Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap

In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common family-wise error (FWE) controlling procedures in imaging, which rely on classical mathematical inequalities or Gaussian random field theory, yield FWE rates that are far from the nominal level. Depending on the approach used, the FWER can be exceedingly small or grossly inflated. Given the widespread use of neuroimaging as a tool for understanding neurological and psychiatric disorders, it is imperative that reliable multiple testing procedures are available. To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. However, these procedures are computationally intensive due to the increasingly available large sample sizes and dimensionality of the images, and analyses can take days to complete. Here, we develop a parametric bootstrap joint testing procedure. The parametric bootstrap procedure works directly with the test statistics, which leads to much faster estimation of adjusted \emph{p}-values than resampling-based procedures while reliably controlling the FWER in sample sizes available in many neuroimaging studies. We demonstrate that the procedure controls the FWER in finite samples using simulations, and present region- and voxel-wise analyses to test for sex differences in developmental trajectories of cerebral blood flow

Urbanization and its implications for food and farming

This paper discusses the influences on food and farming of an increasingly urbanized world and a declining ratio of food producers to food consumers. Urbanization has been underpinned by the rapid growth in the world economy and in the proportion of gross world product and of workers in industrial and service enterprises. Globally, agriculture has met the demands from this rapidly growing urban population, including food that is more energy-, land-, water- and greenhouse gas emission-intensive. But hundreds of millions of urban dwellers suffer under-nutrition. So the key issues with regard to agriculture and urbanization are whether the growing and changing demands for agricultural products from growing urban populations can be sustained while at the same time underpinning agricultural prosperity and reducing rural and urban poverty. To this are added the need to reduce greenhouse gas emissions and to build resilience in agriculture and urban development to climate change impacts. The paper gives particular attention to low- and middle-income nations since these have more than three-quarters of the world's urban population and most of its largest cities and these include nations where issues of food security are most pressing

Globally weaker and topologically different: resting-state connectivity in youth with autism

Abstract Background There is a lack of agreement about functional connectivity differences in individuals with autism spectrum disorder (ASD). Studies using absolute strength have found reduced connectivity, while those using relative strength––a measure of system topology––reveal mostly enhanced connectivity. We hypothesized that mixed findings may be driven by the metric of functional connectivity. Methods Resting-state echo planar 3 T functional magnetic resonance imaging scans were acquired on a Siemens Verio Scanner from 6 to 17-year-old youth with ASD (n = 81) and a matched typically developing control group (n = 82). All functional time series data were preprocessed using a confound regression procedure that has been previously validated in large-scale developmental datasets. It has also been shown to be highly effective at reducing the influence of motion artifact on connectivity data. We extracted time series data from a 333-node parcellation scheme, which was previously mapped to 13 functional systems. A Pearson’s correlation was calculated and transformed to Fisher’s z between every pair of nodes to create a weighted 333 × 333 adjacency matrix. Mean absolute functional connectivity strength was the mean Fisher’s z of the matrix. Relative functional connectivity was corrected for individual differences in mean absolute functional connectivity (i.e., each connection in the matrix was divided by their mean z), and functional connectivity was evaluated within and across each of the functional networks in the parcellation scheme. Results Absolute functional connectivity strength was lower in ASD, and lower functional connectivity was correlated with greater ASD symptom severity. Relative functional connectivity was higher for the ASD group in the ventral attention and retrosplenial-temporal systems, with lower cross-system functional connectivity between the ventral attention and somatomotor-mouth systems. Functional connectivity within the ventral attention and retro-splenial systems correlated significantly with ASD symptom severity. Conclusions Within a context of globally weaker functional connectivity, youth with ASD have an atypical topology of brain systems that support social perception and communication. This study clarifies the mixed results reported previously and demonstrates that the functional connectivity metric influences the observed direction of functional connectivity differences for individuals with ASD

Improving the health and welfare of people who live in slums

Summary In the first paper in this Series we assessed theoretical and empirical evidence and concluded that the health of people living in slums is a function not only of poverty but of intimately shared physical and social environments. In this paper we extend the theory of so-called neighbourhood effects. Slums offer high returns on investment because beneficial effects are shared across many people in densely populated neighbourhoods. Neighbourhood effects also help explain how and why the benefits of interventions vary between slum and non-slum spaces and between slums. We build on this spatial concept of slums to argue that, in all low-income and-middle-income countries, census tracts should henceforth be designated slum or non-slum both to inform local policy and as the basis for research surveys that build on censuses. We argue that slum health should be promoted as a topic of enquiry alongside poverty and health

Striatal intrinsic reinforcement signals during recognition memory: relationship to response bias and dysregulation in schizophrenia

Ventral striatum (VS) is a critical brain region for reinforcement learning and motivation, and VS hypofunction is implicated in psychiatric disorders including schizophrenia. Providing rewards or performance feedback has been shown to activate VS. Intrinsically motivated subjects performing challenging cognitive tasks are likely to engage reinforcement circuitry even in the absence of external feedback or incentives. However, such intrinsic reinforcement responses have received little attention, have not been examined in relation to behavioral performance, and have not been evaluated for impairment in neuropsychiatric disorders such as schizophrenia. Here we used fMRI to examine a challenging “old” vs. “new” visual recognition task in healthy subjects and patients with schizophrenia. Targets were unique fractal stimuli previously presented as salient distractors in a visual oddball task, producing incidental memory encoding. Based on the prediction error theory of reinforcement learning, we hypothesized that correct target recognition would activate VS in controls, and that this activation would be greater in subjects with lower expectation of responding correctly as indexed by a more conservative response bias. We also predicted these effects would be reduced in patients with schizophrenia. Consistent with these predictions, controls activated VS and other reinforcement processing regions during correct recognition, with greater VS activation in those with a more conservative response bias. Patients did not show either effect, with significant group differences suggesting hyporesponsivity in patients to internally generated feedback. These findings highlight the importance of accounting for intrinsic motivation and reward when studying cognitive tasks, and add to growing evidence of reward circuit dysfunction in schizophrenia that may impact cognition and function

Few-layer Nanoplates of Bi2Se3 and Bi2Te3 with Highly Tunable Chemical Potential

Topological insulator (TI) represents an unconventional quantum phase of matter with insulating bulk bandgap and metallic surface states. Recent theoretical calculations and photoemission spectroscopy measurements show that Group V-VI materials Bi2Se3, Bi2Te3 and Sb2Te3 are TI with a single Dirac cone on the surface. These materials have anisotropic, layered structures, in which five atomic layers are covalently bonded to form a quintuple layer, and quintuple layers interact weakly through van der Waals interaction to form the crystal. A few quintuple layers of these materials are predicted to exhibit interesting surface properties. Different from our previous nanoribbon study, here we report the synthesis and characterizations of ultrathin Bi2Te3 and Bi2Se3 nanoplates with thickness down to 3 nm (3 quintuple layers), via catalyst-free vapor-solid (VS) growth mechanism. Optical images reveal thickness-dependant color and contrast for nanoplates grown on oxidized silicon (300nm SiO2/Si). As a new member of TI nanomaterials, ultrathin TI nanoplates have an extremely large surface-to-volume ratio and can be electrically gated more effectively than the bulk form, potentially enhancing surface states effects in transport measurements. Low temperature transport measurements of a single nanoplate device, with a high-k dielectric top gate, show decrease in carrier concentration by several times and large tuning of chemical potential.Comment: 6 figure

Environmental and Parental Influences on Offspring Health and Growth in Great Tits (Parus major)

PMCID: PMC3728352This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Testing the efficacy of voluntary urban greenhouse gas emissions inventories

Drawing from an original dataset of urban metropolitan carbon footprints, we explore the correlations between national level climate change commitments and subnational level inventories. We ask: Does voluntary reporting allow a city to perform better than national average? Does ambitiousness in commitment have an impact on performance in footprint reduction? Does having long-term commitments affect performance in footprint reduction? Do binding national level commitments (such as those under the Kyoto Protocol) affect performance at the city level in terms of footprint reduction? To provide answers, we synthesize data from the largest repository of voluntary sub-national commitments and actions towards footprint reduction and greenhouse gas inventories from around the world, the Carbonn platform. More than 500 cities report at least one action, commitment or inventory to this database. We find, using a subset of this database, perhaps counter intuitively that cities with more ambitious commitments do not necessarily have steeper reductions in emissions. Our data also suggest that having long-term self-reported goals does not make the cities perform better in terms of footprint reduction. This appears to be true for both government and community commitments reported. Lastly, and positively, our data did reveal a statistically significant effect for cities belonging to countries that had committed to the Kyoto Protocol, suggesting the necessity of binding national (and supranational) climate targets