ArticleJournal of vision2021
Biased orientation representations can be explained by experience with nonuniform training set statistics.
Article in Journal of vision, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Using Artificial Neural Networks to Relate External Sensory Features to Internal Decisional Evidence.Open mind : discoveries in cognitive science · 2026Article
- The world through infant eyes: Evidence for the early emergence of the cardinal orientation bias.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Recent, but not long-term, priors induce behavioral oscillations in peri-saccadic vision.Communications psychology · 2025Article
- How human-AI feedback loops alter human perceptual, emotional and social judgements.Nature human behaviour · 2025Article
- Adaptation optimizes sensory encoding for future stimuli.PLoS computational biology · 2025Article
- A gradual transition toward categorical representations along the visual hierarchy during working memory, but not perception.bioRxiv : the preprint server for biology · 2024Article
- A unifying framework for functional organization in early and higher ventral visual cortex.Neuron · 2024Article
- Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks.eLife · 2024Article
- A Unifying Principle for the Functional Organization of Visual Cortex.bioRxiv : the preprint server for biology · 2023Article
- Low-level tuning biases in higher visual cortex reflect the semantic informativeness of visual features.Journal of vision · 2023Article
- Efficient neural codes naturally emerge through gradient descent learning.Nature communications · 2022Article
- Natural scene sampling reveals reliable coarse-scale orientation tuning in human V1.Nature communications · 2022Article
- ImageNet-trained deep neural networks exhibit illusion-like response to the Scintillating grid.Journal of vision · 2021Article
- Artificial cognition: How experimental psychology can help generate explainable artificial intelligence.Psychonomic bulletin & review · 2021Review
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2 authors.
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Abstract
Visual acuity is better for vertical and horizontal compared to other orientations. This cross-species phenomenon is often explained by "efficient coding," whereby more neurons show sharper tuning for the orientations most common in natural vision. However, it is unclear if experience alone can account for such biases. Here, we measured orientation representations in a convolutional neural network, VGG-16, trained on modified versions of ImageNet (rotated by 0°, 22.5°, or 45° counterclockwise of upright). Discriminability for each model was highest near the orientations that were most common in the network's training set. Furthermore, there was an overrepresentation of narrowly tuned units selective for the most common orientations. These effects emerged in middle layers and increased with depth in the network, though this layer-wise pattern may depend on properties of the evaluation stimuli used. Biases emerged early in training, consistent with the possibility that nonuniform representations may play a functional role in the network's task performance. Together, our results suggest that biased orientation representations can emerge through experience with a nonuniform distribution of orientations, supporting the efficient coding hypothesis.
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