Convolutional Neural Networks for Epileptic Seizure Prediction

Epilepsy is the most common neurological disorder and an accurate forecast of seizures would help to overcome the patient's uncertainty and helplessness. In this contribution, we present and discuss a novel methodology for the classification of intracranial electroencephalography (iEEG) for seizure prediction. Contrary to previous approaches, we categorically refrain from an extraction of hand-crafted features and use a convolutional neural network (CNN) topology instead for both the determination of suitable signal characteristics and the binary classification of preictal and interictal segments. Three different models have been evaluated on public datasets with long-term recordings from four dogs and three patients. Overall, our findings demonstrate the general applicability. In this work we discuss the strengths and limitations of our methodology.Comment: accepted for MLESP 201

Verification of German methane emission inventories and their recent changes based on atmospheric observations

Continuous methane concentration records and stable isotope observations measured in the suburbs of Heidelberg, Germany, are presented. While delta13C-CH4 shows a significant trend of -0.14 permil per year, towards more depleted values, no trend is observed in the concentration data. Comparison of the Heidelberg records with clean air observations in the North Atlantic at Izana station (Tenerife) allows the determination of the continental methane excess at Heidelberg, decreasing by 20% from 190 ppb in 1992 to 150 ppb in 1997. The isotope ratio which is associated with this continental methane pile-up in the Heidelberg catchment area shows a significant trend to more depleted values from delta13C (source) = -47.4 ± 1.2 permil in 1992 to 52.9 ± 0.4 permil in 1995/96, pointing to a significant change in the methane source mix. Total methane emissions in the Heidelberg catchment area are estimated using the 222Radon (222Rn) tracer method: from the correlations of half hourly 222Rn and CH4 mixing ratios from 1995 to 1997, and the mean 222Rn exhalation rate from typical soils in the Rhine valley, a mean methane flux of 0.24 ± 0.5 g CH4 km-2 s-1 is derived. For the Heidelberg catchment area with an estimated radius of approximately 150 km, Core Inventories Air 1990 (CORINAIR90) emission estimates yield a flux of 0.47 g CH4 km-2 s-1, which is about 40% higher than the 222Rn derived number if extrapolated to 1990. The discrepancy can be explained by over-estimated emissions from waste management in the CORINAIR90 statistical assessment. The observed decrease in total emissions can be accounted for by decreasing contributions from fossil sources (mainly coal mining) and from cattle breeding. This finding is also supported by the observed decrease in mean source isotopic signatures

Matching pursuit based removal of cardiac pulse-related artifacts in EEG/fMRI

Cardiac pulse-related artifacts in the EEG recorded simultaneously with fMRI are complex and highly variable. Their effective removal is an unsolved problem. Our aim is to develop an adaptive removal algorithm based on the matching pursuit (MP) technique and to compare it to established methods using a visual evoked potential (VEP). We recorded the VEP inside the static magnetic field of an MR scanner (with artifacts) as well as in an electrically shielded room (artifact free). The MP-based artifact removal outperformed average artifact subtraction (AAS) and optimal basis set removal (OBS) in terms of restoring the EEG field map topography of the VEP. Subsequently, a dipole model was fitted to the VEP under each condition using a realistic boundary element head model. The source location of the VEP recorded inside the MR scanner was closest to that of the artifact free VEP after cleaning with the MP-based algorithm as well as with AAS. While none of the tested algorithms offered complete removal, MP showed promising results due to its ability to adapt to variations of latency, frequency and amplitude of individual artifact occurrences while still utilizing a common template

A GLOBAL QCD STUDY OF DIRECT PHOTON PRODUCTION

A global QCD analysis of the direct photon production process from both fixed target and collider experiments is presented. These data sets now completely cover the parton $x$ range from 0.01 to 0.6, thereby providing a stringent test of perturbative QCD and parton distributions. Previous detailed studies of direct photons emphasized fixed target data. We find most data sets have a steeper $p_t$ distribution than the QCD prediction. Neither global fits with new parton distributions nor improved photon fragmentation functions can resolve this problem since the deviation occurs at different $x$ values for experiments at different energies. A more likely explanation is the need for additional broadening of the $k_t$ of the initial state partons. The magnitude and the possible physical origin of this effect are investigated and discussed.Comment: 8 page Latex file using epsf.sty for figures. 6 eps figures submitted separately in uuencoded file

Feasibility studies of time-like proton electromagnetic form factors at PANDA at FAIR

Simulation results for future measurements of electromagnetic proton form factors at \PANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is estimated. The signal channel $\bar p p \to e^+ e^-$ is studied on the basis of two different but consistent procedures. The suppression of the main background channel, $\textit{i.e.}$ $\bar p p \to \pi^+ \pi^-$, is studied. Furthermore, the background versus signal efficiency, statistical and systematical uncertainties on the extracted proton form factors are evaluated using two different procedures. The results are consistent with those of a previous simulation study using an older, simplified framework. However, a slightly better precision is achieved in the PandaRoot study in a large range of momentum transfer, assuming the nominal beam conditions and detector performance

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin