Objective
Visual cognition is our ability to recognize the things we see around us and make inferences about their meaning and
relationships. Deep convolutional neuronal network (CNN) models now achieve human-level performance on certain visual
recognition tasks and currently provide the most powerful models of human visual cognition. A hallmark step in the
development of human visual cognition is the acquisition of object permanence (OP). Object permanence is the ability to
continue to mentally represent an object that has disappeared from view – for example because it is hidden behind another
object. Current deep neural network models of vision lack this fundamental ability, limiting their power as models of human
visual cognition and as artificially intelligent systems. In this action, I will study the computational mechanisms necessary for
OP 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 task
involves viewing a scene of moving objects that occasionally become occluded behind other objects. Models will be trained
to 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 Muckli
at University of Glasgow are world-leading experts on deep neural network models of vision and cortical-layer-resolved highfield
fMRI, respectively. The outcome of this action, a biologically plausible deep recurrent convolutional model that can
explain behavior and brain activity, will significantly enhance our understanding of the computational principles of visual
cognition, with implications also for AI technology.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology medical engineering diagnostic imaging magnetic resonance imaging
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2018
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
G12 8QQ Glasgow
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.