ArticleProceedings of the National Academy of Sciences of the United States of America2021
Oculo-retinal dynamics can explain the perception of minimal recognizable configurations.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Seeing on the fly: No need for space-to-time encoding; saccade-generated transients enable fast, parallel representation of space.Journal of vision · 2025Article
- Neural correlates of minimal recognizable configurations in the human brain.Cell reports · 2025Article
- The visual system does not operate like a camera.Journal of vision · 2025Article
- Thalamocortical loops as temporal demodulators across senses.Communications biology · 2023Review
- Harmonizing the object recognition strategies of deep neural networks with humans.Advances in neural information processing systems · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Natural vision is a dynamic and continuous process. Under natural conditions, visual object recognition typically involves continuous interactions between ocular motion and visual contrasts, resulting in dynamic retinal activations. In order to identify the dynamic variables that participate in this process and are relevant for image recognition, we used a set of images that are just above and below the human recognition threshold and whose recognition typically requires >2 s of viewing. We recorded eye movements of participants while attempting to recognize these images within trials lasting 3 s. We then assessed the activation dynamics of retinal ganglion cells resulting from ocular dynamics using a computational model. We found that while the saccadic rate was similar between recognized and unrecognized trials, the fixational ocular speed was significantly larger for unrecognized trials. Interestingly, however, retinal activation level was significantly lower during these unrecognized trials. We used retinal activation patterns and oculomotor parameters of each fixation to train a binary classifier, classifying recognized from unrecognized trials. Only retinal activation patterns could predict recognition, reaching 80% correct classifications on the fourth fixation (on average, ∼2.5 s from trial onset). We thus conclude that the information that is relevant for visual perception is embedded in the dynamic interactions between the oculomotor sequence and the image. Hence, our results suggest that ocular dynamics play an important role in recognition and that understanding the dynamics of retinal activation is crucial for understanding natural vision.
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