ArticleDevelopmental science2022
Linking patterns of infant eye movements to a neural network model of the ventral stream using representational similarity analysis.
Article in Developmental science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 28 citations in OpenAlex.
- Conceptual priors drive development of predictive attention to emotion.Child development · 2026Article
- A population vector model of visual working memory for real-world scenes.Journal of experimental psychology. General · 2026Article
- Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026Review
- A Population Vector Model of Visual Working Memory for Real-World Scenes.bioRxiv : the preprint server for biology · 2026Article
- What have we learned about infant visual attention in the first 25 years of the 21st century?Infant behavior & development · 2025Review
- Relating Infant Fixations to Adult Cortical Activation Patterns Using the Natural Scenes Dataset.Developmental science · 2025Article
- Fast and robust visual object recognition in young children.Science advances · 2025Article
- Perceptual Expertise and Attention: An Exploration using Deep Neural Networks.bioRxiv : the preprint server for biology · 2024Article
- A new perspective on the role of physical salience in visual search: Graded effect of salience on infants' attention.Developmental psychology · 2023Article
- Perception of an object's global shape is best described by a model of skeletal structure in human infants.eLife · 2022Article
- Visual object categorization in infancy.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Rapid Extraction of the Spatial Distribution of Physical Saliency and Semantic Informativeness from Natural Scenes in the Human Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- The role of local meaning in infants' fixations of natural scenes.Infancy : the official journal of the International Society on Infant StudiesArticle
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Authors and funding
7 authors at 1 institution in 1 country.
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Abstract
Little is known about the development of higher-level areas of visual cortex during infancy, and even less is known about how the development of visually guided behavior is related to the different levels of the cortical processing hierarchy. As a first step toward filling these gaps, we used representational similarity analysis (RSA) to assess links between gaze patterns and a neural network model that captures key properties of the ventral visual processing stream. We recorded the eye movements of 4- to 12-month-old infants (N = 54) as they viewed photographs of scenes. For each infant, we calculated the similarity of the gaze patterns for each pair of photographs. We also analyzed the images using a convolutional neural network model in which the successive layers correspond approximately to the sequence of areas along the ventral stream. For each layer of the network, we calculated the similarity of the activation patterns for each pair of photographs, which was then compared with the infant gaze data. We found that the network layers corresponding to lower-level areas of visual cortex accounted for gaze patterns better in younger infants than in older infants, whereas the network layers corresponding to higher-level areas of visual cortex accounted for gaze patterns better in older infants than in younger infants. Thus, between 4 and 12 months, gaze becomes increasingly controlled by more abstract, higher-level representations. These results also demonstrate the feasibility of using RSA to link infant gaze behavior to neural network models. A video abstract of this article can be viewed at https://youtu.be/K5mF2Rw98Is.
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