Do synaesthesia and mental imagery tap into similar cross-modal processes?

Synaesthesia has previously been linked with imagery abilities, although an understanding of a causal role for mental imagery in broader synaesthetic experiences remains elusive. This can be partly attributed to our relatively poor understanding of imagery in sensory domains beyond vision. Investigations into the neural and behavioural underpinnings of mental imagery have nevertheless identified an important role for imagery in perception, particularly in mediating cross-modal interactions. However, the phenomenology of synaesthesia gives rise to the assumption that associated cross-modal interactions may be encapsulated and specific to synaesthesia. As such, evidence for a link between imagery and perception may not generalize to synaesthesia. Here, we present results that challenge this idea: first, we found enhanced somatosensory imagery evoked by visual stimuli of body parts in mirror-touch synaesthetes, relative to other synaesthetes or controls. Moreover, this enhanced imagery generalized to tactile object properties not directly linked to their synaesthetic associations. Second, we report evidence that concurrent experience evoked in grapheme-colour synaesthesia was sufficient to trigger visual-to-tactile correspondences that are common to all. Together, these findings show that enhanced mental imagery is a consistent hallmark of synaesthesia, and suggest the intriguing possibility that imagery may facilitate the cross-modal interactions that underpin synaesthesic experiences. This article is part of a discussion meeting issue 'Bridging senses: novel insights from synaesthesia'

Vaccination and All Cause Child Mortality 1985-2011: Global Evidence from the Demographic and Health Surveys

Based on models with calibrated parameters for infection, case fatality rates, and vaccine efficacy, basic childhood vaccinations have been estimated to be highly cost effective. We estimated the association of vaccination with mortality directly from survey data. Using 149 cross-sectional Demographic and Health Surveys, we determined the relationship between vaccination coverage and the probability of dying between birth and 5 years of age at the survey cluster level. Our data included approximately 1 million children in 68,490 clusters from 62 countries. We considered the childhood measles, bacillus Calmette-Guérin, diphtheria-pertussis-tetanus, polio, and maternal tetanus vaccinations. Using modified Poisson regression to estimate the relative risk of child mortality in each cluster, we also adjusted for selection bias that resulted from the vaccination status of dead children not being reported. Childhood vaccination, and in particular measles and tetanus vaccination, is associated with substantial reductions in childhood mortality. We estimated that children in clusters with complete vaccination coverage have a relative risk of mortality that is 0.73 (95% confidence interval: 0.68, 0.77) times that of children in a cluster with no vaccinations. Although widely used, basic vaccines still have coverage rates well below 100% in many countries, and our results emphasize the effectiveness of increasing coverage rates in order to reduce child mortality

Football's coming home ? digital reterritorialization, contradictions in the transnational coverage of sport and the sociology of alternative football broadcasts.

This article critically utilizes the work of Manuel Castells to discuss the issue of parallel imported broadcasts (specifically including live-streams) in football. This is of crucial importance to sport because the English Premier League is premised upon the sale of television rights broadcasts to domestic and overseas markets, and yet cheaper alternative broadcasts endanger the price of such rights. Evidence is drawn from qualitative fieldwork and library/Internet sources to explore the practices of supporters and the politics involved in the generation of alternative broadcasts. This enables us to clarify the core sociological themes of ‘milieu of innovation’ and ‘locale’ within today's digitally networked global society

Perceptual learning reconfigures the effects of visual adaptation

Our sensory experiences over a range of different timescales shape our perception of the environment. Two particularly striking short-term forms of plasticity with manifestly different time courses and perceptual consequences are those caused by visual adaptation and perceptual learning. Although conventionally treated as distinct forms of experience-dependent plasticity, their neural mechanisms and perceptual consequences have become increasingly blurred, raising the possibility that they might interact. To optimize our chances of finding a functionally meaningful interaction between learning and adaptation, we examined in humans the perceptual consequences of learning a fine discrimination task while adapting the neurons that carry most information for performing this task. Learning improved discriminative accuracy to a level that ultimately surpassed that in an unadapted state. This remarkable improvement came at a price: adapting directions that before learning had little effect elevated discrimination thresholds afterward. The improvements in discriminative accuracy grew quickly and surpassed unadapted levels within the first few training sessions, whereas the deterioration in discriminative accuracy had a different time course. This learned reconfiguration of adapted discriminative accuracy occurred without a concomitant change to the characteristic perceptual biases induced by adaptation, suggesting that the system was still in an adapted state. Our results point to a functionally meaningful push–pull interaction between learning and adaptation in which a gain in sensitivity in one adapted state is balanced by a loss of sensitivity in other adapted states

Plane of nutrition affects the phylogenetic diversity and relative abundance of transcriptionally active methanogens in the bovine rumen

peer-reviewedMethane generated during enteric fermentation in ruminant livestock species is a major contributor to global anthropogenic greenhouse gas emissions. A period of moderate feed restriction followed by ad libitum access to feed is widely applied in cattle management to exploit the animal’s compensatory growth potential and reduce feed costs. In the present study, we utilised microbial RNA from rumen digesta samples to assess the phylogenetic diversity of transcriptionally active methanogens from feed-restricted and non-restricted animals. To determine the contribution of different rumen methanogens to methanogenesis during dietary restriction of cattle, we conducted high-throughput mcrA cDNA amplicon sequencing on an Illumina MiSeq and analysed both the abundance and phylogenetic origin of different mcrA cDNA sequences. When compared to their unrestricted contemporaries, in feed-restricted animals, the methanogenic activity, based on mcrA transcript abundance, of Methanobrevibacter gottschalkii clade increased while the methanogenic activity of the Methanobrevibacter ruminantium clade and members of the Methanomassiliicoccaceae family decreased. This study shows that the quantity of feed consumed can evoke large effects on the composition of methanogenically active species in the rumen of cattle. These data potentially have major implications for targeted CH4 mitigation approaches such as anti-methanogen vaccines and/or tailored dietary management

Characterizing the role of disparity information in alleviating visual crowding

The ability to identify a target is reduced by the presence of nearby objects, a phenomenon known as visual crowding. The extent to which crowding impairs our perception is generally governed by the degree of similarity between a target stimulus and its surrounding flankers. Here we investigated the influence of disparity differences between target and flankers on crowding. Orientation discrimination thresholds for a parafoveal target were first measured when the target and flankers were presented at the same depth to establish a flanker separation that induced a significant elevation in threshold for each individual. Flankers were subsequently fixed at this spatial separation while the disparity of the flankers relative to the target was altered. For all participants, thresholds showed a systematic decrease as flanker-target disparity increased. The resulting tuning function was asymmetric: Crowding was lower when the target was perceived to be in front of the flankers rather than behind. A series of control experiments confirmed that these effects were driven by disparity, as opposed to other factors such as flanker-target separation in three-dimensional (3-D) space or monocular positional offsets used to create disparity. When flankers were distributed over a range of crossed and uncrossed disparities, such that the mean was in the plane of the target, there was an equivalent or greater release of crowding compared to when all flankers were presented at the maximum disparity of that range. Overall, our results suggest that depth cues can reduce the effects of visual crowding, and that this reduction is unlikely to be caused by grouping of flankers or positional shifts in the monocular image

A Machine Learning Tutorial for Operational Meteorology, Part II: Neural Networks and Deep Learning

Over the past decade the use of machine learning in meteorology has grown rapidly. Specifically neural networks and deep learning have been used at an unprecedented rate. In order to fill the dearth of resources covering neural networks with a meteorological lens, this paper discusses machine learning methods in a plain language format that is targeted for the operational meteorological community. This is the second paper in a pair that aim to serve as a machine learning resource for meteorologists. While the first paper focused on traditional machine learning methods (e.g., random forest), here a broad spectrum of neural networks and deep learning methods are discussed. Specifically this paper covers perceptrons, artificial neural networks, convolutional neural networks and U-networks. Like the part 1 paper, this manuscript discusses the terms associated with neural networks and their training. Then the manuscript provides some intuition behind every method and concludes by showing each method used in a meteorological example of diagnosing thunderstorms from satellite images (e.g., lightning flashes). This paper is accompanied with an open-source code repository to allow readers to explore neural networks using either the dataset provided (which is used in the paper) or as a template for alternate datasets

Perceptual learning shapes multisensory causal inference via two distinct mechanisms

To accurately represent the environment, our brains must integrate sensory signals from a common source while segregating those from independent sources. A reasonable strategy for performing this task is to restrict integration to cues that coincide in space and time. However, because multisensory signals are subject to differential transmission and processing delays, the brain must retain a degree of tolerance for temporal discrepancies. Recent research suggests that the width of this 'temporal binding window' can be reduced through perceptual learning, however, little is known about the mechanisms underlying these experience-dependent effects. Here, in separate experiments, we measure the temporal and spatial binding windows of human participants before and after training on an audiovisual temporal discrimination task. We show that training leads to two distinct effects on multisensory integration in the form of (i) a specific narrowing of the temporal binding window that does not transfer to spatial binding and (ii) a general reduction in the magnitude of crossmodal interactions across all spatiotemporal disparities. These effects arise naturally from a Bayesian model of causal inference in which learning improves the precision of audiovisual timing estimation, whilst concomitantly decreasing the prior expectation that stimuli emanate from a common source