe cases (Bonnet, 1985, 1989; Stepanski, 2002). In addition, recent experimental evidence in humans has unraveled the unprecedented link between sleep of poor quality and dramatic endocrine imbalances such as deregulation of appetite controlling hormones, glucocorticoids and increase in sympathetic tone, ultimately leading to the development of insulin resistance (Spiegel et al., 2009; Stamatakis and Punjabi, 2010). Current animal models for the study of sleep pathology mostly involve short intervention often biased by stress induction and usually involving a complete period of sleep deprivation. These models do not tightly reflect the most common clinical pattern characterized by sleep perturbation over long periods of time. Therefore, paying attention to maximally avoid methodological stress, we designed a new device aiming at performing instrumental SF for fourteen days in mice. Our model mimics SF observed in sleep disorders since it has no major impact on circadian timing and total amount of sleep but clearly shortens individual sleep episodes. With this method, we approached three problematics that were insufficiently addressed in the literature. In our first study, we addressed the question of whether SF could trigger electrophysiological and molecular sleep homeostasis mechanisms in the short-term and whether these effects could be maintained in the long-term. We showed that SF leads to an anticipated homeostatic regulation of Slow Wave Activity (SWA), the sleep EEG hallmark of sleep homeostasis. Furthermore, EEG spectral analysis revealed an unexpected power increase in 4-40 Hz frequencies during sleep with a clear increase in the amplitude of slow waves and spindles. We concluded that sustained sleep pressure in SF leads to a global increase in cortical synchronization. We next explored whether these electrophysiological changes could impact on the expression of transcripts known to be regulated by sleep homeostasis (immediate early genes, clock-genes and heat shock proteins). Only heat shock proteins showed a consistent induction after one day but normalized after fourteen days of SF. These results point to the fact that electrophysiological and molecular aspects of sleep homeostasis are dissociable and that long-term sleep pressure triggers allostatic cellular processes of adaptation. In our second study, we explored the effects of long-term SF on general metabolism. We showed that SF led to a general imbalance in energy intake and expenditure, possibly through a slight elevation of brain temperature at rest. We also observed that glucocorticoids were slightly elevated at given circadian points and were accompanied by glucose intolerance. Altogether, this study brings evidence for the participation of SF in addition to intermittent hypoxia in the development of a metabolic syndrome in OSA patients. In the third study, we combined our chronic model with a spatial learning task spanning over several days (Morris Water Maze) in order to study the impact of SF on memory and metabolic plasticity. We showed that SF impaired proper memory consolidation supporting the idea that continuous sleep is required for specific mechanisms of memory trace post-processing. We also provide preliminary evidence that brain energy metabolism is not optimally responsive to neural activation after SF and that this effect might underlie the observed cognitive impairment. In conclusion, we showed that our animal SF model is suitable for studying the specific mechanisms underlying cognitive impairments and metabolic imbalance observed in sleep medicine. Our results underscore the existence of a global allostatic load in a wide range of systems during SF. Sensitization of the population to the prevalence of SF and its stealthy mode of presentation might improve its detection. Increased recognition of the problematic would be especially beneficial to cognitive development in school children with sleep apnea and might reduce accidents related to sleepiness. More specifically, we propose that screening sleep quality and effective correction of SF in patients with endocrine disorders has the potential to improve glucose metabolism and energy balance

Under-sampling in epilepsy: Limitations of conventional EEG.

The cyclical structure of epilepsy was recently (re)-discovered through years-long intracranial electroencephalography (EEG) obtained with implanted devices. In this review, we discuss how new revelations from chronic EEG relate to the practice and interpretation of conventional EEG. We argue for an electrographic definition of seizures and highlight the caveats of counting epileptiform discharges in EEG recordings of short duration. Limitations of conventional EEG have practical implications with regard to titrating anti-seizure medications and allowing patients to drive, and we propose that chronic monitoring of brain activity could greatly improve epilepsy care. An impending paradigm shift in epilepsy will involve using next-generation devices for chronic EEG to leverage known biomarkers of disease state