Objective Visual cognition is our ability to recognize the things we see around us and make inferences about their meaning andrelationships. Deep convolutional neuronal network (CNN) models now achieve human-level performance on certain visualrecognition tasks and currently provide the most powerful models of human visual cognition. A hallmark step in thedevelopment of human visual cognition is the acquisition of object permanence (OP). Object permanence is the ability tocontinue to mentally represent an object that has disappeared from view – for example because it is hidden behind anotherobject. Current deep neural network models of vision lack this fundamental ability, limiting their power as models of humanvisual cognition and as artificially intelligent systems. In this action, I will study the computational mechanisms necessary forOP using a highly innovative approach that combines four elements: (1) a novel behavioral task that requires OP, (2)development of a deep recurrent neural network models, (3) testing of both human participants and models at the task, and(4) measurement of brain activity with functional magnetic resonance imaging (fMRI) during task performance. The OP taskinvolves viewing a scene of moving objects that occasionally become occluded behind other objects. Models will be trainedto represent objects continually, even as they vanish behind an occluder, and selected to match behavioral and cortical-layer-resolved high-field fMRI data of human observers. The hosts, Prof Kriegeskorte at Columbia University and Prof Muckliat University of Glasgow are world-leading experts on deep neural network models of vision and cortical-layer-resolved highfieldfMRI, respectively. The outcome of this action, a biologically plausible deep recurrent convolutional model that canexplain behavior and brain activity, will significantly enhance our understanding of the computational principles of visualcognition, with implications also for AI technology. Fields of science engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imagingnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2018 - Individual Fellowships Call for proposal H2020-MSCA-IF-2018 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator UNIVERSITY OF GLASGOW Net EU contribution € 271 732,80 Address University avenue G12 8QQ Glasgow United Kingdom See on map Region Scotland West Central Scotland Glasgow City Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Partners (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all Partner Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement. TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK United States Net EU contribution € 0,00 Address Amsterdam avenue 1210 room 10027 7003 New york See on map Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 165 265,92
