A spatial variation model of white matter microstructure

In this study, we introduce a new technique to model the variation of microstructural parameters across speci c brain regions. We use a simple model of di usion in each voxel, but model the variation of parameters across the region using penalised splines. We t the whole region model directly to the di usion-weighted signals. We test the tech- nique on the mid-sagittal section of the corpus callosum (CC) using a di usion MRI data set with distinct age groups. The method detects di erences and separates the groups

A holographic system for subsea recording and analysis of plankton and other marine particles

We report here details of the design, development, initial testing and field-deployment of the HOLOMAR system for in-situ subsea holography and analysis of marine plankton and nonliving particles. HOLOMAR comprises a submersible holographic camera ("HoloCam") able to record in-line and off-axis holograms at depths down to 100 m, together with specialised reconstruction hardware ("HoloScan") linked to custom image processing and classification software. The HoloCam consists of a laser and power supply, holographic recording optics and holographic plate holders, a water-tight housing and a support frame. It utilises two basic holographic geometries, in-line and off-axis such that a wide range of species, sizes and concentrations can be recorded. After holograms have been recorded and processed they are reconstructed in full three-dimensional detail in air in a dedicated replay facility. A computer-controlled microscope, using video cameras to record the image at a given depth, is used to digitise the scene. Specially written software extracts a binarised image of an object in its true focal plane and is classified using a neural network. The HoloCam was deployed on two separate cruises in a Scottish sea loch (Loch Etive) to a depth of 100 m and over 300 holograms were recorded

Sympathetic autonomic dysfunction and impaired cardiovascular performance in higher risk surgical patients: implications for perioperative sympatholysis

OBJECTIVE: Recent perioperative trials have highlighted the urgent need for a better understanding of why sympatholytic drugs intended to reduce myocardial injury are paradoxically associated with harm (stroke, myocardial infarction). We hypothesised that following a standardised autonomic challenge, a subset of patients may demonstrate excessive sympathetic activation which is associated with exercise-induced ischaemia and impaired cardiac output. METHODS: Heart rate rise during unloaded pedalling (zero workload) prior to the onset of cardiopulmonary exercise testing (CPET) was measured in 2 observation cohorts of elective surgical patients. The primary outcome was exercise-evoked, ECG-defined ischaemia (>1 mm depression; lead II) associated with an exaggerated increase in heart rate (EHRR ≥12 bpm based on prognostic data for all-cause cardiac death in preceding epidemiological studies). Secondary outcomes included cardiopulmonary performance (oxygen pulse (surrogate for left ventricular stroke volume), peak oxygen consumption (VO2peak), anaerobic threshold (AT)) and perioperative heart rate. RESULTS: EHRR was present in 40.4-42.7% in both centres (n=232, n=586 patients). Patients with EHRR had higher heart rates perioperatively (p<0.05). Significant ST segment depression during CPET was more common in EHRR patients (relative risk 1.7 (95% CI 1.3 to 2.1); p<0.001). EHRR was associated with 11% (95%CI 7% to 15%) lower predicted oxygen pulse (p<0.0001), consistent with impaired left ventricular function. CONCLUSIONS: EHRR is common and associated with ECG-defined ischaemia and impaired cardiac performance. Perioperative sympatholysis may further detrimentally affect cardiac output in patients with this phenotype

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Self-Affirmation Improves Problem-Solving under Stress

High levels of acute and chronic stress are known to impair problem-solving and creativity on a broad range of tasks. Despite this evidence, we know little about protective factors for mitigating the deleterious effects of stress on problem-solving. Building on previous research showing that self-affirmation can buffer stress, we tested whether an experimental manipulation of self-affirmation improves problem-solving performance in chronically stressed participants. Eighty undergraduates indicated their perceived chronic stress over the previous month and were randomly assigned to either a self-affirmation or control condition. They then completed 30 difficult remote associate problem-solving items under time pressure in front of an evaluator. Results showed that self-affirmation improved problem-solving performance in underperforming chronically stressed individuals. This research suggests a novel means for boosting problem-solving under stress and may have important implications for understanding how self-affirmation boosts academic achievement in school settings. © 2013 Creswell et al

Global services and support for children with developmental delays and disabilities: Bridging research and policy gaps

Summary: 1. The United Nations Sustainable Development Goals and the UN Convention on the Rights of the Child (CRC) envision an inclusive society in which health and education contribute to the well-being of all. To achieve this vision, children with developmental delays and behavioral, cognitive, mental, and neurological disabilities need greater access to health care, early childhood care and development services, and education. 2. Improved population-level detection, alongside screening, assessment, and linkage to evidence-based, intersectoral services in the first years of life, can help maximize capabilities and increase the chances of social inclusion for children with developmental delays and disabilities. 3. Educational programs for children with delays and disabilities whose service delivery structure supports the ability of parents to work should be encouraged so that parents can participate in achieving children’s educational goals while also meeting their financial needs. 4. Parents and caregivers who receive training in psychosocial interventions and ongoing support can help children with delays and disabilities thrive in family contexts. 5. Family mental health influences the developmental trajectory of children. Ensuring that parents and caregivers have access to affordable, quality mental health services helps to prevent poor outcomes for children. 6. Rigorous evaluation, continuous quality improvement, and regular monitoring of the programmatic outcomes of services and policy approaches targeting children and caregivers would inform their implementation and serve to disseminate lessons learned from successful policy and program implementation