Human visual recognition is remarkably efficient. With just a single glance, we can identify our surroundings as a forest, a street, or an office, or determine whether a specific object contained in the scene is a deer, a car, or a computer. Uncovering the neural mechanisms underlying such fast and accurate recognition has been a core initiative in cognitive neuroscience, such that the structural and functional characteristics of object-selective and scene-selective cortex are now well understood. Yet there is a surprising and substantial gap in our understanding of the intermediate representational space between objects and scenes: One relevant level of visual organisation that has received very little attention to date is the 'object-constellation', defined here as a familiar configuration of objects bearing conceptual relevance to each other (e.g., a fork and knife arranged either side of a plate). Just as the visual system exploits physical regularities in Gestalt-like grouping, we hypothesise that the learned statistical regularities contained in object-constellations give rise to a higher-order perceptual unit, the neural basis of which has yet to be explored. This project will bring advanced neurocognitive methods to bear on the question of how the brain processes familiar object-constellations, using fMRI and MEG to characterise the spatiotemporal profile of object-constellation representation in the human brain. In providing the first systematic investigation of the neural representation of object-constellations, this work will shed new light on the statistical regularities the brain is specialised to exploit, and advance our understanding of the intermediary representational space between single-objects and whole-scenes.
Field of science
- /natural sciences/biological sciences/neurobiology/neuroscience/cognitive neuroscience
Call for proposal
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