TY - JOUR T1 - A massive 7T fMRI dataset to bridge cognitive and computational neuroscience JF - bioRxiv DO - 10.1101/2021.02.22.432340 SP - 2021.02.22.432340 AU - Emily J. Allen AU - Ghislain St-Yves AU - Yihan Wu AU - Jesse L. Breedlove AU - Logan T. Dowdle AU - Brad Caron AU - Franco Pestilli AU - Ian Charest AU - J. Benjamin Hutchinson AU - Thomas Naselaris AU - Kendrick Kay Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/02/22/2021.02.22.432340.abstract N2 - Extensive sampling of neural activity during rich cognitive phenomena is critical for robust understanding of brain function. We present the Natural Scenes Dataset (NSD), in which high-resolution fMRI responses to tens of thousands of richly annotated natural scenes are measured while participants perform a continuous recognition task. To optimize data quality, we develop and apply novel estimation and denoising techniques. Simple visual inspections of the NSD data reveal clear representational transformations along the ventral visual pathway. Further exemplifying the inferential power of the dataset, we use NSD to build and train deep neural network models that predict brain activity more accurately than state-of-the-art models from computer vision. NSD also includes substantial resting-state and diffusion data, enabling network neuroscience perspectives to constrain and enhance models of perception and memory. Given its unprecedented scale, quality, and breadth, NSD opens new avenues of inquiry in cognitive and computational neuroscience.Competing Interest StatementThe authors have declared no competing interest. ER -