News Finding: "Frankly, the BOLD5000 dataset is still way too small," Tarr said, suggesting that a reasonable fMRI dataset would require at least 50,000 stimulus images and many more volunteers to make headway in light of the fact that the class of deep neural nets used to analyze visual imagery are trained on millions of images.
Paper Finding: Critically, the human neuroimaging data available in BOLD5000 is: 1) significantly larger than prior slow event-related fMRI datasets by an order of magnitude; 2) extremely diverse in stimuli; 3) overlaps considerably with standard computer vision datasets.
News Context: The group views BOLD5000 as only the first step toward leveraging modern computer vision models to study biological vision. "Frankly, the BOLD5000 dataset is still way too small," Tarr said, suggesting that a reasonable fMRI dataset would require at least 50,000 stimulus images and many more volunteers to make headway in light of the fact that the class of deep neural nets used to analyze visual imagery are trained on millions of images. To this end, the research team hopes their ability to generate a dataset of 5,000 brain scans will pave the way for larger collaborative efforts between human vision and computer vision scientists.
Paper Context: Marr's nearly four-decades-old dream of a singular vision science -the intertwined study of biological and computer vision -is, at long last, being realized. Critically, the human neuroimaging data available in BOLD5000 is: 1) significantly larger than prior slow event-related fMRI datasets by an order of magnitude; 2) extremely diverse in stimuli; 3) overlaps considerably with standard computer vision datasets. At the same time, BOLD5000 represents a significant dataset for the study of human vision in and of itself.