522 research outputs found

    Do emotional faces capture attention, and does this depend on awareness? Evidence from the visual probe paradigm

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    The visual probe (VP) paradigm provides evidence that emotional stimuli attract attention. Such effects have been reported even when stimuli are presented outside of awareness. These findings have shaped the idea that humans possess a processing pathway that detects evolutionarily significant signals independently of awareness. Here, we addressed 2 unresolved questions: First, if emotional stimuli attract attention, is this driven by their affective content, or by low-level image properties (e.g., luminance contrast)? Second, does attentional capture occur under conditions of genuine unawareness? We found that observers preferentially allocated attention to emotional faces under aware viewing conditions. However, this effect was best explained by low-level stimulus properties, rather than emotional content. When stimuli were presented outside of awareness (via continuous flash suppression or masking), we found no evidence that attention was directed toward emotional face stimuli. Finally, observer's awareness of the stimuli (assessed by d') predicted attentional cuing. Our data challenge existing literature: First, we cast doubt on the notion of preferential attention to emotional stimuli in the absence of awareness. Second, we question whether effects revealed by the VP paradigm genuinely reflect emotion-sensitive processes, instead suggesting they can be more parsimoniously explained by low-level variability between stimuli. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

    Does comorbid anxiety counteract emotion recognition deficits in conduct disorder?

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    Background: Previous research has reported altered emotion recognition in both conduct disorder (CD) and anxiety disorders (ADs) - but these effects appear to be of different kinds. Adolescents with CD often show a generalised pattern of deficits, while those with ADs show hypersensitivity to specific negative emotions. Although these conditions often cooccur, little is known regarding emotion recognition performance in comorbid CD+ADs. Here, we test the hypothesis that in the comorbid case, anxiety-related emotion hypersensitivity counteracts the emotion recognition deficits typically observed in CD. Method: We compared facial emotion recognition across four groups of adolescents aged 12-18 years: those with CD alone (n = 28), ADs alone (n = 23), cooccurring CD+ADs (n = 20) and typically developing controls (n = 28). The emotion recognition task we used systematically manipulated the emotional intensity of facial expressions as well as fixation location (eye, nose or mouth region). Results: Conduct disorder was associated with a generalised impairment in emotion recognition; however, this may have been modulated by group differences in IQ. AD was associated with increased sensitivity to low-intensity happiness, disgust and sadness. In general, the comorbid CD+ADs group performed similarly to typically developing controls. Conclusions: Although CD alone was associated with emotion recognition impairments, ADs and comorbid CD+ADs were associated with normal or enhanced emotion recognition performance. The presence of comorbid ADs appeared to counteract the effects of CD, suggesting a potentially protective role, although future research should examine the contribution of IQ and gender to these effects

    Motion adaptation and attention: A critical review and meta-analysis

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    The motion aftereffect (MAE) provides a behavioural probe into the mechanisms underlying motion perception, and has been used to study the effects of attention on motion processing. Visual attention can enhance detection and discrimination of selected visual signals. However, the relationship between attention and motion processing remains contentious: not all studies find that attention increases MAEs. Our meta-analysis reveals several factors that explain superficially discrepant findings. Across studies (37 independent samples, 76 effects) motion adaptation was significantly and substantially enhanced by attention (Cohen's d = 1.12, p < .0001). The effect more than doubled when adapting to translating (vs. expanding or rotating) motion. Other factors affecting the attention-MAE relationship included stimulus size, eccentricity and speed. By considering these behavioural analyses alongside neurophysiological work, we conclude that feature-based (rather than spatial, or object-based) attention is the biggest driver of sensory adaptation. Comparisons between naïve and non-naïve observers, different response paradigms, and assessment of 'file-drawer effects' indicate that neither response bias nor publication bias are likely to have significantly inflated the estimated effect of attention

    Are visual threats prioritized without awareness? A critical review and meta analysis involving 3 behavioral paradigms and 2696 observers

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    Given capacity limits, only a subset of stimuli 1 give rise to a conscious percept. Neurocognitive models suggest that humans have evolved mechanisms that operate without awareness and prioritize threatening stimuli over neutral stimuli in subsequent perception. In this meta analysis, we review evidence for this ‘standard hypothesis’ emanating from three widely used, but rather different experimental paradigms that have been used to manipulate awareness. We found a small pooled threat-bias effect in the masked visual probe paradigm, a medium effect in the binocular rivalry paradigm and highly inconsistent effects in the breaking continuous flash suppression paradigm. Substantial heterogeneity was explained by the stimulus type: the only threat stimuli that were robustly prioritized across all three paradigms were fearful faces. Meta regression revealed that anxiety may modulate threat biases, but only under specific presentation conditions. We also found that insufficiently rigorous awareness measures, inadequate control of response biases and low level confounds may undermine claims of genuine unconscious threat processing. Considering the data together, we suggest that uncritical acceptance of the standard hypothesis is premature: current behavioral evidence for threat-sensitive visual processing that operates without awareness is weak

    Use of Local Image Information in Depth Edge Classification by Humans and Neural Networks

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    Humans can use local cues to distinguish image edges caused by a depth change from other types of edges (Vilankar et al., 2014). But which local cues? Here we use the SYNS database (Adams et al., 2016) to automatically label edges in images of natural scenes as depth or non-depth. We use this ground truth to identify the cues used by human observers and convolutional neural networks (CNNs) for edge classification. Eight observers viewed square image patches, each centered on an image edge, ranging in width from 0.6 to 2.4 degrees (8 to 32 pixels). Human judgments (depth/non-depth) were compared to responses of a CNN trained on the same task. Human performance improved with patch size (65%-74% correct) but remained well below CNN accuracy (82-86% correct). Agreement between humans and the CNN was above chance but lower than human-human agreement. Decision Variable Correlation (Sebastian & Geisler, in press) was used to evaluate the relationships between depth responses and local edge cues. Humans seem to rely primarily on contrast cues, specifically luminance contrast and red-green contrast across the edge. The CNN also relies on luminance contrast, but unlike humans it seems to make use of mean luminance and red-green intensity as well. These local luminance and color features provide valid cues for depth edge discrimination in natural scenes

    The Southampton-York Natural Scenes (SYNS) dataset: statistics of surface attitude

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    Recovering 3D scenes from 2D images is an under-constrained task; optimal estimation depends upon knowledge of the underlying scene statistics. Here we introduce the Southampton-York Natural Scenes dataset (SYNS: https://syns.soton.ac.uk), which provides comprehensive scene statistics useful for understanding biological vision and for improving machine vision systems. In order to capture the diversity of environments that humans encounter, scenes were surveyed at random locations within 25 indoor and outdoor categories. Each survey includes (i) spherical LiDAR range data (ii) high-dynamic range spherical imagery and (iii) a panorama of stereo image pairs. We envisage many uses for the dataset and present one example: an analysis of surface attitude statistics, conditioned on scene category and viewing elevation. Surface normals were estimated using a novel adaptive scale selection algorithm. Across categories, surface attitude below the horizon is dominated by the ground plane (0° tilt). Near the horizon, probability density is elevated at 90°/270° tilt due to vertical surfaces (trees, walls). Above the horizon, probability density is elevated near 0° slant due to overhead structure such as ceilings and leaf canopies. These structural regularities represent potentially useful prior assumptions for human and machine observers, and may predict human biases in perceived surface attitude

    Avoimen systeemin magmaattisten prosessien diagnosointi Magmakammiosimulaattorilla. Osa II: hivenalkuaineet ja isotoopit

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    The Magma Chamber Simulator (MCS) is a thermodynamic model that computes the phase, thermal, and compositional evolution of a multiphase–multicomponent system of a Fractionally Crystallizing resident body of magma (i.e., melt ± solids ± fluid), linked wallrock that may either be assimilated as Anatectic melts or wholesale as Stoped blocks, and multiple Recharge reservoirs (RnASnFC system, where n is the number of user-selected recharge events). MCS calculations occur in two stages; the first utilizes mass and energy balance to produce thermodynamically constrained major element and phase equilibria information for an RnASnFC system; this tool is informally called MCS-PhaseEQ, and is described in a companion paper (Bohrson et al. 2020). The second stage of modeling, called MCS-Traces, calculates the RASFC evolution of up to 48 trace elements and seven radiogenic and one stable isotopic system (Sr, Nd, Hf, 3xPb, Os, and O) for the resident melt. In addition, trace element concentrations are calculated for bulk residual wallrock and each solid (± fluid) phase in the cumulate reservoir and residual wallrock. Input consists of (1) initial trace element concentrations and isotope ratios for the parental melt, wallrock, and recharge magmas/stoped wallrock blocks and (2) solid-melt and solid–fluid partition coefficients (optional temperature-dependence) for stable phases in the resident magma and residual wallrock. Output can be easily read and processed from tabulated worksheets. We provide trace element and isotopic results for the same example cases (FC, R2FC, AFC, S2FC, and R2AFC) presented in the companion paper. These simulations show that recharge processes can be difficult to recognize based on trace element data alone unless there is an independent reference frame of successive recharge events or if serial recharge magmas are sufficiently distinct in composition relative to the parental magma or magmas on the fractionation trend. In contrast, assimilation of wallrock is likely to have a notable effect on incompatible trace element and isotopic compositions of the contaminated resident melt. The magnitude of these effects depends on several factors incorporated into both stages of MCS calculations (e.g., phase equilibria, trace element partitioning, style of assimilation, and geochemistry of the starting materials). Significantly, the effects of assimilation can be counterintuitive and very different from simple scenarios (e.g., bulk mixing of magma and wallrock) that do not take account phase equilibria. Considerable caution should be practiced in ruling out potential assimilation scenarios in natural systems based upon simple geochemical “rules of thumb”. The lack of simplistic responses to open-system processes underscores the need for thermodynamical RASFC models that take into account mass and energy conservation. MCS-Traces provides an unprecedented and detailed framework for utilizing thermodynamic constraints and element partitioning to document trace element and isotopic evolution of igneous systems. Continued development of the Magma Chamber Simulator will focus on easier accessibility and additional capabilities that will allow the tool to better reproduce the documented natural complexities of open-system magmatic processes.Peer reviewe

    Apolipoprotein A–I binding to anionic vesicles and lipopolysaccharides: Role for lysine residues in antimicrobial properties

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    AbstractHuman apolipoprotein A–I (apoA–I) is a 28kDa protein and a major component of high-density lipoproteins, mediating several essential metabolic functions related to heart disease. In the present study the potential protective role against bacterial pathogens was explored. ApoA–I suppressed bacterial growth of Escherichia coli and Klebsiella pneumoniae. The protein was able to bind lipopolysaccharides and showed a strong preference for bilayer vesicles made of phosphatidylglycerol over phosphatidylcholine. Lysine side chains of apoA–I were acetylated to evaluate the importance of electrostatic forces in the binding interaction with both membrane components. Electrophoresis properties, dot blot analysis, circular dichroism, and fluorescence spectroscopy to probe for changes in protein structure indicated that the acetylated protein displayed a strongly reduced lipopolysaccharide and phosphatidylglycerol binding. A mutant containing only the N-terminal domain of apoA–I also showed a reduced ability to interact with the membrane components, although to a lesser extent. These results indicate the potential for apoA–I to function as an antimicrobial protein and exerts this function through lysine residues

    Report of the Pathogenesis and Pathophysiology of Lyme Disease Subcommittee of the HHS Tick Borne Disease Working Group

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    An understanding of the pathogenesis and pathophysiology of Lyme disease is key to the ultimate care of patients with Lyme disease. To better understand the various mechanisms underlying the infection caused by Borrelia burgdorferi, the Pathogenesis and Pathophysiology of Lyme Disease Subcommittee was formed to review what is currently known about the pathogenesis and pathophysiology of Lyme disease, from its inception, but also especially about its ability to persist in the host. To that end, the authors of this report were assembled to update our knowledge about the infectious process, identify the gaps that exist in our understanding of the process, and provide recommendations as to how to best approach solutions that could lead to a better means to manage patients with persistent Lyme disease
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