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Object perception is inherently multidimensional: information about color, material, texture and shape all guide how we interact with objects. We developed a paradigm that quantifies how two object properties (color and material) combine in object selection. On each experimental trial, observers viewed three blob-shaped objects-the target and two tests-and selected the test that was more similar to the target. Across trials, the target object was fixed, while the tests varied in color (across 7 levels) and material (also 7 levels, yielding 49 possible stimuli). We used an adaptive trial selection procedure (Quest+) to present, on each trial, the stimulus test pair that is most informative of underlying processes that drive selection. We present a novel computational model that allows us to describe observers' selection data in terms of (1) the underlying perceptual stimulus representation and (2) a color-material weight, which quantifies the relative importance of color vs. material in selection. We document large individual differences in the color-material weight across the 12 observers we tested. Furthermore, our analyses reveal limits on how precisely selection data simultaneously constrain perceptual representations and the color-material weight. These limits should guide future efforts towards understanding the multidimensional nature of object perception.

Perceived object color and material help us to select and interact with objects. Because there is no simple mapping between the pattern of an object’s image on the retina and its physical reflectance, our perceptions of color and material are the result of sophisticated visual computations. A long-standing goal in vision science is to describe how these computations work, particularly as they act to stabilize perceived color and material against variation in scene factors extrinsic to object surface properties, such as the illumination. If we take seriously the notion that perceived color and material are useful because they help guide behavior in natural tasks, then we need experiments that measure and models that describe how they are used in such tasks. To this end, we have developed selection-based methods and accompanying perceptual models for studying perceived object color and material. This focused review highlights key aspects of our work. It includes a discussion of future directions and challenges, as well as an outline of a computational observer model that incorporates early, known, stages of visual processing and that clarifies how early vision shapes selection performance. Perceived object color and material help us to select and interact with objects. There is no simple mapping between the pattern of an object’s image on the retina and its physical reflectance; our perceptions of color and material are the result of sophisticated visual computations. A long-standing goal in vision science is to describe how these computations work. We have developed selection-based methods and accompanying perceptual models for studying perceived object color and material. This focused review highlights key aspects of our work and includes a discussion of future directions and challenges.

Information about color, material, texture and shape guide how we interact with objects. We developed a paradigm that quantifies how two object properties (color and material) combine in object selection. On each experimental trial, observers viewed three blob-shaped objects - the target and two tests - and selected the test that was more similar to the target. Across trials the target was fixed while the tests varied in color and material. We present a novel observer model that allows us to describe observers selection data in terms of (1) the underlying perceptual stimulus representation and (2) a color-material weight, which quantifies the relative importance of color vs. material in selection. We document large individual differences in the color-material weight. Furthermore, our analyses reveal limits on how precisely selection data simultaneously constrain perceptual representations and the color-material weight. These limits should guide future efforts towards understanding the multidimensional nature of object perception.

According to the coplanar ratio principle (CRP), when the luminance range in the image is larger than 30:1 the lightness of a target surface depends on the luminance ratio between that target and its adjacent, coplanar neighbor. This conclusion was based on experiments (Gilchrist, 1977) using a dihedral corner display in which a change in the perceived spatial position of a target produced large changes in its perceived lightness, with no significant change in the observer’s retinal image. Using variations of this dihedral display, a series of experiments was conducted to test a group of conflicting claims made by CRP, the anchoring theory (Gilchrist et al., 1999) and other writers (e.g. Kardos, 1934, Howe, 2006) concerning the role of coplanarity, adjacency, surroundedness, articulation, and luminance range. Generally consistent with the predictions of the anchoring theory, the results show the following: (1) Articulation can substantially increase the depth effect. (2) Target lightness depends, not simply on its adjacent coplanar luminance, but on the highest luminance in its plane, irrespective of its position relative to the target. (3) When two or more levels of illumination are present on a plane, target lightness depends on the highest luminance in its framework of illumination, not on the highest luminance in its plane. (4) The size of the depth effect depends on the luminance ratio between the highest luminance values in the two planes, not on the overall luminance range across the planes. Thus strong depth effects can be obtained with a luminance range no greater than 30:1. (5) Surface continuity within a plane is necessary for the operation of coplanar ratios, although surroundedness can partially substitute for continuity, but only within the brightly illuminated plane.

The spectral properties of the ambient illumination provide useful information about time of day and weather. We study the perceptual representation of illumination by analyzing measurements of how well people discriminate between illuminations across scene configurations. More specifically, we compare human performance to a computational-observer analysis that evaluates the information available in the isomerizations of the cones in a model human photoreceptor mosaic. Some patterns of human performance are predicted by the computational observer, other aspects are not. The analysis clarifies which aspects of performance require additional explanation in terms of the action of visual mechanisms beyond the isomerization of light by the cones.

Perceived object color and material help us to select and interact with objects. Because there is no simple mapping between the pattern of an objects image on the retina and its physical reflectance, our perceptions of color and material are the result of sophisticated visual computations. A long-standing goal in vision science is to describe how these computations work, particularly as they act to stabilize perceived color and material against variation in scene factors extrinsic to object surface properties, such as the illumination. If we take seriously the notion that perceived color and material are useful because they help guide behavior in natural tasks, then we need experiments that measure and models that describe how they are used in such tasks. To this end, we have developed selection-based methods and accompanying perceptual models for studying perceived object color and material. This focused review highlights key aspects of our work. It includes a discussion of future directions and challenges, as well as an outline of a computational observer model that incorporates early, known, stages of visual processing and that clarifies how early vision shapes selection performance. Footnotes * Minor clarifications to text, fixed some typos, sharpened discussionl

A comprehensive review of contemporary research in the vision sciences, reflecting the rapid advances of recent years.Visual science is the model system for neuroscience, its findings relevant to all other areas. This essential reference to contemporary visual neuroscience covers the extraordinary range of the field today, from molecules and cell assemblies to systems and therapies. It provides a state-of-the art companion to the earlier book The Visual Neurosciences (MIT Press, 2003). This volume covers the dramatic advances made in the last decade, offering new topics, new authors, and new chapters. The New Visual Neurosciences assembles groundbreaking research, written by international authorities. Many of the 112 chapters treat seminal topics not included in the earlier book. These new topics include retinal feature detection; cortical connectomics; new approaches to mid-level vision and spatiotemporal perception; the latest understanding of how multimodal integration contributes to visual perception; new theoretical work on the role of neural oscillations in information processing; and new molecular and genetic techniques for understanding visual system development. An entirely new section covers invertebrate vision, reflecting the importance of this research in understanding fundamental principles of visual processing. Another new section treats translational visual neuroscience, covering recent progress in novel treatment modalities for optic nerve disorders, macular degeneration, and retinal cell replacement. The New Visual Neurosciences is an indispensable reference for students, teachers, researchers, clinicians, and anyone interested in contemporary neuroscience.Associate EditorsMarie Burns, Joy Geng, Mark Goldman, James Handa, Andrew Ishida, George R. Mangun, Kimberley McAllister, Bruno Olshausen, Gregg Recanzone, Mandyam Srinivasan, W.Martin Usrey, Michael Webster, David WhitneySectionsRetinal Mechanisms and ProcessesOrganization of Visual PathwaysSubcortical ProcessingProcessing in Primary Visual CortexBrightness and ColorPattern, Surface, and ShapeObjects and ScenesTime, Motion, and DepthEye MovementsCortical Mechanisms of Attention, Cognition, and Multimodal IntegrationInvertebrate VisionTheoretical PerspectivesMolecular and Developmental ProcessesTranslational Visual Neuroscience

Free radicals are implicated in the aetiology of gastrointestinal disorders such as gastric ulcer, colorectal cancer and inflammatory bowel disease. Strawberries are common and important fruit due to their high content of essential nutrient and beneficial phytochemicals which seem to have relevant biological activity on human health. In the present study we investigated the antioxidant and protective effects of three strawberry extracts against ethanol-induced gastric mucosa damage in an experimental in vivo model and to test whether strawberry extracts affect antioxidant enzyme activities in gastric mucosa. Strawberry extracts were obtained from Adria, Sveva and Alba cultivars. Total antioxidant capacity and radical scavenging capacity were performed by TEAC, ORAC and electron paramagnetic resonance assays. Identification and quantification of anthocyanins was carried out by HPLC-DAD-MS analyses. Different groups of animals received 40 mg/day/kg body weight of strawberry crude extracts for 10 days. Gastric damage was induced by ethanol. The ulcer index was calculated together with the determination of catalase and SOD activities and MDA contents. Strawberry extracts are rich in anthocyanins and present important antioxidant capacity. Ethanol caused severe gastric damage and strawberry consumption protected against its deleterious role. Antioxidant enzyme activities increased significantly after strawberry extract intake and a concomitantly decrease in gastric lipid peroxidation was found. A significant correlation between total anthocyanin content and percent of inhibition of ulcer index was also found. Strawberry extracts prevented exogenous ethanol-induced damage to rats' gastric mucosa. These effects seem to be associated with the antioxidant activity and phenolic content in the extract as well as with the capacity of promoting the action of antioxidant enzymes. A diet rich in strawberries might exert a beneficial effect in the prevention of gastric diseases related to generation of reactive oxygen species.

The aim of this study was to investigate the role of peripheral blood markers as additional diagnostic tools to transvaginal ultrasound (TVU) findings in the diagnosis of endometriosis. This study included 40 patients undergoing laparoscopy for suspected endometriosis from January to December 2012. Preoperative levels of serum CA125, CA19-9, CEA and mRNA expression levels for survivin and VEGF were obtained. Real-time PCR was used to determine relative gene expression. A new diagnostic score was obtained by deploying the peripheral blood markers to the TVU findings. Statistical methods used were Chi-square, Fisher's, Student's t-test or the Mann - Whitney test. There was a statistically significant difference in serum CA125, survivin and VEGF levels in patients with endometriosis and those without endometriosis (p<0.001, p=0.025 and p=0.009, respectively). False negative TVU findings were noted in 3/13 patients (23.1%) with peritoneal endometriosis without ovaries involvement. High sensitivity (93.3%), specificity (90.0%), PPV (96.6%), NPV (81.8%) and accuracy (92.5%) were obtained for a diagnostic score based on TVU and significant peripheral blood markers (CA125, survivin and VEGF). Determination of serum CA125, mRNA expression levels for survivin and VEGF along with TVU can contribute to higher accuracy of the noninvasive diagnostic tools for endometriosis.

Surveillance of antimicrobial medicines consumption is central to improving their use and reducing resistance rates. There are few published data on antibiotic consumption in Eastern Europe and Central Asia. To address this, 18 non-European Union (EU) countries and territories contribute to the WHO Regional Office for Europe (WHO Europe) Antimicrobial Medicines Consumption (AMC) Network. (i) Analyze 2015 consumption of J01 class antibacterials for systemic use from 16 AMC Network members; (ii) compare results with 2011 data and 2015 ESAC-Net estimates; (iii) assess consumption against suggested indicators; (iv) evaluate the impact of planned changes to defined daily doses (DDDs) in 2019 for some commonly used antibiotics; and (v) consider the utility of quantitative metrics of consumption for policy action. Analysis methods are similar to ESAC-Net for EU countries. The Anatomical Therapeutic Chemical (ATC) classification and DDD methodology were used to calculate total consumption (DDD/1000 inhabitants/day [DID]), relative use measures (percentages), extent of use of WHO Watch and Reserve group antibiotics and impact of DDD changes. Total J01 consumption in 2015 ranged 8.0-41.5 DID (mean 21.2 DID), generally lower than in 2011 (6.4-42.3 DID, mean 23.6 DID). Beta-lactam penicillins, cephalosporins, and quinolones represented 16.2-56.6, 9.4-28.8, and 7.5-24.6% of total J01 consumption, respectively. Third-generation cephalosporins comprised up to 90% of total cephalosporin consumption in some countries. Consumption of WHO Reserve antibiotics was very low; Watch antibiotics comprised 17.3-49.5% of total consumption (mean 30.9%). Variability was similar to 2015 ESAC-Net data (11.7-38.3 DID; mean 22.6 DID). DDD changes in 2019 impact both total and relative consumption estimates: total DIDs reduced on average by 12.0% (7.3-35.5 DID), mostly due to reduced total DDDs for commonly used penicillins; impact on rankings and relative use estimates were modest. Quantitative metrics of antibiotic consumption have value. Improvements over time reflect national activities, however, changes in total volumes may conceal shifts to less desirable choices. Relative use measures targeting antibiotics of concern may be more informative. Some, including WHO Watch and Reserve classifications, lend themselves to prescribing targets supported by guidelines and treatment protocols.