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Computer Science > Neural and Evolutionary Computing

arXiv:1809.02440 (cs)
[Submitted on 7 Sep 2018]

Title:Optimizing deep video representation to match brain activity

Authors:Hugo Richard (PARIETAL), Ana Pinho (NEUROSPIN), Bertrand Thirion (PARIETAL), Guillaume Charpiat (TAU)
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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.
Subjects: Neural and Evolutionary Computing (cs.NE); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Neurons and Cognition (q-bio.NC)
Cite as: arXiv:1809.02440 [cs.NE]
  (or arXiv:1809.02440v1 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.1809.02440
Journal reference: 2018 Conference on Cognitive Computational Neuroscience, Sep 2018, Philadelphia, United States

Submission history

From: Hugo Richard [view email] [via CCSD proxy]
[v1] Fri, 7 Sep 2018 12:37:50 UTC (6,410 KB)
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