ArticleNature human behaviour2025
End-to-end topographic networks as models of cortical map formation and human visual behaviour.
Article in Nature human behaviour, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Self-supervised learning yields representational signatures of category-selective cortex.Communications biology · 2026Article
- A single computational objective can produce specialization of streams in visual cortex.Nature communications · 2026Article
- Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Re-emergence of orientation coding in primate IT cortex and deep networks reveals functional hubs for visual processing.bioRxiv : the preprint server for biology · 2026Article
- Category selectivity observed in the human brain is distinct from category selectivity observed in artificial neural networks.bioRxiv : the preprint server for biology · 2026Article
- Metabolic organization of macaque visual cortex reflects visual field topography and perceptual specialization.PLoS biology · 2026Article
- Linking retinal sampling in neural encoding models to temporal profiles of visual processing in humans.PLoS computational biology · 2026Article
- Representations converge as brain maps diverge along the cortical hierarchy.bioRxiv : the preprint server for biology · 2026Article
- Foveated Retinotopy Improves Classification and Localization in Convolutional Neural Networks.Vision (Basel, Switzerland) · 2026Article
- Local lateral connectivity is sufficient for replicating cortex-like topographical organization in deep neural networks.Nature communications · 2026Article
- Achieving more human brain-like vision via human EEG representational alignment.Communications biology · 2026Article
- Representational differentiation and integration within the hippocampal circuit during naturalistic stimuli.Communications biology · 2026Article
- Investigating action topography in visual cortex and deep artificial neural networks.Nature communications · 2025Article
- Teaching CORnet human fMRI representations for enhanced model-brain alignment.Cognitive neurodynamics · 2025Article
- TopoNets: High performing vision and language models with brain-like topography.... International Conference on Learning Representations · 2025Article
- A unifying framework for functional organization in early and higher ventral visual cortex.Neuron · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
A prominent feature of the primate visual system is its topographic organization. For understanding its origins, its computational role and its behavioural implications, computational models are of central importance. Yet, vision is commonly modelled using convolutional neural networks, which are hard-wired to learn identical features across space and thus lack topography. Here we overcome this limitation by introducing all-topographic neural networks (All-TNNs). All-TNNs develop several features reminiscent of primate topography, including smooth orientation and category selectivity maps, and enhanced processing of regions with task-relevant information. In addition, All-TNNs operate on a low energy budget, suggesting a metabolic benefit of smooth topographic organization. To test our model against behaviour, we collected a dataset of human spatial biases in object recognition and found that All-TNNs significantly outperform control models. All-TNNs thereby offer a promising candidate for modelling primate visual topography and its role in downstream behaviour.
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