Network-Targeted Approach and Postoperative Resting-State Functional Magnetic Resonance Imaging Are Associated with Seizure Outcome

Objective Postoperative resting‐state functional magnetic resonance imaging (MRI) in children with intractable epilepsy has not been quantified in relation to seizure outcome. Therefore, its value as a biomarker for epileptogenic pathology is not well understood. Methods In a sample of children with intractable epilepsy who underwent prospective resting‐state seizure onset zone (SOZ)‐targeted epilepsy surgery, postoperative resting‐state functional MRI (rs‐fMRI) was performed 6 to 12 months later. Graded normalization of the postoperative resting‐state SOZ was compared to seizure outcomes, patient, surgery, and anatomical MRI characteristics. Results A total of 64 cases were evaluated. Network‐targeted surgery, followed by postoperative rs‐fMRI normalization was significantly (p < 0.001) correlated with seizure reduction, with a Spearman rank correlation coefficient of 0.83. Of 39 cases with postoperative rs‐fMRI SOZ normalization, 38 (97%) became completely seizure free. In contrast, of the 25 cases without complete rs‐fMRI SOZ normalization, only 3 (5%) became seizure free. The accuracy of rs‐fMRI as a biomarker predicting seizure freedom is 94%, with 96% sensitivity and 93% specificity. Interpretation Among seizure localization techniques in pediatric epilepsy, network‐targeted surgery, followed by postoperative rs‐fMRI normalization, has high correlation with seizure freedom. This study shows that rs‐fMRI SOZ can be used as a biomarker of the epileptogenic zone, and postoperative rs‐fMRI normalization is a biomarker for SOZ quiescence

A simplified, lossless re-analysis of PAPER-64

We present limits on the 21cm power spectrum from the Epoch of Reionization (EoR) using data from the 64 antenna configuration of the Donald C. Backer Precision Array for Probing the Epoch of Reionization (PAPER) analyzed through a power spectrum pipeline independent from previous PAPER analyses. Previously reported results from PAPER have been found to contain significant signal loss (Cheng et al. 2018, arxiv:1810.05175). Several lossy steps from previous PAPER pipelines have not been included in this analysis, namely: delay-based foreground filtering, optimal fringe-rate filtering, and empirical covariance-based estimators. Steps which remain in common with previous analyses include redundant calibration and local sidereal time (LST) binning. The power spectra reported here are effectively the result of applying a linear Fourier transform analysis to the calibrated, LST binned data. This analysis also uses more data than previous publications, including the complete available redshift range of $z \sim 7.5$ to $11$. In previous PAPER analyses, many power spectrum measurements were found to be detections of noncosmological power at levels of significance ranging from two to hundreds of times the theoretical noise. Here, excess power is examined using redundancy between baselines and power spectrum jackknives. The upper limits we find on the 21cm power spectrum from reionization are ($1500$ mK)$^{2}$, ($1900$ mK)$^{2}$, ($280$ mK)$^{2}$, ($200$ mK)$^{2}$, ($380$ mK)$^{2}$, ($300$ mK)$^{2}$ at redshifts $z=10.87,\ 9.93,\ 8.68,\ 8.37,\ 8.13,$ and $7.48$, respectively. For reasons described in Cheng et al. 2018 (arxiv:1810.05175), these limits supersede all previous PAPER results (Ali et al. 2018, arxiv:1502.06016).Comment: 28 Pages, 17 Pages, Accepted to AP

Improved 21 cm Epoch of Reionization Power Spectrum Measurements with a Hybrid Foreground Subtraction and Avoidance Technique

Observations of the 21 cm Epoch of Reionization signal are dominated by Galactic and extragalactic foregrounds. The need for foreground removal has led to the development of two main techniques, often referred to as “foreground avoidance” and “foreground subtraction.” Avoidance is associated with filtering foregrounds in Fourier space, while subtraction uses an explicit foreground model that is removed. Using 1088 hr of data from the 64-element PAPER array, we demonstrate that subtraction of a foreground model prior to delay-space foreground filtering results in a modest but measurable improvement of the performance of the filter. This proof-of-concept result shows that improvement stems from the reduced dynamic range requirements needed for the foreground filter: subtraction of a foreground model reduces the total foreground power, so for a fixed dynamic range, the filter can push toward fainter limits. We also find that the choice of window function used in the foreground filter can have an appreciable affect on the performance near the edges of the observing band. We demonstrate these effects using a smaller 3 hr sampling of data from the MWA, and find that the hybrid filtering and subtraction removal approach provides similar improvements across the band as seen in the case with PAPER-64

Optimizing Sparse RFI Prediction using Deep Learning

Radio Frequency Interference (RFI) is an ever-present limiting factor among radio telescopes even in the most remote observing locations. When looking to retain the maximum amount of sensitivity and reduce contamination for Epoch of Reionization studies, the identification and removal of RFI is especially important. In addition to improved RFI identification, we must also take into account computational efficiency of the RFI-Identification algorithm as radio interferometer arrays such as the Hydrogen Epoch of Reionization Array grow larger in number of receivers. To address this, we present a Deep Fully Convolutional Neural Network (DFCN) that is comprehensive in its use of interferometric data, where both amplitude and phase information are used jointly for identifying RFI. We train the network using simulated HERA visibilities containing mock RFI, yielding a known "ground truth" dataset for evaluating the accuracy of various RFI algorithms. Evaluation of the DFCN model is performed on observations from the 67 dish build-out, HERA-67, and achieves a data throughput of 1.6$\times 10^{5}$ HERA time-ordered 1024 channeled visibilities per hour per GPU. We determine that relative to an amplitude only network including visibility phase adds important adjacent time-frequency context which increases discrimination between RFI and Non-RFI. The inclusion of phase when predicting achieves a Recall of 0.81, Precision of 0.58, and $F_{2}$ score of 0.75 as applied to our HERA-67 observations.Comment: 11 pages, 7 figure

Detection of Cosmic Structures using the Bispectrum Phase. II. First Results from Application to Cosmic Reionization Using the Hydrogen Epoch of Reionization Array

Characterizing the epoch of reionization (EoR) at $z\gtrsim 6$ via the redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the brightness temperature of the intergalactic medium (IGM). From this limited data, at $z=7.7$ we infer "$1\sigma$" upper limits on the IGM brightness temperature to be $\le 316$ "pseudo" mK at $\kappa_\parallel=0.33$ "pseudo" $h$ Mpc$^{-1}$ (data-limited) and $\le 1000$ "pseudo" mK at $\kappa_\parallel=0.875$ "pseudo" $h$ Mpc$^{-1}$ (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at $\gtrsim 10^6$ dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues.Comment: 22 pages, 12 figures (including sub-figures). Published in PhRvD. Abstract may be slightly abridged compared to the actual manuscript due to length limitations on arXi

Mitigating Internal Instrument Coupling for 21 cm Cosmology. II. A Method Demonstration with the Hydrogen Epoch of Reionization Array

We present a study of internal reflection and cross-coupling systematics in Phase I of the Hydrogen Epoch of Reionization Array (HERA). In a companion paper, we outlined the mathematical formalism for such systematics and presented algorithms for modeling and removing them from the data. In this work, we apply these techniques to data from HERA's first observing season as a method demonstration. The data show evidence for systematics that, without removal, would hinder a detection of the 21 cm power spectrum for the targeted Epoch of Reionization (EoR) line-of-sight modes in the range 0.2 h −1 Mpc−1 < ${k}_{\parallel }$ < 0.5 h −1 Mpc−1. In particular, we find evidence for nonnegligible amounts of spectral structure in the raw autocorrelations that overlaps with the EoR window and is suggestive of complex instrumental effects. Through systematic modeling on a single night of data, we find we can recover these modes in the power spectrum down to the integrated noise floor, achieving a dynamic range in the EoR window of 106 in power (mK2 units) with respect to the bright galactic foreground signal. Future work with deeper integrations will help determine whether these systematics can continue to be mitigated down to EoR levels. For future observing seasons, HERA will have upgraded analog and digital hardware to better control these systematics in the field