Optimizing deep video representation to match brain activity
September 07, 2018 ยท Declared Dead ยท ๐ 2018 Conference on Cognitive Computational Neuroscience
"No code URL or promise found in abstract"
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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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