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274 Projects, page 1 of 55
  • Funder: European Commission Project Code: 625248
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  • Funder: European Commission Project Code: 329316
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  • Funder: European Commission Project Code: 628720
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  • Funder: European Commission Project Code: 273051
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  • Funder: European Commission Project Code: 898520
    Overall Budget: 246,669 EURFunder Contribution: 246,669 EUR

    When inspecting a visual scene, we make a succession of saccadic eye movements to analyze objects of interest with the high precision of the fovea. Each saccade drastically shifts the image on the retina. As the acuity of the fovea markedly decreases with eccentricity, to maintain a stable percept, the visual system needs to seamlessly integrate blurry peripheral representations with their high-resolution equivalents once brought into the fovea by the saccade. We hypothesize that this integration is achieved by predictive and selective tuning of feature sensitivity shortly before the eye movement, to assimilate pre and postsaccadic percept. Combining a new psychophysical protocol that enables a continuous assessment of visual sensitivity throughout the view field with a powerful reverse correlation approach, we will conduct a systematic investigation of human presaccadic orientation and frequency modulations across space and time. We will establish whether local feature information is predictively modulated shortly before a saccade to enable a stable, continuous perception across the eye movement, and contrast the observed presaccadic modulations to the dynamics elicited by the preparation of goal-directed hand movements. Furthermore, using transcranial magnetic stimulation (TMS) we will selectively disrupt the functioning of early and higher visual areas to reveal their temporal interplay and characterize their respective contribution to both presaccadic attention and covert attentional orienting in the absence of eye movements. Understanding how the human visual system seamlessly integrates foveal and peripheral feature representations is not only critical to further our understanding of healthy and impaired human perception, but also forms the basis for artificial vision. Our findings will help constrain computational models of perception and attention and could improve the design of safer human-machine interfaces, e.g. for driving and air traffic control.

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