BOLD5000 ...

Brain, Object, Landscape Dataset Vision science - particularly machine vision - is being revolutionized by large-scale datasets. State-of-the-art artificial vision models critically depend on large-scale datasets to achieve high performance. In contrast, although large-scale learning models (e.g., AlexNet) have been applied to human neuroimaging data, the stimuli for such neuroimaging experiments include significantly fewer images. The small size of these stimulus sets also translates to limited image diversity. Here we dramatically increase the stimulus set size deployed in an fMRI study of visual scene processing. We scanned four participants in a slow-evented related design that incorporated 4,916 unique scenes. Data was collected over 16 sessions, 15 of which were task-related sessions, plus an additional session for acquiring high resolution anatomical scans. In 8 of the 15 task-related sessions, a functional localizer was run in order to independently define scene-selective cortex. In each scanning ...