Revealing hidden states in visual working memory using electroencephalography

It is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively "activity-silent" neural state. Silent vWM is consistent with recent cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity? We propose a novel approach that is analogous to echolocation: using a high-contrast visual stimulus, it may be possible to drive brain activity during vWM maintenance and measure the vWM-dependent impulse response. We recorded electroencephalography (EEG) while participants performed a vWM task in which a randomly oriented grating was remembered. Crucially, a high-contrast, task-irrelevant stimulus was shown in the maintenance period in half of the trials. The electrophysiological response from posterior channels was used to decode the orientations of the gratings. While orientations could be decoded during and shortly after stimulus presentation, decoding accuracy dropped back close to baseline in the delay. However, the visual evoked response from the task-irrelevant stimulus resulted in a clear re-emergence in decodability. This result provides important proof-of-concept for a promising and relatively simple approach to decode "activity-silent" vWM content using non-invasive EEG

Obesity and Cancer Screening according to Race and Gender

The relationship between obesity and cancer screening varies by screening test, race, and gender. Most studies on cervical cancer screening found a negative association between increasing weight and screening, and this negative association was most consistent in white women. Recent literature on mammography reports no association with weight. However, some studies show a negative association in white, but not black, women. In contrast, obese/overweight men reported higher rates of prostate-specific antigen (PSA) testing. Comparison of prostate cancer screening, mammography, and Pap smears implies a gender difference in the relationship between screening behavior and weight. In colorectal cancer (CRC) screening, the relationship between weight and screening in men is inconsistent, while there is a trend towards lower CRC screening in higher weight women

Robust Machine Learning Applied to Astronomical Datasets I: Star-Galaxy Classification of the SDSS DR3 Using Decision Trees

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that these star/galaxy classifications are expected to be reliable for approximately 22 million objects with r < ~20. The general machine learning environment Data-to-Knowledge and supercomputing resources enabled extensive investigation of the decision tree parameter space. This work presents the first public release of objects classified in this way for an entire SDSS data release. The objects are classified as either galaxy, star or nsng (neither star nor galaxy), with an associated probability for each class. To demonstrate how to effectively make use of these classifications, we perform several important tests. First, we detail selection criteria within the probability space defined by the three classes to extract samples of stars and galaxies to a given completeness and efficiency. Second, we investigate the efficacy of the classifications and the effect of extrapolating from the spectroscopic regime by performing blind tests on objects in the SDSS, 2dF Galaxy Redshift and 2dF QSO Redshift (2QZ) surveys. Given the photometric limits of our spectroscopic training data, we effectively begin to extrapolate past our star-galaxy training set at r ~ 18. By comparing the number counts of our training sample with the classified sources, however, we find that our efficiencies appear to remain robust to r ~ 20. As a result, we expect our classifications to be accurate for 900,000 galaxies and 6.7 million stars, and remain robust via extrapolation for a total of 8.0 million galaxies and 13.9 million stars. [Abridged]Comment: 27 pages, 12 figures, to be published in ApJ, uses emulateapj.cl

Attentional selectivity, automaticity, and self-efficacy predict simulator-acquired skill transfer to the clinical environment

Introduction Several studies demonstrated that simulator-acquired skill transfer to the operating room is incomplete. Our objective was to identify trainee characteristics that predict the transfer of simulator-acquired skill to the operating room. Methods Trainees completed baseline assessments including intracorporeal suturing (IS) performance, attentional selectivity, self-reported use of mental skills, and self-reported prior clinical and simulated laparoscopic experience and confidence. Residents then followed proficiency-based laparoscopic skills training, and their skill transfer was assessed on a live-anesthetized porcine model. Predictive characteristics for transfer test performance were assessed using multiple linear regression. Results Thirty-eight residents completed the study. Automaticity, attentional selectivity, resident perceived ability with laparoscopy and simulators, and post-training IS performance were predictive of IS performance during the transfer test. Conclusions Promoting automaticity, self-efficacy, and attention selectivity may help improve the transfer of simulator-acquired skill. Mental skills training and training to automaticity may therefore be valuable interventions to achieve this goal

Mental Skills Training Limits the Decay in Operative Technical Skill under Stressful Conditions: Results of a Multisite, Randomized Controlled Study

Background Overwhelming stress in the operating room can lead to decay in operative performance, particularly for residents who lack experience. Mental skills training can minimize deterioration in performance during challenging situations. We hypothesized that residents trained on mental skills would outperform controls under increased stress conditions in the simulated operating room. Methods Residents from Indiana University enrolled voluntarily in this institutional review board–approved study. Residents were stratified according to baseline characteristics and randomized into a mental skills and control group. Both groups trained to proficiency in laparoscopic suturing, but only the mental skills group received mental skills training. After training, technical skill transfer was assessed under regular and stressful conditions on a porcine model. Performance was assessed using an objective suturing score. The Test of Performance Strategies was used to assess the use of mental skills. Data were combined and compared with data that had been collected at Carolinas Healthcare System because residents underwent the same protocol. Results A total of 38 residents completed all study elements. There were no differences in the effects observed between sites. We observed no group differences at baseline. The groups achieved similar technical performance at baseline, posttest, and transfer test under low-stress conditions, but the mental skills group outperformed the control group during the transfer test under high-stress conditions. Conclusion Our comprehensive mental skills curriculum implemented with surgery residents at two institutions was effective at minimizing the deterioration of resident technical performance under stressful conditions compared with controls. These results provide further evidence for the effectiveness of mental skills training to optimize surgery trainees’ technical performance during challenging clinical situations

Near Infrared Spectra and Intrinsic Luminosities of Candidate Type II Quasars at 2 < z < 3.4

We present JHK near-infrared (NIR) spectroscopy of 25 candidate Type II quasars selected from the Sloan Digital Sky Survey, using Triplespec on the Apache Point Observatory 3.5m telescope, FIRE at the Magellan/Baade 6.5m telescope, and GNIRS on Gemini. At redshifts of 2 < z < 3.4, our NIR spectra probe the rest-frame optical region of these targets, which were initially selected to have strong lines of CIV and Ly alpha, with FWHM<2000 km/s from the SDSS pipeline. We use the [OIII]5007 line shape as a model for the narrow line region emission, and find that \halpha\ consistently requires a broad component with FWHMs ranging from 1000 to 7500 km/s. Interestingly, the CIV lines also require broad bases, but with considerably narrower widths of 1000 to 4500 km/s. Estimating the extinction using the Balmer decrement and also the relationship in lower-z quasars between rest equivalent width and luminosity in the [OIII] line, we find typical A_V values of 0-2 mag, which naturally explain the attenuated CIV lines relative to Halpha. We propose that our targets are moderately obscured quasars. We also describe one unusual object with three distinct velocity peaks in its [OIII] spectrum.Comment: Accepted for publication in ApJ, 18 pages, 14 figure

Butterfly Community Dynamics in a Restored Prairie Used for Biofuel Production

The conversion of native Midwestern tallgrass prairie to monoculture production of corn (Zea mays) and soybeans (Glycene max) for food and fuel has resulted in a significant decrease in habitat for insect pollinators, including butterflies. Compared to conventional biofuels such as corn ethanol, prairie biomass produces greater energy yields while providing high quality wildlife habitat and protecting soil and water resources. My research took place at Cedar River Natural Resource Area in Black Hawk County Iowa, USA. In spring 2009, the University of Northern Iowa’s Tallgrass Prairie Center seeded 48 research plots in conventional fields to one of four experimental treatments of native vegetation: 1) switchgrass monoculture, 2) warm-season grass mix (5 species), 3) biomass mix (8 forb and 8 grass species), or 4) prairie mix (20 forb, 3 sedge, and 9 grass species). During the summers of 2010, 2011, and 2012, our team conducted visual surveys of butterflies (class Lepidoptera), a group widely recognized as bioindicators of ecosystem health. I used these data to compare butterfly abundance, species richness, and composition among treatments over the three year study. I hypothesized that butterfly abundance and richness would increase over the three year period and that more diverse plantings would support a greater abundance and diversity of butterflies. Our results indicate that butterfly abundance and richness fluctuated depending on site management. This year, butterfly abundance started out high and remained high in biomass and prairie plots but decreased in grass plots, whereas richness started out high and decreased over the three survey periods. The conversion of marginal agricultural lands to areas of natural vegetation cultivated for biofuel production would be beneficial to increase abundance of butterflies through creation of habitat and providing host plant and nectar resources