To address the first objective of identifying the core dimensions underlying our neural representation of objects, we have collected a large-scale representatively sampled dataset of brain responses to natural images, tailored to capture the breadth of our visual experiences. Specifically, we have first developed a sampling strategy that has allowed for broad coverage of the space of natural stimuli, distilling around 30.000 natural images to be representative of a set of 120 million natural photographs. Using a smaller dataset, we have already successfully identified the brain responses related to core object dimensions derived from behavior. Building on this work, we have used advanced brain imaging technique (7 Tesla functional and structural MRI, 3 Tesla Connectom MRI) to collect data from over 40 neuroimaging sessions per participant, providing the deepest sampling not only of retinotopic responses, anatomical and structural connectivity, but also functional responses to thousands of natural images. Our next step is to apply computational modeling to this data to reveal core dimensions underlying human neural representation of objects. Together, this promises a much deeper understanding of how our brain allows us to interpret the visual world.
The second objective of COREDIM is to distinguish the role of visual perception and semantic knowledge in our object representations. To address this, we have used innovative experimental designs using speeded similarity judgments. In a first step, we have compared different similarity tasks to each other, identifying the unique and shared aspects of mental representations measured by these tasks. In the next step, we will use speeded similarity judgments in a visual search task. This will identify core dimensions underlying fast representations which also serve as the basis for visual search without a predefined target. We will further use unrecognizable images to distinguish the impact of visual dimensions from the semantic knowledge we have about objects. In addition, this part of the project involves comparing human visual processing with that of non-human primates who lack the same level of semantic knowledge, where we have identified both commonalities and differences in their visual processing strategies. Together, this work promises a much better understanding of how strongly our object processing relies on vision alone as compared to our object knowledge.
