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The left clip is a segment of a Hollywood movie trailer that the subject viewed while in the magnet. The right clip shows the reconstruction of this segment from brain activity measured using fMRI. The procedure is as follows: [1] Record brain activity while the subject watches several hours of movie trailers. [2] Build dictionaries (i.e., regression models) that translate between the shapes, edges and motion in the movies and measured brain activity. A separate dictionary is constructed for each of several thousand points at which brain activity was measured. (For experts: The real advance of this study was the construction of a movie-to-brain activity encoding model that accurately predicts brain activity evoked by arbitrary novel movies.) [3] Record brain activity to a new set of movie trailers that will be used to test the quality of the dictionaries and reconstructions. [4] Build a random library of ~18,000,000 seconds (5000 hours) of video downloaded at random from YouTube. (Note these videos have no overlap with the movies that subjects saw in the magnet). Put each of these clips through the dictionaries to generate predictions of brain activity. Select the 100 clips whose predicted activity is most similar to the observed brain activity. Average these clips together. This is reconstruction.
