Single-trial analysis of EEG during rapid visual discrimination: enabling cortically-coupled computer vision

We describe our work using linear discrimination of multi-channel electroencephalography for single-trial detection of neural signatures of visual recognition events. We demonstrate the approach as a methodology for relating neural variability to response variability, describing studies for response accuracy and response latency during visual target detection. We then show how the approach can be utilized to construct a novel type of brain-computer interface, which we term cortically-coupled computer vision. In this application, a large database of images is triaged using the detected neural signatures. We show how ‘corticaltriaging’ improves image search over a strictly behavioral response

Evidence for Type Ia Supernova Diversity from Ultraviolet Observations with the Hubble Space Telescope

We present ultraviolet (UV) spectroscopy and photometry of four Type Ia supernovae (SNe 2004dt, 2004ef, 2005M, and 2005cf) obtained with the UV prism of the Advanced Camera for Surveys on the Hubble Space Telescope. This dataset provides unique spectral time series down to 2000 Angstrom. Significant diversity is seen in the near maximum-light spectra (~ 2000--3500 Angstrom) for this small sample. The corresponding photometric data, together with archival data from Swift Ultraviolet/Optical Telescope observations, provide further evidence of increased dispersion in the UV emission with respect to the optical. The peak luminosities measured in uvw1/F250W are found to correlate with the B-band light-curve shape parameter dm15(B), but with much larger scatter relative to the correlation in the broad-band B band (e.g., ~0.4 mag versus ~0.2 mag for those with 0.8 < dm15 < 1.7 mag). SN 2004dt is found as an outlier of this correlation (at > 3 sigma), being brighter than normal SNe Ia such as SN 2005cf by ~0.9 mag and ~2.0 mag in the uvw1/F250W and uvm2/F220W filters, respectively. We show that different progenitor metallicity or line-expansion velocities alone cannot explain such a large discrepancy. Viewing-angle effects, such as due to an asymmetric explosion, may have a significant influence on the flux emitted in the UV region. Detailed modeling is needed to disentangle and quantify the above effects.Comment: 17 pages, 13 figures, accepted by Ap

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Proceedings of the 13th annual conference of INEBRIA

CITATION: Watson, R., et al. 2016. Proceedings of the 13th annual conference of INEBRIA. Addiction Science & Clinical Practice, 11:13, doi:10.1186/s13722-016-0062-9.The original publication is available at https://ascpjournal.biomedcentral.comENGLISH SUMMARY : Meeting abstracts.https://ascpjournal.biomedcentral.com/articles/10.1186/s13722-016-0062-9Publisher's versio

Recipes for the linear analysis of EEG

In this paper, we describe a simple set of &quot;recipes&quot; for the analysis of high spatial density EEG. We focus on a linear integration of multiple channels for extracting individual components without making any spatial or anatomical modeling assumptions, instead requiring particular statistical properties such as maximum difference, maximum power, or statistical independence. We demonstrate how corresponding algorithms, for example, linear discriminant analysis, principal component analysis and independent component analysis, can be used to remove eye-motion artifacts, extract strong evoked responses, and decompose temporally overlapping components. The general approach is shown to be consistent with the underlying physics of EEG, which specifies a linear mixing model of the underlying neural and nonneural current source

Single-trial analysis of EEG during rapid visual discrimination: enabling cortically-coupled computer vision

We describe our work using linear discrimination of multi-channel electroencephalography for single-trial detection of neural signatures of visual recognition events. We demonstrate the approach as a methodology for relating neural variability to response variability, describing studies for response accuracy and response latency during visual target detection. We then show how the approach can be utilized to construct a novel type of brain-computer interface, which we term cortically-coupled computer vision. In this application, a large database of images is triaged using the detected neural signatures. We show how ‘corticaltriaging’ improves image search over a strictly behavioral response

A System for Single-trial Analysis of Simultaneously Acquired EEG and fMRI

Abstract — In this paper we describe a system for simulta-neously acquiring EEG and fMRI and evaluate it in terms of discriminating, single-trial, task-related neural components in the EEG. Using an auditory oddball stimulus paradigm, we acquire EEG data both inside and outside a 1.5T MR scanner and compare both power spectra and single-trial discrimination performance for both conditions. We find that EEG activity acquired inside the MR scanner during echo planer image acquisition is of high enough quality to enable single-trial discrimination performance that is 95 % of that acquired outside the scanner. We conclude that EEG acquired simultaneously with fMRI is of high enough fidelity to permit single-trial analysis. I

Single-trial analysis of EEG during rapid visual discrimination: Enabling cortically-coupled

We describe our work using linear discrimination of multi-channel electroencephalography for single-trial detection of neural signatures of visual recognition events. We demonstrate the approach as a methodology for relating neural variability to response variability, describing studies for response accuracy and response latency during visual target detection. We then show how the approach can be utilized to construct a novel type of brain-computer interface, which we term cortically-coupled computer vision. In this application, a large database of images is triaged using the detected neural signatures. We show how `corticaltriaging &apos; improves image search over a strictly behavioral response