Diminished neural adaptation during implicit learning in autism

Neuroimaging studies have shown evidence of disrupted neural adaptation during learning in individuals with autism spectrum disorder (ASD) in several types of tasks, potentially stemming from frontal-posterior cortical underconnectivity (Schipul et al., 2012). The aim of the current study was to examine neural adaptations in an implicit learning task that entails participation of frontal and posterior regions. Sixteen high-functioning adults with ASD and sixteen neurotypical control participants were trained on and performed an implicit dot pattern prototype learning task in a functional magnetic resonance imaging (fMRI) session. During the preliminary exposure to the type of implicit prototype learning task later to be used in the scanner, the ASD participants took longer than the neurotypical group to learn the task, demonstrating altered implicit learning in ASD. After equating task structure learning, the two groups’ brain activation differed during their learning of a new prototype in the subsequent scanning session. The main findings indicated that neural adaptations in a distributed task network were reduced in the ASD group, relative to the neurotypical group, and were related to ASD symptom severity. Functional connectivity was reduced and did not change as much during learning for the ASD group, and was related to ASD symptom severity. These findings suggest that individuals with ASD show altered neural adaptations during learning, as seen in both activation and functional connectivity measures. This finding suggests why many real-world implicit learning situations may pose special challenges for ASD

Tea: A High-level Language and Runtime System for Automating Statistical Analysis

Though statistical analyses are centered on research questions and hypotheses, current statistical analysis tools are not. Users must first translate their hypotheses into specific statistical tests and then perform API calls with functions and parameters. To do so accurately requires that users have statistical expertise. To lower this barrier to valid, replicable statistical analysis, we introduce Tea, a high-level declarative language and runtime system. In Tea, users express their study design, any parametric assumptions, and their hypotheses. Tea compiles these high-level specifications into a constraint satisfaction problem that determines the set of valid statistical tests, and then executes them to test the hypothesis. We evaluate Tea using a suite of statistical analyses drawn from popular tutorials. We show that Tea generally matches the choices of experts while automatically switching to non-parametric tests when parametric assumptions are not met. We simulate the effect of mistakes made by non-expert users and show that Tea automatically avoids both false negatives and false positives that could be produced by the application of incorrect statistical tests.Comment: 11 page

The Effect of iReady Mathematics Intervention on Student Achievement for Students in Kindergarten & First Grade

The purpose of this research is to examine the effects of the implementation of iReady mathematics intervention on student achievement. The study was conducted in a public school setting in two kindergarten classrooms and one first-grade classroom. The classrooms consisted of a total of 55 students between the ages of five and seven. Out of the 55 students, 12 qualified for the iReady intervention program. Data collection methods included district baseline and summative assessments, AimsWeb Progress monitoring assessment, a teacher observational journal, and a student conference form. After the four week implementation of the iReady mathematics intervention our data indicated increased student achievement for students performing below grade level and above grade level. However, the assessment data showed it was more effective for the below level students. Based on these results we will continue to implement the iReady mathematic intervention program in order to continue to increase student achievement

Inter-Regional Brain Communication and Its Disturbance in Autism

In this review article, we summarize recent progress toward understanding disturbances in functional and anatomical brain connectivity in autism. Autism is a neurodevelopmental disorder affecting language, social interaction, and repetitive behaviors. Recent studies have suggested that limitations of frontal–posterior brain connectivity in autism underlie the varied set of deficits associated with this disorder. Specifically, the underconnectivity theory of autism postulates that individuals with autism have a reduced communication bandwidth between frontal and posterior cortical areas, which constrains the psychological processes that rely on the integrated functioning of frontal and posterior brain networks. This review summarizes the recent findings of reduced frontal–posterior functional connectivity (synchronization) in autism in a wide variety of high-level tasks, focusing on data from functional magnetic resonance imaging studies. It also summarizes the findings of disordered anatomical connectivity in autism, as measured by a variety of techniques, including distribution of white matter volumes and diffusion tensor imaging. We conclude with a discussion of the implications of these findings for autism and future directions for this line of research

Does Ocean Acidification Benefit Seagrasses in a Mesohaline Environment? A Mesocosm Experiment in the Northern Gulf of Mexico

Ocean acidification is thought to benefit seagrasses because of increased carbon dioxide (CO2) availability for photosynthesis. However, in order to truly assess ecological responses, effects of ocean acidification need to be investigated in a variety of coastal environments. We tested the hypothesis that ocean acidification would benefit seagrasses in the northern Gulf of Mexico, where the seagrasses Halodule wrightii and Ruppia maritima coexist in a fluctuating environment. To evaluate if benefits of ocean acidification could alter seagrass bed composition, cores of H. wrightii and R. maritima were placed alone or in combination into aquaria and maintained in an outdoor mesocosm. Half of the aquaria were exposed to either ambient (mean pH of 8.1 ± 0.04 SD on total scale) or high CO2 (mean pH 7.7 ± 0.05 SD on total scale) conditions. After 54 days of experimental exposure, the δ13C values were significantly lower in seagrass tissue in the high CO2 condition. This integration of a different carbon source (either: preferential use of CO2, gas from cylinder, or both) indicates that plants were not solely relying on stored energy reserves for growth. Yet, after 41 to 54 days, seagrass morphology, biomass, photo-physiology, metabolism, and carbon and nitrogen content in the high CO2 condition did not differ from those at ambient. There was also no indication of differences in traits between the homospecific or heterospecific beds. Findings support two plausible conclusions: (1) these seagrasses rely heavily on bicarbonate use and growth will not be stimulated by near future acidification conditions or (2) the mesohaline environment limited the beneficial impacts of increased CO2 availability

A Population of X-ray Weak Quasars: PHL 1811 Analogs at High Redshift

We report the results from Chandra and XMM-Newton observations of a sample of 10 type 1 quasars selected to have unusual UV emission-line properties (weak and blueshifted high-ionization lines; strong UV Fe emission) similar to those of PHL 1811, a confirmed intrinsically X-ray weak quasar. These quasars were identified by the Sloan Digital Sky Survey at high redshift (z~2.2); eight are radio quiet while two are radio intermediate. All of the radio-quiet PHL 1811 analogs are notably X-ray weak by a mean factor of ~13. These sources lack broad absorption lines and have blue UV/optical continua, suggesting they are intrinsically X-ray weak. However, their average X-ray spectrum appears to be harder than those of typical quasars, which may indicate the presence of heavy intrinsic X-ray absorption. Our radio-quiet PHL 1811 analogs support a connection between an X-ray weak spectral energy distribution and PHL 1811-like UV emission lines; this connection provides an economical way to identify X-ray weak type 1 quasars. The fraction of radio-quiet PHL 1811 analogs in the radio-quiet quasar population is estimated to be < 1.2%. We have investigated correlations between relative X-ray brightness and UV emission-line properties for a sample combining radio-quiet PHL 1811 analogs, PHL 1811, and typical type 1 quasars. These correlation analyses suggest that PHL 1811 analogs may have extreme wind-dominated broad emission-line regions. Observationally, radio-quiet PHL 1811 analogs appear to be a subset (~30%) of radio-quiet weak-line quasars. The existence of a subset of quasars in which high-ionization "shielding gas" covers most of the BELR, but little more than the BELR, could potentially unify the PHL 1811 analogs and WLQs. The two radio-intermediate PHL 1811 analogs are X-ray bright. One of them appears to have jet-dominated X-ray emission, while the nature of the other remains unclear.Comment: ApJ accepted; 25 pages, 11 figures and 8 table

A Quasar Catalog with Simultaneous UV, Optical and X-ray Observations by Swift

We have compiled a catalog of optically-selected quasars with simultaneous observations in UV/optical and X-ray bands by the Swift Gamma Ray Burst Explorer. Objects in this catalog are identified by matching the Swift pointings with the Sloan Digital Sky Survey Data Release 5 quasar catalog. The final catalog contains 843 objects, among which 637 have both UVOT and XRT observations and 354 of which are detected by both instruments. The overall X-ray detection rate is ~60% which rises to ~85% among sources with at least 10 ks of XRT exposure time. We construct the time-averaged spectral energy distribution for each of the 354 quasars using UVOT photometric measurements and XRT spectra. From model fits to these SEDs, we find that the big blue bump contributes about 0.3 dex to the quasar luminosity. We re-visit the alpha_ox-L_uv relation by selecting a clean sample with only type 1 radio-quiet quasars; the dispersion of this relation is reduced by at least 15% compared to studies that use non-simultaneous UV/optical and X-ray data. We only found a weak correlation between L/L_Edd and alpha_uv. We do not find significant correlations between alpha_x and alpha_ox, alpha_ox and alpha_uv, and alpha_x and Log L(0.3-10 keV). The correlations between alpha_uv and alpha_x, alpha_ox and alpha_x, alpha_ox and alpha_uv, L/L_Edd and alpha_x, and L/L_Edd and alpha_ox are stronger amongst low-redshift quasars, indicating that these correlations are likely driven by the changes of SED shape with accretion state.Comment: 63 pages, 22 figures, accepted by ApJ

Standardized NEON organismal data for biodiversity research

Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high-quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators\u27 workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open-source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks

Geographic Variation in Salt Marsh Structure and Function for Nekton: a Guide to Finding Commonality Across Multiple Scales

Coastal salt marshes are distributed widely across the globe and are considered essential habitat for many fish and crustacean species. Yet, the literature on fishery support by salt marshes has largely been based on a few geographically distinct model systems, and as a result, inadequately captures the hierarchical nature of salt marsh pattern, process, and variation across space and time. A better understanding of geographic variation and drivers of commonalities and differences across salt marsh systems is essential to informing future management practices. Here, we address the key drivers of geographic variation in salt marshes: hydroperiod, seascape configuration, geomorphology, climatic region, sediment supply and riverine input, salinity, vegetation composition, and human activities. Future efforts to manage, conserve, and restore these habitats will require consideration of how environmental drivers within marshes affect the overall structure and subsequent function for fisheries species. We propose a future research agenda that provides both the consistent collection and reporting of sources of variation in small-scale studies and collaborative networks running parallel studies across large scales and geographically distinct locations to provide analogous information for data poor locations. These comparisons are needed to identify and prioritize restoration or conservation efforts, identify sources of variation among regions, and best manage fisheries and food resources across the globe