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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]

Neonatal electroencephalogram (EEG), though often perceived as being difficult to record and interpret, is relatively easy to study due to the immature nature of the brain, which expresses only a few well-defined set of patterns. The EEG interpreter needs to be aware of the maturational changes as well as the effect of pathological processes and medication on brain activity. It gives valuable information for the treatment and prognostication in encephalopathic neonates. In this group, serial EEGs or EEG monitoring often gives additional information regarding deterioration/improvement of the brain function or occurrence of seizures.

Abstract Background The CMAP (Compound Muscle Action Potential) scan is a non-invasive electrodiagnostic tool, which provides a quick and visual assessment of motor unit potentials as electrophysiological components that together constitute the CMAP. The CMAP scan records the electrical activity of the muscle (CMAP) in response to transcutaneous stimulation of the motor nerve with gradual changes in stimulus intensity. Large MUs, including those that result from collateral reinnervation, appear in the CMAP scan as so-called steps, i.e., clearly visible jumps in CMAP amplitude. The CMAP scan also provides information on nerve excitability. This study aims to evaluate the influence of the stimulation protocol used on the CMAP scan and its quantification. Methods The stimulus frequency (1, 2 and 3 Hz), duration (0.05, 0.1 and 0.3 ms), or number (300, 500 and 1000 stimuli) in CMAP scans of 23 subjects was systematically varied while the other two parameters were kept constant. Pain was measured by means of a visual analogue scale (VAS). Non-parametric paired tests were used to assess significant differences in excitability and step variables and VAS scores between the different stimulus parameter settings. Results We found no effect of stimulus frequency on CMAP scan variables or VAS scores. Stimulus duration affected excitability variables significantly, with higher stimulus intensity values for shorter stimulus durations. Step variables showed a clear trend towards increasing values with decreasing stimulus number. Conclusions A protocol delivering 500 stimuli at a frequency of 2 Hz with a 0.1 ms pulse duration optimized CMAP scan quantification with a minimum of subject discomfort, artefact and duration of the recording. CMAP scan variables were influenced by stimulus duration and number; hence, these need to be standardized in future studies.

Seismic full waveform inversion (FWI) is a powerful method for estimating quantitative subsurface physical parameters from seismic data. As the FWI is a nonlinear problem, the linearized approach updates model iteratively from an initial model, which can get trapped in local minima. In the presence of a high-velocity contrast, such as at Moho, the reflection coefficient and recorded waveforms from wide-aperture seismic acquisition are extremely nonlinear around critical angles. The problem at the Moho is further complicated by the interference of lower crustal (Pg) and upper mantle (Pn) turning ray arrivals with the critically reflected Moho arrivals (PmP). In order to determine velocity structure near Moho, a nonlinear method should be used. We propose to solve this strong nonlinear FWI problem at Moho using a trans-dimensional Markov chain Monte Carlo (MCMC) method, where the earth model between lower crust and upper mantle is ideally parametrized with a 1-D assumption using a variable number of velocity interfaces. Different from common MCMC methods that require determining the number of unknown as a fixed prior before inversion, trans-dimensional MCMC allows the flexibility for an automatic estimation of both the model complexity (e.g. the number of velocity interfaces) and the velocity–depth structure from the data. We first test the algorithm on synthetic data using four representative Moho models and then apply to an ocean bottom seismometer (OBS) data from the Mid-Atlantic Ocean. A 2-D finite-difference solution of an acoustic wave equation is used for data simulation at each iteration of MCMC search, for taking into account the lateral heterogeneities in the upper crust, which is constrained from traveltime tomography and is kept unchanged during inversion; the 1-D model parametrization near Moho enables an efficient search of the trans-dimensional model space. Inversion results indicate that, with very little prior and the wide-aperture seismograms, the trans-dimensional FWI method is able to infer the posterior distribution of both the number of velocity interfaces and the velocity–depth model for a strong nonlinear problem, making the inversion a complete data-driven process. The distribution of interface matches the velocity discontinuities. We find that the Moho in the study area is a transition zone of 0.7 km, or a sharp boundary with velocities from around 7 km s−1 in the lower crust to 8 km s−1 of the upper mantle; both provide nearly identical waveform match for the field data. The ambiguity comes from the resolution limit of the band-limited seismic data and limited offset range for PmP arrivals. [ABSTRACT FROM AUTHOR]

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]

Our objective was to investigate the longitudinal development of incidence parameters of fetal body movements to define normal reference ranges, to relate them to episodes of fetal heart rate patterns A and B, and to determine the intrafetal consistency for these parameters. Twenty-nine fetuses were studied longitudinally from 24 wk of gestation. Fetal body movements and heart rate were recorded at fortnightly intervals between 24 and 36 wk of gestation and weekly from 36 wk of gestation. Data were analyzed using multilevel analysis. Reference ranges were constructed for the percentage of observation time that movements were present, the number of movement bursts per hour, the mean burst duration, and the median onset-onset interval. The median percentage incidence of fetal body movements decreased from 17% at 24 wk to about 7% near term. The developmental course was the same during active episodes. Body movements also decreased during episodes of relative quiescence, in the course of pregnancy. Intrafetal variance was on average 40-80% of the total range of the four movement parameters. Normal reference ranges were developed for incidence parameters of fetal body movements from 24 wk of gestation onward. The overall decline in the incidence of movements during pregnancy appeared to be a developmental phenomenon and not due to progressively increasing episodes of fetal quiescence. Individual fetuses showed a degree of consistency in the percentage incidence of body movements, but intra- and interfetal variances were generally high, resulting in wide ranges.