English

Optimizing deep video representation to match brain activity

Neural and Evolutionary Computing 2018-09-10 v1 Computer Vision and Pattern Recognition Machine Learning Neurons and Cognition

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.

Keywords

Cite

@article{arxiv.1809.02440,
  title  = {Optimizing deep video representation to match brain activity},
  author = {Hugo Richard and Ana Pinho and Bertrand Thirion and Guillaume Charpiat},
  journal= {arXiv preprint arXiv:1809.02440},
  year   = {2018}
}
R2 v1 2026-06-23T03:57:53.613Z