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      Training improves visual processing speed and generalizes to untrained functions

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Studies show that manipulating certain training features in perceptual learning determines the specificity of the improvement. The improvement in abnormal visual processing following training and its generalization to visual acuity, as measured on static clinical charts, can be explained by improved sensitivity or processing speed. Crowding, the inability to recognize objects in a clutter, fundamentally limits conscious visual perception. Although it was largely considered absent in the fovea, earlier studies report foveal crowding upon very brief exposures or following spatial manipulations. Here we used GlassesOff's application for iDevices to train foveal vision of young participants. The training was performed at reading distance based on contrast detection tasks under different spatial and temporal constraints using Gabor patches aimed at testing improvement of processing speed. We found several significant improvements in spatio-temporal visual functions including near and also non-trained far distances. A remarkable transfer to visual acuity measured under crowded conditions resulted in reduced processing time of 81 ms, in order to achieve 6/6 acuity. Despite a subtle change in contrast sensitivity, a robust increase in processing speed was found. Thus, enhanced processing speed may lead to overcoming foveal crowding and might be the enabling factor for generalization to other visual functions.

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          Most cited references 100

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          Speed of processing in the human visual system.

          How long does it take for the human visual system to process a complex natural image? Subjectively, recognition of familiar objects and scenes appears to be virtually instantaneous, but measuring this processing time experimentally has proved difficult. Behavioural measures such as reaction times can be used, but these include not only visual processing but also the time required for response execution. However, event-related potentials (ERPs) can sometimes reveal signs of neural processing well before the motor output. Here we use a go/no-go categorization task in which subjects have to decide whether a previously unseen photograph, flashed on for just 20 ms, contains an animal. ERP analysis revealed a frontal negativity specific to no-go trials that develops roughly 150 ms after stimulus onset. We conclude that the visual processing needed to perform this highly demanding task can be achieved in under 150 ms.
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            The role of phase synchronization in memory processes.

            In recent years, studies ranging from single-unit recordings in animals to electroencephalography and magnetoencephalography studies in humans have demonstrated the pivotal role of phase synchronization in memory processes. Phase synchronization - here referring to the synchronization of oscillatory phases between different brain regions - supports both working memory and long-term memory and acts by facilitating neural communication and by promoting neural plasticity. There is evidence that processes underlying working and long-term memory might interact in the medial temporal lobe. We propose that this is accomplished by neural operations involving phase-phase and phase-amplitude synchronization. A deeper understanding of how phase synchronization supports the flexibility of and interaction between memory systems may yield new insights into the functions of phase synchronization in general.
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              Crowding--an essential bottleneck for object recognition: a mini-review.

              Crowding, generally defined as the deleterious influence of nearby contours on visual discrimination, is ubiquitous in spatial vision. Crowding impairs the ability to recognize objects in clutter. It has been extensively studied over the last 80 years or so, and much of the renewed interest is the hope that studying crowding may lead to a better understanding of the processes involved in object recognition. Crowding also has important clinical implications for patients with macular degeneration, amblyopia and dyslexia. There is no shortage of theories for crowding-from low-level receptive field models to high-level attention. The current picture is that crowding represents an essential bottleneck for object perception, impairing object perception in peripheral, amblyopic and possibly developing vision. Crowding is neither masking nor surround suppression. We can localize crowding to the cortex, perhaps as early as V1; however, there is a growing consensus for a two-stage model of crowding in which the first stage involves the detection of simple features (perhaps in V1), and a second stage is required for the integration or interpretation of the features as an object beyond V1. There is evidence for top-down effects in crowding, but the role of attention in this process remains unclear. The strong effect of learning in shrinking the spatial extent of crowding places strong constraints on possible models for crowding and for object recognition. The goal of this review is to try to provide a broad, balanced and succinct review that organizes and summarizes the diverse and scattered studies of crowding, and also helps to explain it to the non-specialist. A full understanding of crowding may allow us to understand this bottleneck to object recognition and the rules that govern the integration of features into objects.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                28 November 2014
                2014
                : 4
                Affiliations
                [1 ]Faculty of Medicine, Goldschleger Eye Research Institute, Tel Aviv University , Israel
                [2 ]Visual Perception Laboratory, Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin , Germany
                [3 ]Department of Psychology , Humboldt-Universität zu Berlin, Germany
                [4 ]UCL Institute of Cognitive Neuroscience , London, UK
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep07251
                10.1038/srep07251
                4246693
                25431233
                Copyright © 2014, Macmillan Publishers Limited. All rights reserved

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

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