Research
Overview
The role of real-world statistics in the representation of scene parts and objects
Projects
Perceiving natural environments is a challenging task for the human visual system. Almost any natural scene, such as our workplace or living room, contains dozens of separable objects that need to be perceived simultaneously. This research project focuses on how the natural scene structure contributes to efficient scene and object perception. A key question therein concerns how the typical arrangements of objects across a scene (e.g., the typical arrangement of objects across our office workspace) allows the visual system to represent multiple simultaneous objects in smart ways.
To answer this question, the project will use a variety of research methods, including experimental psychophysics, EEG recordings, fMRI-based neuroimaging, and deep neural network modeling. By combining these methods, it aims at a multi-faceted characterization of how the visual brain represents visual content, such as objects and scenes in accordance with real-world statistic
Collaborators
Publications
Selected publications
Pavan, A., Contillo, A., Ghin, F., Foxwell, M. J., & Mather, G. (2019). Limited Attention Diminishes Spatial Suppression From Large Field Glass Patterns. Perception, 48(4), 286-315. https://journals.sagepub.com/doi/full/10.1177/0301006619835457
