An Investigation of Skill Acquisition under Conditions of Augmented Reality

Augmented reality is a virtual environment that integrates rendered content with the experience of the real world. There is evidence suggesting that augmented reality provides for important spatial constancy of objects relative to the real world coordinate system and that this quality contributes to rapid skill acquisition. The qualities of simulation, through the use of augmented reality, may be incorporated into actual job activities to produce a condition of just-in-time learning. This may make possible the rapid acquisition of information and reliable completion of novel or infrequently performed tasks by individuals possessing a basic skill-set. The purpose of this research has been to investigate the degree to which the acquisition of a skill is enhanced through the use of an augmented reality training device

An Open Resource for Non-human Primate Imaging

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets

An Open Resource for Non-human Primate Imaging

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets

A benchmark for prediction of psychiatric multimorbidity from resting EEG data in a large pediatric sample

Psychiatric disorders are among the most common and debilitating illnesses across the lifespan and begin usually during childhood and adolescence, which emphasizes the importance of studying the developing brain. Most of the previous pediatric neuroimaging studies employed traditional univariate statistics on relatively small samples. Multivariate machine learning approaches have a great potential to overcome the limitations of these approaches. On the other hand, the vast majority of existing multivariate machine learning studies have focused on differentiating between children with an isolated psychiatric disorder and typically developing children. However, this line of research does not reflect the real-life situation as the majority of children with a clinical diagnosis have multiple psychiatric disorders (multimorbidity), and consequently, a clinician has the task to choose between different diagnoses and/or the combination of multiple diagnoses. Thus, the goal of the present benchmark is to predict psychiatric multimorbidity in children and adolescents. For this purpose, we implemented two kinds of machine learning benchmark challenges: The first challenge targets the prediction of the seven most prevalent DSM-V psychiatric diagnoses for the available data set, of which each individual can exhibit multiple ones concurrently (i.e. multi-task multi-label classification). Based on behavioral and cognitive measures, a second challenge focuses on predicting psychiatric symptom severity on a dimensional level (i.e. multiple regression task). For the present benchmark challenges, we will leverage existing and future data from the biobank of the Healthy Brain Network (HBN) initiative, which offers a unique large-sample dataset (N = 2042) that provides a wide array of different psychiatric developmental disorders and true hidden data sets. Due to limited real-world practicability and economic viability of MRI measurements, the present challenge will permit only resting state EEG data and demographic information to derive predictive models. We believe that a community driven effort to derive predictive markers from these data using advanced machine learning algorithms can help to improve the diagnosis of psychiatric developmental disorders

Age and sex affect intersubject correlation of EEG throught development

Recent efforts have aimed to characterize clinical pediatric populations by using neurophysiological tests in addition to behavioral assays. Here we report on a data collection effort in which electroencephalography (EEG) was recorded in both juveniles and adults (N=114 participants, ages 6-44 years of age) during various stimulation protocols. The present analysis focuses on how neural responses during passive viewing of naturalistic videos vary with age and sex, and in particular, how similar they are within developmental groups. Similarity of neural responses was measured as the inter-subject correlation of the EEG. Stimulus-evoked neural responses are more similar among children and decrease in similarity with age. Among children, males respond more similarly to each other than females. This was uniformly true for a variety of videos. The decrease in group similarity with age may result from an overall decline in the magnitude of evoked responses, but this cannot explain the sex differences found in the young. We therefore propose that as children mature, neural function may become more variable

Effect of Soil pH on Emergence and Survival of \u3ci\u3eAustrodanthonia\u3c/i\u3e spp.

We evaluated the effects of soil acidity on seedling emergence and seedling persistence of several ecotypes of Austrodanthonia spp. collected from the Central, Southern and Monaro Tablelands of New South Wales (NSW) in southern temperate Australia. A pot experiment was conducted outdoors to identify the most promising material tolerant to soil acidity for domestication. In the experiment, 183 ecotypes and two commercial cultivars of Austrodanthonia were grown in pots at three levels of pHCa (3.9, 4.4 and 5.3). The pH treatments were achieved by adding either aluminium sulphate or lime to an acid earthy sandy loam soil collected from a grazing farm. Seedling emergence and persistence were recorded for 170 days after sowing (DAS). Establishment of all lines was severely reduced by soil acidity. At pH 3.9, average seedling emergence over all lines was 11%, whereas, at higher pH (pH 4.4 and 5.3) emergence was about 72%. Of the seeds sown, survival at 170 DAS was, on average, less than 1% at pH 3.9, compared with 25% at pH 4.4 and 5.3. Further investigations on species/ecotypes, particularly those favoured at low soil pH, should provide a useful basis for selection programmes

The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex

Neural development is generally marked by an increase in the efficiency and diversity of neural processes. In a large sample (n=114) of human children and adults with ages ranging from 5 to 44 yr, we investigated the neural responses to naturalistic video stimuli. Videos from both real-life classroom settings and Hollywood feature films were used to probe different aspects of attention and engagement. For all stimuli, older ages were marked by more variable neural responses. Variability was assessed by the intersubject correlation of evoked electroencephalographic responses. Young males also had less-variable responses than young females. These results were replicated in an independent cohort (n = 303). When interpreted in the context of neural maturation, we conclude that neural function becomes more variable with maturity, at least during the passive viewing of real-world stimuli.Fil: Petroni, Agustín. City University of New York; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cohen, Samantha S.. City University of New York; Estados UnidosFil: Ai, Lei. City University of New York; Estados UnidosFil: Langer, Nicolas. City University of New York; Estados UnidosFil: Henin, Simon. City University of New York; Estados UnidosFil: Vanderwal, Tamara. City University of New York; Estados UnidosFil: Milham, Michael P.. City University of New York; Estados UnidosFil: Parra, Lucas C.. City University of New York; Estados Unido

Toward open sharing of task-based fMRI data: the OpenfMRI project

The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function

Quantification of AMPA receptor subunits and RNA editing-related proteins in the J20 mouse model of Alzheimer’s disease by capillary western blotting

IntroductionAccurate modelling of molecular changes in Alzheimer’s disease (AD) dementia is crucial for understanding the mechanisms driving neuronal pathology and for developing treatments. Synaptic dysfunction has long been implicated as a mechanism underpinning memory dysfunction in AD and may result in part from changes in adenosine deaminase acting on RNA (ADAR) mediated RNA editing of the GluA2 subunit of AMPA receptors and changes in AMPA receptor function at the post synaptic cleft. However, few studies have investigated changes in proteins which influence RNA editing and notably, AD studies that focus on studying changes in protein expression, rather than changes in mRNA, often use traditional western blotting.MethodsHere, we demonstrate the value of automated capillary western blotting to investigate the protein expression of AMPA receptor subunits (GluA1-4), the ADAR RNA editing proteins (ADAR1-3), and proteins known to regulate RNA editing (PIN1, WWP2, FXR1P, and CREB1), in the J20 AD mouse model. We describe extensive optimisation and validation of the automated capillary western blotting method, demonstrating the use of total protein to normalise protein load, in addition to characterising the optimal protein/antibody concentrations to ensure accurate protein quantification. Following this, we assessed changes in proteins of interest in the hippocampus of 44-week-old J20 AD mice.ResultsWe observed an increase in the expression of ADAR1 p110 and GluA3 and a decrease in ADAR2 in the hippocampus of 44-week-old J20 mice. These changes signify a shift in the balance of proteins that play a critical role at the synapse. Regression analysis revealed unique J20-specific correlations between changes in AMPA receptor subunits, ADAR enzymes, and proteins that regulate ADAR stability in J20 mice, highlighting potential mechanisms mediating RNA-editing changes found in AD.DiscussionOur findings in J20 mice generally reflect changes seen in the human AD brain. This study underlines the importance of novel techniques, like automated capillary western blotting, to assess protein expression in AD. It also provides further evidence to support the hypothesis that a dysregulation in RNA editing-related proteins may play a role in the initiation and/or progression of AD

Racial Disparities in In-hospital Mortality and Discharge Disposition among Trauma Patients in Massachusetts

Background: Population-based data on trauma care are important to a solid understanding of racial disparities in the care and outcomes of trauma patients. Methods: Data on inpatient hospitalizations for trauma were obtained from the Massachusetts (MA) Statewide Trauma Registry which conducts annual census of trauma-related hospitalizations in MA. This analysis included patients who were MA residents and admitted to a MA hospital between 2008 and 2010, and 15 years and older at the time of admission. Patients were grouped as non-Hispanic white, non-Hispanic black, Hispanic, Asian, and other or unknown race. Injury severity, discharge disposition and mortality of the first hospitalization of the patients were compared among the groups while adjusting for sex, age and severity. Results: The data were from 23,666 patients with a mean age of 63.8 years. The patients included 51.8% women, 86.1% whites, 4.3% blacks, 5.6% Hispanics, 1.2% Asians and 2.7% other or unknown races. In total, 597 (2.52%) died in the hospital. Asians and other races had higher risk for death (OR=2.96, p Conclusions: Remarkable racial/ethnic disparities in inhospital mortality and discharge dispositions were seen among trauma patients in MA. The determinants of the disparities and related policy implications are under investigation by a study supported by the National Institute on Minority Health and Health Disparities