Facilitation of epileptic activity during sleep is mediated by high amplitude slow waves

Epileptic discharges in focal epilepsy are frequently activated during non-rapid eye movement sleep. Sleep slow waves are present during this stage and have been shown to include a deactivated ('down', hyperpolarized) and an activated state ('up', depolarized). The 'up' state enhances physiological rhythms, and we hypothesize that sleep slow waves and particularly the 'up' state are the specific components of non-rapid eye movement sleep that mediate the activation of epileptic activity. We investigated eight patients with pharmaco-resistant focal epilepsies who underwent combined scalp-intracerebral electroencephalography for diagnostic evaluation. We analysed 259 frontal electroencephalographic channels, and manually marked 442 epileptic spikes and 8487 high frequency oscillations during high amplitude widespread slow waves, and during matched control segments with low amplitude widespread slow waves, non-widespread slow waves or no slow waves selected during the same sleep stages (total duration of slow wave and control segments: 49 min each). During the slow waves, spikes and high frequency oscillations were more frequent than during control segments (79% of spikes during slow waves and 65% of high frequency oscillations, both P ~ 0). The spike and high frequency oscillation density also increased for higher amplitude slow waves. We compared the density of spikes and high frequency oscillations between the 'up' and 'down' states. Spike and high frequency oscillation density was highest during the transition from the 'up' to the 'down' state. Interestingly, high frequency oscillations in channels with normal activity expressed a different peak at the transition from the 'down' to the 'up' state. These results show that the apparent activation of epileptic discharges by non-rapid eye movement sleep is not a state-dependent phenomenon but is predominantly associated with specific events, the high amplitude widespread slow waves that are frequent, but not continuous, during this state of sleep. Both epileptic spikes and high frequency oscillations do not predominate, like physiological activity, during the 'up' state but during the transition from the 'up' to the 'down' state of the slow wave, a period of high synchronization. Epileptic discharges appear therefore more associated with synchronization than with excitability. Furthermore, high frequency oscillations in channels devoid of epileptic activity peak differently during the slow wave cycle from those in channels with epileptic activity. This property may allow differentiating physiological from pathological high frequency oscillations, a problem that is unresolved until now

Dreaming furiously? – A sleep laboratory study on the dream content of people with parkinson's disease and with or without rapid eye movement sleep behavior disorder

Objective: Rapid eye movement (REM) sleep behavior disorder (RBD) has been related to altered, action-filled, vivid, and aggressive dream content, but research comparing the possible differences in dreams of Parkinson&#39;s disease (PD) patients with and without RBD is scarce. The dream content of PD patients with and without RBD was analyzed with specific focus on action-filledness, vividness, emotional valence, and threats. Methods: A total of 69 REM and NREM dream reports were collected in the sleep laboratory, 37 from nine PD patients with RBD and 32 from six PD patients without RBD. A content analysis of (1) action-filledness (actions and environmental events); (2) vividness (emotions and cognitive activity); (3) intensity of actions, events and emotions; (4) emotional valence, and (5) threatening events was performed on the transcripts. Results: Altogether 563 dream elements expressing action-filledness and vividness were found. There were no significant between-group differences in the number or distribution of elements reflecting action-filledness or vividness, emotional valence or threats. In within-group analyses, PD patients with RBD had significantly more negative compared to positive dreams (p = 0.012) and compared to PD patients without RBD, a tendency to have more intense actions in their dreams (p = 0.066). Conclusions: Based on the results of this study, there are no major between-group differences in the action-filledness, vividness, or threat content of dreams of PD patients with and without RBD. However, within-group analyses revealed that dreams were more often negatively than positively toned in PD patients with RBD.</p

Generalizability of electroencephalographic interpretation using artificial intelligence : An external validation study

The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE-AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings. We assessed the diagnostic accuracy of a "fixed-and-frozen" AI model, using an independent dataset and external gold standard, and benchmarked it against three experts blinded to all other data. The dataset comprised 50% normal and 50% abnormal routine EEGs, equally distributed among the four major classes of EEG abnormalities (focal epileptiform, generalized epileptiform, focal nonepileptiform, and diffuse nonepileptiform). To assess diagnostic accuracy, we computed sensitivity, specificity, and accuracy of the AI model and the experts against the external gold standard. We analyzed EEGs from 104 patients (64 females, median age = 38.6 [range = 16-91] years). SCORE-AI performed equally well compared to the experts, with an overall accuracy of 92% (95% confidence interval [CI] = 90%-94%) versus 94% (95% CI = 92%-96%). There was no significant difference between SCORE-AI and the experts for any metric or category. SCORE-AI performed well independently of the vigilance state (false classification during awake: 5/41 [12.2%], false classification during sleep: 2/11 [18.2%]; p =.63) and normal variants (false classification in presence of normal variants: 4/14 [28.6%], false classification in absence of normal variants: 3/38 [7.9%]; p =.07). SCORE-AI achieved diagnostic performance equal to human experts in an EEG dataset independent of the development dataset, in a geographically distinct patient population, recorded with different equipment and technical settings than the development dataset

Sleep and epilepsy: A snapshot of knowledge and future research lines

Sleep and epilepsy have a reciprocal relationship, and have been recognized as bedfellows since antiquity. However, research on this topic has made a big step forward only in recent years. In this narrative review we summarize the most stimulating discoveries and insights reached by the “European school.” In particular, different aspects concerning the sleep–epilepsy interactions are analysed: (a) the effects of sleep on epilepsy; (b) the effects of epilepsy on sleep structure; (c) the relationship between epilepsy, sleep and epileptogenesis; (d) the impact of epileptic activity during sleep on cognition; (e) the relationship between epilepsy and the circadian rhythm; (f) the history and features of sleep hypermotor epilepsy and its differential diagnosis; (g) the relationship between epilepsy and sleep disorders

HippoMaps: Multiscale cartography of human hippocampal organization

The hippocampus has a specialized microarchitecture, is situated at the nexus of multiple macroscale functional networks, contributes to numerous cognitive as well as affective processes and is highly susceptible to brain pathology across common disorders. These features make the hippocampus a model to understand how brain structure covaries with function, in both health and disease. Here we introduce HippoMaps, an open access toolbox and online data warehouse for the mapping and contextualization of subregional hippocampal data in the human brain ( http://hippomaps.readthedocs.io ). HippoMaps capitalizes on a unified hippocampal unfolding approach as well as shape intrinsic registration capabilities to allow for cross-participant and cross-modal data aggregation. We initialize this repository with a combination of hippocampal data spanning three-dimensional ex vivo histology, ex vivo 9.4-Tesla magnetic resonance imaging (MRI), as well as in vivo structural MRI and resting-state functional MRI obtained at 3 Tesla and 7 Tesla, together with intracranial encephalography recordings in patients with epilepsy. All code, data and tools are openly available online, with the aim of fostering further community contributions

Temporal lobe epilepsy perturbs the brain‐wide excitation‐inhibition balance: Associations with microcircuit organization, clinical parameters, and cognitive dysfunction

Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole-brain level, and its microcircuit-level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting-state fMRI time series, and microcircuit parameters are simulated using biophysical models. A broad decrease in the Hurst exponent is observed in pharmaco-resistant temporal lobe epilepsy (TLE), suggesting more excitable network dynamics. Connectome decoders point to temporolimbic and frontocentral cortices as plausible network epicenters of E/I imbalance. Furthermore, computational simulations reveal that enhancing cortical excitability in TLE reflects atypical increases in recurrent connection strength of local neuronal ensembles. Mixed cross-sectional and longitudinal analyses show stronger E/I ratio elevation in patients with longer disease duration, more frequent electroclinical seizures as well as interictal epileptic spikes, and worse cognitive functioning. Hurst exponent-informed classifiers discriminate patients from healthy controls with high accuracy (72.4% [57.5%-82.5%]). Replicated in an independent dataset, this work provides in vivo evidence of a macroscale shift in E/I balance in TLE patients and points to progressive functional imbalances that relate to cognitive decline

Pharmaco-resistant temporal lobe epilepsy gradually perturbs the cortex-wide excitation-inhibition balance

Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with a mounting body of previous research focusing on elucidating its cellular manifestations. However, there are limited studies into E/I imbalance at macroscale and its microcircuit-level mechanisms and clinical associations. In our current work, we computed the Hurst exponent—a previously validated index of the E/I ratio—from resting-state fMRI time series, and simulated microcircuit parameters using biophysical computational models. We found a broad reduction in the Hurst exponent in pharmaco-resistant temporal lobe epilepsy (TLE), indicative of a shift towards more excitable network dynamics. Connectome decoders pointed to temporolimbic and frontocentral areas as plausible network epicenters of E/I imbalance. Computational simulations further revealed that enhancing cortical excitability in patients likely reflected atypical increases in recurrent connection strength of local neuronal ensembles. Moreover, mixed cross-sectional and longitudinal analyses revealed heightened E/I elevation in patients with longer disease duration, more frequent electroclinical seizures and inter-ictal epileptic spikes, and worse cognitive functioning. Replicated in an independent dataset, our work provides compelling in-vivo evidence of a macroscale shift in E/I balance in TLE patients that undergoes progressive changes and underpins cognitive impairments, potentially informing treatment strategies targeting E/I mechanisms

GBA mutations are associated with Rapid eye movement sleep behavior disorder

Rapid eye movement sleep behavior disorder and GBA mutations are both associated with Parkinson’s disease. The GBA gene was sequenced in idiopathic rapid eye movement sleep behavior disorder patients (n = 265), and compared to controls (n = 2240). Rapid eye movement sleep behavior disorder questionnaire was performed in an independent Parkinson’s disease cohort (n = 120). GBA mutations carriers had an OR of 6.24 (10.2% in patients vs. 1.8% in controls, P < 0.0001) for rapid eye movement sleep behavior disorder, and among Parkinson’s disease patients, the OR for mutation carriers to have probable rapid eye movement sleep behavior disorder was 3.13 (P = 0.039). These results demonstrate that rapid eye movement sleep behavior disorder is associated with GBA mutations, and that combining genetic and prodromal data may assist in identifying individuals susceptible to Parkinson’s disease

The role of the melanoma gene MC1R in Parkinson disease and REM sleep behavior disorder

The MC1R gene, suggested to be involved in Parkinson disease (PD) and melanoma, was sequenced in PD patients (n=539) and controls (n=265) from New-York, and PD patients (n=551), rapid eye movement sleep behavior disorder (RBD) patients (n=351) and controls (n=956) of European ancestry. Sixty-eight MC1R variants were identified, including 7 common variants with frequency>0.01. None of the common variants was associated with PD or RBD in the different regression models. In a meta-analysis with fixed-effect model, the p.R160W variant was associated with an increased risk for PD (OR=1.22, 95%CI 1.02-1.47, p=0.03) but with significant heterogeneity (p=0.048). Removing one study that introduced the heterogeneity resulted in nonsignificant association (OR=1.11, 95%CI 0.92-1.35, p=0.27, heterogeneity p=0.57). Rare variants had similar frequencies in patients and controls (10.54% and 10.15%, respectively, p=0.75), and no cumulative effect of carrying more than one MC1R variant was found. The current study does not support a role for the MC1R p.R160W and other variants in susceptibility for PD or RBD