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What comparing deep neural networks can teach us about human vision

Nature Machine Intelligence volume 6, pages 122–123 (2024)Cite this article

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Recent work has demonstrated important parallels between human visual representations and those found in deep neural networks. A new study comparing functional MRI data to deep neural network models highlights factors that may determine this similarity.

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Fig. 1: Image processing by neural network models and resulting brain maps.

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Authors and Affiliations

  1. Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

    Katja Seeliger & Martin N. Hebart

  2. Department of Medicine, Justus Liebig University, Giessen, Germany

    Martin N. Hebart

Authors
  1. Katja Seeliger
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  2. Martin N. Hebart
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Correspondence to Martin N. Hebart.

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The authors declare no competing interests.

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Seeliger, K., Hebart, M.N. What comparing deep neural networks can teach us about human vision. Nat Mach Intell 6, 122–123 (2024). https://doi.org/10.1038/s42256-024-00789-8

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