230 days of ultra long‐term subcutaneous EEG : seizure cycle analysis and comparison to patient diary

© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.We describe the longest period of subcutaneous EEG (sqEEG) monitoring to date, in a 35-year-old female with refractory epilepsy. Over 230 days, 4791/5520 h of sqEEG were recorded (86%, mean 20.8 [IQR 3.9] hours/day). Using an electronic diary, the patient reported 22 seizures, while automatically-assisted visual sqEEG review detected 32 seizures. There was substantial agreement between days of reported and recorded seizures (Cohen's kappa 0.664), although multiple clustered seizures remained undocumented. Circular statistics identified significant sqEEG seizure cycles at circadian (24-hour) and multidien (5-day) timescales. Electrographic seizure monitoring and analysis of long-term seizure cycles are possible with this neurophysiological tool.This work was supported by the Epilepsy Foundation’s Epilepsy Innovation Institute My Seizure Gauge Project. MPR is supported by the NIHR Biomedical Research Centre; the MRC Centre for Neurodevelopmental Disorders (MR/N026063/1); the EPSRC Centre for Predictive Modelling in Healthcare (EP/N014391/1); the RADAR‐CNS project (www.radar‐cns.org, grant agreement 115902).info:eu-repo/semantics/publishedVersio

A Simple Statistical Method for the Automatic Detection of Ripples in Human Intracranial EEG

High frequency oscillations (HFOs) are a promising biomarker of epileptic tissue, but detection of these electrographic events remains a challenge. Automatic detectors show encouraging results, but they typically require optimization of multiple parameters, which is a barrier to good performance and broad applicability. We therefore propose a new automatic HFO detection algorithm, focusing on simplicity and ease of implementation. It requires tuning of only an amplitude threshold, which can be determined by an iterative process or directly calculated from statistics of the rectified filtered data (i.e. mean plus standard deviation). The iterative approach uses an estimate of the amplitude probability distribution of the background activity to calculate the optimum threshold for identification of transient high amplitude events. We tested both the iterative and non-iterative approaches using a dataset of visually marked HFOs, and we compared the performance to a commonly used detector based on the root-mean-square. When the threshold was optimized for individual channels via ROC curve, all three methods were comparable. The iterative detector achieved a sensitivity of 99.6%, false positive rate (FPR) of 1.1%, and false detection rate (FDR) of 37.3%. However, in an eight-fold cross-validation test, the iterative method had better sensitivity than the other two methods (80.0% compared to 64.4 and 65.8%), with FPR and FDR of 1.3, and 49.4%, respectively. The simplicity of this algorithm, with only a single parameter, will enable consistent application of automatic detection across research centers and recording modalities, and it may therefore be a powerful tool for the assessment and localization of epileptic activity

Evolution of Global Ocean Tide Levels Since the Last Glacial Maximum

AbstractThis study addresses the evolution of global tidal dynamics since the Last Glacial Maximum focusing on the extraction of tidal levels that are vital for the interpretation of geologic sea‐level markers. For this purpose, we employ a truly‐global barotropic ocean tide model which considers the non‐local effect of Self‐Attraction and Loading. A comparison to a global tide gauge data set for modern conditions yields agreement levels of 65%–70%. As the chosen model is data‐unconstrained, and the considered dissipation mechanisms are well understood, it does not have to be re‐tuned for altered paleoceanographic conditions. In agreement with prior studies, we find that changes in bathymetry during glaciation and deglaciation do exert critical control over the modeling results with minor impact by ocean stratification and sea ice friction. Simulations of 4 major partial tides are repeated in time steps of 0.5–1 ka and augmented by 4 additional partial tides estimated via linear admittance. These are then used to derive time series from which the tidal levels are determined and provided as a global data set conforming to the HOLSEA format. The modeling results indicate a strengthened tidal resonance by M2, but also by O1, under glacial conditions, in accordance with prior studies. Especially, a number of prominent changes in local resonance conditions are identified, that impact the tidal levels up to several meters difference. Among other regions, resonant features are predicted for the North Atlantic, the South China Sea, and the Arctic Ocean.Plain Language Summary: We discuss changes in ocean tides during the last 21,000 years. This time marks the Last Glacial Maximum when large parts of the Earth's surface were covered by ice and the sea level was more than 100 m lower than today. Such a low sea level means that many regions of the Earth became land and the ocean's depth changed markedly. The distribution of land and water dominates changes in the tidal levels like the spring or neap tide. With a tidal computer model recently developed by our group, we determine these tidal levels for different times steps from 21,000 years to today. Tidal levels are important for geologists who want to understand former sea level changes with samples found at ancient shorelines. As many of such samples were deposited at a specific tidal level, our modeled information will help them to relate their height to the mean sea‐level. Of course, our model is not the only one that can estimate such changes, but we discuss the advantages of our recent development over previous tools available.Key Points: Evolution of four major partial tides from Last Glacial Maximum until present times. Validation of the employed ocean tide model with present‐day tide gauge data and dissipation rates. Diligent derivation of global tidal levels for the interpretation of sea level indexpoints. Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/50110000165

Shallow phylogeographic structuring of Vimba vimba across Europe suggests two distinct refugia during the last glaciation

Genetic variation and geographical structuring of vimba Vimba vimba were analysed across 26 sites (80 individuals) by means of mtDNA sequences (cyt b gene, mitochondrial control region) to localize hypothesized glacial refugia and to reconstruct postglacial recoloniation routes. Although genetic diversity among sequenced individuals was low, a combined analysis of the two sequenced fragments revealed a western (central and northern Europe: Danube, Elbe and lakes of Sweden) and an eastern clade (eastern Europe: Dnieper-South Bug, Don, Neman). Furthermore, a number of divergent ancestral haplotypes distributed around the Black and Caspian Seas became apparent. Mismatch analyses supported a sudden expansion model for the populations of the western clade between 50 and 10 000 bp. Overall, the study provides strong evidence for a northward and westward expansion of V. vimba from two refugial regions located in the Danubian drainage and the northern Pontic regions respectively

Evolution of Global Ocean Tide Levels Since the Last Glacial Maximum

This study addresses the evolution of global tidal dynamics since the Last Glacial Maximum focusing on the extraction of tidal levels that are vital for the interpretation of geologic sea-level markers. For this purpose, we employ a truly-global barotropic ocean tide model which considers the non-local effect of Self-Attraction and Loading. A comparison to a global tide gauge data set for modern conditions yields agreement levels of 65%–70%. As the chosen model is data-unconstrained, and the considered dissipation mechanisms are well understood, it does not have to be re-tuned for altered paleoceanographic conditions. In agreement with prior studies, we find that changes in bathymetry during glaciation and deglaciation do exert critical control over the modeling results with minor impact by ocean stratification and sea ice friction. Simulations of 4 major partial tides are repeated in time steps of 0.5–1 ka and augmented by 4 additional partial tides estimated via linear admittance. These are then used to derive time series from which the tidal levels are determined and provided as a global data set conforming to the HOLSEA format. The modeling results indicate a strengthened tidal resonance by M2, but also by O1, under glacial conditions, in accordance with prior studies. Especially, a number of prominent changes in local resonance conditions are identified, that impact the tidal levels up to several meters difference. Among other regions, resonant features are predicted for the North Atlantic, the South China Sea, and the Arctic Ocean. Key Points Evolution of four major partial tides from Last Glacial Maximum until present times Validation of the employed ocean tide model with present-day tide gauge data and dissipation rates Diligent derivation of global tidal levels for the interpretation of sea level indexpoint

Influence of Anisotropic Conductivity on EEG source Reconstruction: Investigations in a Rabbit Model

Abstract—The aim of our work was to quantify the influence of white matter anisotropic conductivity information on electroencephalography (EEG) source reconstruction. We performed this quantification in a rabbit head using both simulations and source localization based on invasive measurements. In vivo anisotropic (tensorial) conductivity information was obtained from magnetic resonance diffusion tensor imaging and included into a high-resolution finite-element model. When neglecting anisotropy in the simulations, we found a shift in source location of up to 1.3 mm with a mean value of 0.3 mm. The averaged orientational deviation was 10 degree and the mean magnitude error of the dipole was 29%. Source localization of the first cortical components after median and tibial nerve stimulation resulted in anatomically verified dipole positions with no significant anisotropy effect. Our results indicate that the expected average source localization erro

Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning

Abstract The ability to forecast seizures minutes to hours in advance of an event has been verified using invasive EEG devices, but has not been previously demonstrated using noninvasive wearable devices over long durations in an ambulatory setting. In this study we developed a seizure forecasting system with a long short-term memory (LSTM) recurrent neural network (RNN) algorithm, using a noninvasive wrist-worn research-grade physiological sensor device, and tested the system in patients with epilepsy in the field, with concurrent invasive EEG confirmation of seizures via an implanted recording device. The system achieved forecasting performance significantly better than a random predictor for 5 of 6 patients studied, with mean AUC-ROC of 0.80 (range 0.72–0.92). These results provide the first clear evidence that direct seizure forecasts are possible using wearable devices in the ambulatory setting for many patients with epilepsy