Deep learning with convolutional neural networks for decoding and visualization of EEG pathology

We apply convolutional neural networks (ConvNets) to the task of distinguishing pathological from normal EEG recordings in the Temple University Hospital EEG Abnormal Corpus. We use two basic, shallow and deep ConvNet architectures recently shown to decode task-related information from EEG at least as well as established algorithms designed for this purpose. In decoding EEG pathology, both ConvNets reached substantially better accuracies (about 6% better, ~85% vs. ~79%) than the only published result for this dataset, and were still better when using only 1 minute of each recording for training and only six seconds of each recording for testing. We used automated methods to optimize architectural hyperparameters and found intriguingly different ConvNet architectures, e.g., with max pooling as the only nonlinearity. Visualizations of the ConvNet decoding behavior showed that they used spectral power changes in the delta (0-4 Hz) and theta (4-8 Hz) frequency range, possibly alongside other features, consistent with expectations derived from spectral analysis of the EEG data and from the textual medical reports. Analysis of the textual medical reports also highlighted the potential for accuracy increases by integrating contextual information, such as the age of subjects. In summary, the ConvNets and visualization techniques used in this study constitute a next step towards clinically useful automated EEG diagnosis and establish a new baseline for future work on this topic.Comment: Published at IEEE SPMB 2017 https://www.ieeespmb.org/2017

Practitioner review: pathways to care for ADHD - a systematic review of barriers and facilitators

Background. Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder starting in childhood that may persist into adulthood. It can be managed through carefully monitored medication and nonpharmacological interventions. Access to care for children at risk of ADHD varies both within and between countries. A systematic literature review was conducted to investigate the research evidence related to factors which influence children accessing services for ADHD

Can virtual nature improve patient experiences and memories of dental treatment? A study protocol for a randomized controlled trial

Background Dental anxiety and anxiety-related avoidance of dental care create significant problems for patients and the dental profession. Distraction interventions are used in daily medical practice to help patients cope with unpleasant procedures. There is evidence that exposure to natural scenery is beneficial for patients and that the use of virtual reality (VR) distraction is more effective than other distraction interventions, such as watching television. The main aim of this randomized controlled trial is to determine whether the use of VR during dental treatment can improve the overall dental experience and recollections of treatment for patients, breaking the negative cycle of memories of anxiety leading to further anxiety, and avoidance of future dental appointments. Additionally, the aim is to test whether VR benefits dental patients with all levels of dental anxiety or whether it could be especially beneficial for patients suffering from higher levels of dental anxiety. The third aim is to test whether the content of the VR distraction can make a difference for its effectiveness by comparing two types of virtual environments, a natural environment and an urban environment. Methods/design The effectiveness of VR distraction will be examined in patients 18 years or older who are scheduled to undergo dental treatment for fillings and/or extractions, with a maximum length of 30 minutes. Patients will be randomly allocated into one of three groups. The first group will be exposed to a VR of a natural environment. The second group will be exposed to a VR of an urban environment. A third group consists of patients who receive standard care (control group). Primary outcomes relate to patients’ memories of the dental treatment one week after treatment: (a) remembered pain, (b) intrusive thoughts and (c) vividness of memories. Other measures of interest are the dental experience, the treatment experience and the VR experience. Trial registration Current Controlled Trials ISRCTN4144280

Close-packed floating clusters: granular hydrodynamics beyond the freezing point?

Monodisperse granular flows often develop regions with hexagonal close packing of particles. We investigate this effect in a system of inelastic hard spheres driven from below by a "thermal" plate. Molecular dynamics simulations show, in a wide range of parameters, a close-packed cluster supported by a low-density region. Surprisingly, the steady-state density profile, including the close-packed cluster part, is well described by a variant of Navier-Stokes granular hydrodynamics (NSGH). We suggest a simple explanation for the success of NSGH beyond the freezing point.Comment: 4 pages, 5 figures. To appear in Phys. Rev. Let

A Thorough Search for Elusive Lunar Granophyres

Recent remote sensing studies [e.g., 1-3] indicate that several un-sampled regions of the Moon have significantly higher concentrations of silicic material (also high in [K], [U], and [Th]) than sampled regions. Within these areas are morphological features that are best explained by the existence of chemically evolved volcanic rocks. Observations of silicic domes [e.g., 1-5] suggest that sizable networks of silicic melt were present during crust-formation. Because of these recent findings there is a renewed interest in the petrogenesis of lunar, felsic igneous rocks. Specific questions are: (1) when were these magmas generated?, and (2) what was the source material? The two main hypotheses for generating silicic melts on Earth are fractional crystallization or partial melting of preexisting crust. On the Moon silicic melts are thought to have been generated during extreme fractional crystallization involving end-stage silicate liquid immiscibility (SLI) [e.g. 6, 7]. However, SLI cannot account for the production of significant volumes of silicic melt and its wide distribution, as reported by the remote global surveys [1, 2, 3]. In addition, experimental and natural products of SLI show that U and Th, which are abundant in the lunar granites and seen in the remote sensing data of the domes, are preferentially partitioned into the depolymerized ferrobasaltic magma and not the silicic portion [8, 9]. If SLI is not the mechanism that generated silicic magmas on the Moon then alternative processes such as fractional crystallization (only crystal-liquid separation) or partial melting should be considered as viable possibilities to be tested

Stochastic Approach to Enantiomeric Excess Amplification and Chiral Symmetry Breaking

Stochastic aspects of chemical reaction models related to the Soai reactions as well as to the homochirality in life are studied analytically and numerically by the use of the master equation and random walk model. For systems with a recycling process, a unique final probability distribution is obtained by means of detailed balance conditions. With a nonlinear autocatalysis the distribution has a double-peak structure, indicating the chiral symmetry breaking. This problem is further analyzed by examining eigenvalues and eigenfunctions of the master equation. In the case without recycling process, final probability distributions depend on the initial conditions. In the nonlinear autocatalytic case, time-evolution starting from a complete achiral state leads to a final distribution which differs from that deduced from the nonzero recycling result. This is due to the absence of the detailed balance, and a directed random walk model is shown to give the correct final profile. When the nonlinear autocatalysis is sufficiently strong and the initial state is achiral, the final probability distribution has a double-peak structure, related to the enantiomeric excess amplification. It is argued that with autocatalyses and a very small but nonzero spontaneous production, a single mother scenario could be a main mechanism to produce the homochirality.Comment: 25 pages, 6 figure

The use of decision support to measure documented adherence to a national imaging quality measure

RATIONALE AND OBJECTIVES: Present methods for measuring adherence to national imaging quality measures often require a resource-intensive chart review. Computerized decision support systems may allow for automated capture of these data. We sought to determine the feasibility of measuring adherence to a national quality measure (NQM) regarding computed tomography pulmonary angiograms (CTPAs) for pulmonary embolism using measure-targeted clinical decision support and whether the associated increased burden of data captured required by this system would affect the use and yield of CTs. MATERIALS AND METHODS: This institutional review board-approved prospective cohort study enrolled patients from September 1, 2009, through November 30, 2011, in the emergency department (ED) of a 776-bed quaternary-care adults-only academic medical center. Our intervention consisted of an NQM-targeted clinical decision support tool for CTPAs, which required mandatory input of the Wells criteria and serum D-dimer level. The primary outcome was the documented adherence to the quality measure prior and subsequent to the intervention, and the secondary outcomes were the use and yield of CTPAs. RESULTS: A total of 1209 patients with suspected PE (2.0% of 58,795 ED visits) were imaged by CTPA during the 12-month control period, and 1212 patients were imaged in the 12 months after the quarter during which the intervention was implemented (2.0% of 59,478 ED visits, P = .84). Documented baseline adherence to the NQM was 56.9% based on a structured review of the provider notes. After implementation, documented adherence increased to 75.6% (P \u3c .01). CTPA yield remained unchanged and was 10.4% during the control period and 10.1% after the intervention (P = .88). CONCLUSIONS: Implementation of a clinical decision support tool significantly improved documented adherence to an NQM, enabling automated measurement of provider adherence to evidence without the need for resource-intensive chart review. It did not adversely affect the use or yield of CTPAs