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Objective Following a sudden death at a residential care unit, the Dutch Health and Care Inspectorate advised intensification of the use of video monitoring ( VM) at the unit. We assessed whether VM resulted in increased identification of seizures that required clinical intervention. Methods The unit provides care for 340 individuals with refractory epilepsy and severe learning disabilities. Acoustic detection systems ( ADSs) cover all individuals; 37 people also have a bed motion sensor ( BMS) and 46 people with possible nocturnal seizures are now monitored by VM. During a 6-month period, in all cases of a suspected seizure we asked the caregivers to specify which device alerted them and to indicate whether this led to an intervention. Staff costs of VM were estimated using payroll information. Results We identified 1,208 seizures in 37 individuals: 4 had no nocturnal seizures and 393 (33%) seizures were seen only on video. In 169 (14%) of 1,208 seizures an intervention was made and this included 39 (10%) of 393 seizures seen only on video. When compared to seizures observed with an ADS or BMS, seizures seen only on video were more often tonic seizures (71% vs. 22%, p < 0.001) and occurred mostly in the beginning or at the end of the night (40% vs. 26%, p < 0.001). The extra staff costs of monitoring was 7,035 euro per seizure seen only on video and leading to an intervention. Significance VM facilitates nocturnal surveillance, but the costs are high. This underscores the need for development of reliable seizure detection devices. [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation (TMS) with electroencephalography (EEG), that is TMS‐EEG, may assist in managing epilepsy. We systematically reviewed the quality of reporting and findings in TMS‐EEG studies on people with epilepsy and healthy controls, and on healthy individuals taking anti‐seizure medication. We searched the Cochrane Library, Embase, PubMed and Web of Science databases for original TMS‐EEG studies comparing people with epilepsy and healthy controls, and healthy subjects before and after taking anti‐seizure medication. Studies should involve quantitative analyses of TMS‐evoked EEG responses. We evaluated the reporting of study population characteristics and TMS‐EEG protocols (TMS sessions and equipment, TMS trials and EEG protocol), assessed the variation between protocols, and recorded the main TMS‐EEG findings. We identified 20 articles reporting 14 unique study populations and TMS methodologies. The median reporting rate for the group of people with epilepsy parameters was 3.5/7 studies and for the TMS parameters was 13/14 studies. TMS protocols varied between studies. Fifteen out of 28 anti‐seizure medication trials in total were evaluated with time‐domain analyses of single‐pulse TMS‐EEG data. Anti‐seizure medication significantly increased N45, and decreased N100 and P180 component amplitudes but in marginal numbers (N45: 8/15, N100: 7/15, P180: 6/15). Eight articles compared people with epilepsy and controls using different analyses, thus limiting comparability. The reporting quality and methodological uniformity between studies evaluating TMS‐EEG as an epilepsy biomarker is poor. The inconsistent findings question the validity of TMS‐EEG as an epilepsy biomarker. To demonstrate TMS‐EEG clinical applicability, methodology and reporting standards are required. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) and progressive muscular atrophy (PMA) are characterized by a loss of motor units (MUs), reinnervation and, eventually, muscle fibre loss. These three aspects are all reflected in the compound muscle action potential scan (CMAP scan, a high-detail stimulus response curve), which visualizes large MU potentials as 'steps'. We explored changes in the CMAP scan over time, combined the information on steps and CMAP amplitude into a CMAP scan-based progression score (CSPS), and correlated this score with motor unit number estimates (MUNE). Ten patients (three PMA, seven ALS; age 37−77 years) were included. CMAP scan and MUNE measurements were performed five times during a three-month period. Nine patients had additional measurements. The follow-up period was 3−24 months. Results demonstrated that abnormalities in steps preceded a decline in maximum CMAP amplitude during follow-up. Usually, both steps and maximum CMAP amplitude changed between recordings. The correlation between the CSPS and MUNE was −0.80 ( p < 0.01). In conclusion, the CMAP scan can be used to visualize and quantify disease progression in a muscle affected by MND. The CSPS is a measure of MU loss that is quick and easy to obtain and that, in contrast to MUNE, has no sample bias. [ABSTRACT FROM AUTHOR]

When building 3D models of the subsurface, reconciling several geological and geophysical data of diverse nature, resolutions, coverage, or sensitivity, is challenging, both numerically and petrophysically. In this work, we propose a workflow for mapping selected geological features and characterise their uncertainty using a Bayesian Estimate Fusion algorithm. Different datasets such as 1D probabilistic models derived from geophysical data, drillholes and geological data are combined to produce probabilistic maps of selected geological boundaries, relying on petrophysical and geological assumptions. Leveraging large, high-quality geophysical datasets acquired in the eastern Gawler Craton in South Australia, we demonstrate the applicability of our approach with two examples: (1) we map in 3D the top of a stratigraphic unit in the cover, the Tregolana Shale, using 1D magnetotelluric (MT) and 1D Airborne Electromagnetic (AEM) probabilistic models, drill holes and surface geology; (2) we map the depth to basement using 1D probabilistic MT models, drill holes and interpreted structural information. Our results show that the different resolution, data sampling, depth of investigation and reliability of the utilised datasets can be combined in a complementary fashion, overcoming their respective limitations, to find solutions/models that satisfy all the datasets. We show that probabilistic workflows permit characterisation and reduce uncertainty when mapping the location of features of interest, but also permit the testing of geological hypotheses against other geophysical and geological data. These types of models are valuable to better characterise, interpret, and conceptualise the subsurface, enabling better exploration targeting and supporting efforts to discover new mineral deposits. [ABSTRACT FROM AUTHOR]

• An automated non-contact algorithm for detection of central apneas is proposed. • It detects cessation of oscillatory movements of breathing in absence of body motion. • All apnea episodes were detected in the signals from at least one camera angle. • Integrating camera inputs capturing different angles improved detection sensitivity. • >99% specificity was achieved with individual cameras and integrated camera inputs. Central apneas occurring in the aftermath of epileptic seizures may lead to sudden death. Contact-sensors currently used to detect apneas are not always suitable or tolerated. We developed a robust automated non-contact algorithm for real-time detection of central apneas using video cameras. One video recording with simulated apneas and nine with real-life apneas associated with epileptic seizures, each recorded from 3 to 4 angles, were used to develop the algorithm. Videos were preprocessed using optical flow, from which translation, dilatation and shear rates were extracted. Presence of breathing motions was quantified in the time-frequency spectrum by calculating the relative power in the respiratory range (0.1–1 Hz). Sigmoid modulation was calculated over different scales to quantify sigmoid-like drops in respiratory range power. Each sigmoid modulation maximum constitutes a possible apnea event. Two event features were calculated to enable distinction between apnea events and movements: modulation maximum amplitude and total spectral power modulation at the time of the event. An ensemble support vector machine was trained to classify events using a bagging procedure and validated in a leave-one-subject-out cross validation procedure. All apnea episodes were detected in the signals from at least one camera angle. Integrating camera inputs capturing different angles increased overall detection sensitivity (>90%). Overall detection specificity of >99% was achieved with both individual cameras and integrated camera inputs. These results suggest that it is feasible to detect central apneas automatically in video, using this algorithm. When validated, the algorithm might be used as an online remote apnea detector for safety monitoring. [ABSTRACT FROM AUTHOR]

In this paper, we use a new workflow to substantiate the characterization of a prominent, deep sediment conductor in the hyperextended Bjørnøya Basin (SW Barents Sea) previously identified in smooth resistivity models from 3-D deterministic inversion of magnetotelluric data. In low-dimensionality environments like layered sedimentary basin, 1-D Bayesian inversion can be advantageous for a thorough exploration of the solution space, but the violation of the 1-D assumption has to be efficiently handled. The primary geological objectives of this work is therefore preceded by a secondary task: the application of a new machine learning approach for handling the 1-D violation assumption for 21 MT field stations in the Barents Sea. We find that a decision tree can adequately learn the relationship between MT dimensionality parameters and the 1-D–3-D residual response for a training set of synthetic models, mimicking typical resistivity structures of the SW Barents Sea. The machine learning model is then used to predict the dimensionality compensation error for MT signal periods ranging of 1–3000 s for 21 receivers located over the Bjørnøya Basin and Veslemøy High. After running 1-D Bayesian inversion, we generated a posterior resistivity distribution for an ensemble of 6000 1-D models fitting the compensated MT data for each 21 field stations. The proportion of 1-D models showing ρ < 1 Ω·m is consistently beyond 80 per cent and systemically reaches a maximum of 100 per cent in the Early Aptian–Albian interval in the Bjørnøya Basin. In hyperextended basins of the SW Barents Sea, the dimensionality compensation workflow has permitted to refine the characterization of the deep basin conductor by leveraging the increased vertical resolution and optimal used of MT data. In comparison, the smooth 3-D deterministic models only poorly constrained depth and lateral extent of the basin anomaly. The highest probability of finding ρ < 1 Ω·m is robustly assigned to the syn-tectonic Early Aptian–Albian marine shales, now buried at 6–8 km depth. Based on a theoretical two phase fluid-rock model, we show that the pore fluid of these marine shales must have a higher salinity than seawater to explain the anomaly ρ < 1 Ω·m. Therefore, the primary pore fluid underwent mixing with a secondary brine during rifting. Using analogue rift systems in palaeomargins, we argue that two possible secondary brine reservoir may contribute to deep saline fluid circulation in the hyperextended basin: (1) Permian salt-derived fluid and, (2) mantle-reacted fluid from serpentinization. [ABSTRACT FROM AUTHOR]

• Absence seizures affect visual attention and eye movements variably. • Deficits in visual attention during absences are associated with differences in EEG features and network activation. • Our findings can be employed in clinical practice for tailored risk assessment in patients. Absences affect visual attention and eye movements variably. Here, we explore whether the dissimilarity of these symptoms during absences is reflected in differences in electroencephalographic (EEG) features, functional connectivity, and activation of the frontal eye field. Pediatric patients with absences performed a computerized choice reaction time task, with simultaneous recording of EEG and eye-tracking. We quantified visual attention and eye movements with reaction times, response correctness, and EEG features. Finally, we studied brain networks involved in the generation and propagation of seizures. Ten pediatric patients had absences during the measurement. Five patients had preserved eye movements (preserved group) and five patients showed disrupted eye movements (unpreserved group) during seizures. Source reconstruction showed a stronger involvement of the right frontal eye field during absences in the unpreserved group than in the preserved group (dipole fraction 1.02% and 0.34%, respectively, p < 0.05). Graph analysis revealed different connection fractions of specific channels. The impairment of visual attention varies among patients with absences and is associated with differences in EEG features, network activation, and involvement of the right frontal eye field. Assessing the visual attention of patients with absences can be usefully employed in clinical practice for tailored advice to the individual patient. [ABSTRACT FROM AUTHOR]

Background Long-term video-EEG monitoring (LTM) aims to record the habitual event and is a useful diagnostic tool for neurological paroxysmal clinical events. In our epilepsy monitoring unit (EMU) setting, admissions are usually planned to last up to five days. We ascertained time taken for the recording of a first event and determined correlations between different clinical characteristics and timings. Methods We retrospectively reviewed diagnostic and classification LTM recording performed at a tertiary epilepsy centre. Results Sixty-three recordings were reviewed. Most subjects (89%) had events at least once a week prior to admission. In 40 (63%) a habitual event was recorded, mostly (93%) within the first two days. No events were recorded on day four or five. A few characteristics were associated with a trend for events occurring earlier (events more than once a week vs less than once a week, motor symptoms compared with aura or dyscognitive events, and reduction of antiepileptic drugs versus no reduction). Conclusions Our finding suggests that, for diagnostic event recording in people with epilepsy or PNEA, a maximum recording time of three days is sufficient in two thirds of them, if event frequency is at least once a week. In the remaining third, prolonged recording up to five days did not result in capturing a clinical event. For these individuals, shorter admission could be planned, for example for 2 days rather than 5 days. [ABSTRACT FROM AUTHOR]

We propose, test and apply a methodology integrating 1D magnetotelluric (MT) and magnetic data inversion, with a focus on the characterisation of the cover–basement interface. It consists of a cooperative inversion workflow relying on standalone inversion codes. Probabilistic information about the presence of rock units is derived from MT and passed on to magnetic inversion through constraints combining structural constraints with petrophysical prior information. First, we perform the 1D probabilistic inversion of MT data for all sites and recover the respective probabilities of observing the cover–basement interface, which we interpolate to the rest of the study area. We then calculate the probabilities of observing the different rock units and partition the model into domains defined by combinations of rock units with non-zero probabilities. Third, we combine these domains with petrophysical information to apply spatially varying, disjoint interval bound constraints (DIBC) to least-squares magnetic data inversion using the alternating direction method of multipliers (or ADMM). We demonstrate the proof-of-concept using a realistic synthetic model reproducing features from the Mansfield area (Victoria, Australia) using a series of uncertainty indicators. We then apply the workflow to field data from the prospective mining region of Cloncurry (Queensland, Australia). Results indicate that our integration methodology efficiently leverages the complementarity between separate MT and magnetic data modelling approaches and can improve our capability to image the cover–basement interface. In the field application case, our findings also suggest that the proposed workflow may be useful to refine existing geological interpretations and to infer lateral variations within the basement. [ABSTRACT FROM AUTHOR]