318 research outputs found

    Time dilation in dynamic visual display

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    How does the brain estimate time? This old question has led to many biological and psychological models of time perception (R. A. Block, 1989; P. Fraisse, 1963; J. Gibbon, 1977; D. L. I. Zakay, 1989). Because time cannot be directly measured at a given moment, it has been proposed that the brain estimates time based on the number of changes in an event (S. W. Brown, 1995; P. Fraisse, 1963; W. D. Poynter, 1989). Consistent with this idea, dynamic visual stimuli are known to lengthen perceived time (J. F. Brown, 1931; S. Goldstone & W. T. Lhamon, 1974; W. T. Lhamon & S. Goldstone, 1974, C. O. Z. Roelofs & W. P. C. Zeeman, 1951). However, the kind of information that constitutes the basis for time perception remains unresolved. Here, we show that the temporal frequency of a stimulus serves as the “clock” for perceived duration. Other aspects of changes, such as speed or coherence, were found to be inconsequential. Time dilation saturated at a temporal frequency of 4–8 Hz. These results suggest that the clock governing perceived time has its basis at early processing stages. The possible links between models of time perception and neurophysiological functions of early visual areas are discussed

    Predictive coding of visual motion in both monocular and binocular human visual processing

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    Neural processing of sensory input in the brain takes time, and for that reason our awareness of visual events lags behind their actual occurrence. One way the brain might compensate to minimize the impact of the resulting delays is through extrapolation. Extrapolation mechanisms have been argued to underlie perceptual illusions in which moving and static stimuli are mislocalised relative to one another (such as the flash-lag and related effects). However, where in the visual hierarchy such extrapolation processes take place remains unknown. Here, we address this question by identifying monocular and binocular contributions to the flash-grab illusion. In this illusion, a brief target is flashed on a moving background that reverses direction. As a result, the perceived position of the target is shifted in the direction of the reversal. We show that the illusion is attenuated, but not eliminated, when the motion reversal and the target are presented dichoptically to separate eyes. This reveals extrapolation mechanisms at both monocular and binocular processing stages contribute to the illusion. We interpret the results in a hierarchical predictive coding framework, and argue that prediction errors in this framework manifest directly as perceptual illusions

    Presence of osteoclast-like multinucleated giant cells in the bone and nonostotic lesions of Langerhans cell histiocytosis

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    Langerhans cell histiocytosis (LCH) is a disease that can involve one or multiple organ systems characterized by an accumulation of CD1a+ Langerhans-like cells as well as several other myeloid cell types. The precise origin and role of one of these populations, the multinucleated giant cell (MGC), in this disease remains unknown. This work shows that in three different lesional tissues, bone, skin, and lymph node, the MGCs expressed the characteristic osteoclast markers, tartrate-resistant acid phosphatase and vitronectin receptor, as well as the enzymes cathepsin K and matrix metalloproteinase-9. Although, in bone lesions, the osteoclast-like MGCs were only CD68+, in the nonostotic sites, they coexpressed CD1a. The presence of osteoclast-like MGCs may be explained by the production of osteoclast-inducing cytokines such as receptor activator of nuclear factor ÎşB ligand and macrophage colony-stimulating factor by both the CD1a+ LCH cells and T cells in these lesions. As osteoclast-derived enzymes play a major role in tissue destruction, the osteoclast-like nature of MGCs in all LCH lesions makes them a potential target for the treatment of this disease

    OER Metadata Rosetta Stone

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    This document is the technical specification of core and contextual elements for Open Educational Resources using existing schema to create a Metadata Application Profile. It provides a list of relevant classes and properties used in OER metadata records at the institutional and repository level. It is our hope that this document will support best practices for OER repositories and institutions to leverage existing library expertise and networks
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