This award supports the preparation and sharing of computational neuroscience data as part of an exploratory activity aimed at catalyzing rapid and innovative advances in computational neuroscience and related fields. The data to be shared in this project are single- and multi-unit recordings from primary visual cortex, obtained using either standard microelectrodes or micro-machined electrode arrays. Both spontaneous and stimulus driven activity are available in a number of different conditions, including standard receptive field characterizations (e.g., orientation tuning, spatial and temporal frequency tuning) and more specific experiments such as sub-space receptive field mapping and natural image sequences. Data from micro-machined electrode arrays also include local field potentials and surface EEG. It is anticipated that these data will be useful for studies of visual processing, population coding, and retinotopy, and that the large-scale high-dimensional data will be well suited for exploration by novel machine learning and statistical methods.