Light falling on the retina triggers neural activity that is propagated along sub-cortical and cortical pathways to ultimately elicit the perceptual experience of a world that is full of people, places, and things. However, much prior research has focused on broad visual distinctions (e.g. scenes, objects) and the task of recognition or classification. Here, I will argue that we need to move beyond notions of so-called ‘category selectivity’ and consider the range of behaviors that are supported by processing in high-level visual cortex. In particular, I will focus on recent work in which we developed a data-driven computational approach to identify the core dimensions underlying our mental representations of objects.
Using a large-scale database of images from over 1500 object concepts and behavioral responses across nearly 1.5 million trials, we find that human behavioral judgments can be captured by 49 highly reproducible and meaningful object dimensions that reflect various conceptual and perceptual properties of those objects. MEG and fMRI data reveal the spatiotemporal neural dynamics associated with the processing of these dimensions. Collectively, this work highlights an alternative framework for understanding how we make sense of the visual world.