Optimizing deep video representation to match brain activity

September 07, 2018 ยท Declared Dead ยท ๐Ÿ› 2018 Conference on Cognitive Computational Neuroscience

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Authors Hugo Richard, Ana Pinho, Bertrand Thirion, Guillaume Charpiat arXiv ID 1809.02440 Category cs.NE: Neural & Evolutionary Cross-listed cs.CV, cs.LG, q-bio.NC Citations 5 Venue 2018 Conference on Cognitive Computational Neuroscience Last Checked 4 months ago
Abstract
The comparison of observed brain activity with the statistics generated by artificial intelligence systems is useful to probe brain functional organization under ecological conditions. Here we study fMRI activity in ten subjects watching color natural movies and compute deep representations of these movies with an architecture that relies on optical flow and image content. The association of activity in visual areas with the different layers of the deep architecture displays complexity-related contrasts across visual areas and reveals a striking foveal/peripheral dichotomy.
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