ArticleNature neuroscience2024
Semi-orthogonal subspaces for value mediate a binding and generalization trade-off.
Article in Nature neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed.
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- Neural geometry in the human hippocampus enables generalization across spatial position and gaze.ArXiv · 2026Article
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- Neural population geometry and optimal coding of tasks with shared latent structure.Nature neuroscience · 2026Article
- Rethinking the centrality of brain areas in understanding functional organization.Nature neuroscience · 2026Review
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- Humans and neural networks show similar patterns of transfer and interference during continual learning.Nature human behaviour · 2026Article
- A neural circuit framework for economic choice: from building blocks of valuation to compositionality in multitasking.bioRxiv : the preprint server for biology · 2025Article
- A transformation from vision to imagery in the human brain.bioRxiv : the preprint server for biology · 2025Article
- Cognitive processes are disentangled at cortex-wide scales.bioRxiv : the preprint server for biology · 2025Article
- Rarely categorical, always high-dimensional: how the neural code changes along the cortical hierarchy.bioRxiv : the preprint server for biology · 2025Article
- Semi-orthogonal subspaces for value mediate a binding and generalization trade-off.Nature neuroscience · 2024Article
- Modular representations emerge in neural networks trained to perform context-dependent tasks.bioRxiv : the preprint server for biology · 2024Article
- Rational inattention in neural coding for economic choice.bioRxiv : the preprint server for biology · 2024Article
- The neural basis of swap errors in working memory.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The neural basis of swap errors in working memory.bioRxiv : the preprint server for biology · 2023Article
- Multimodal subspace independent vector analysis effectively captures latent relationships between brain structure and function.Imaging neuroscience (Cambridge, Mass.)Article
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Abstract
When choosing between options, we must associate their values with the actions needed to select them. We hypothesize that the brain solves this binding problem through neural population subspaces. Here, in macaques performing a choice task, we show that neural populations in five reward-sensitive regions encode the values of offers presented on the left and right in distinct subspaces. This encoding is sufficient to bind offer values to their locations while preserving abstract value information. After offer presentation, all areas encode the value of the first and second offers in orthogonal subspaces; this orthogonalization also affords binding. Our binding-by-subspace hypothesis makes two new predictions confirmed by the data. First, behavioral errors should correlate with spatial, but not temporal, neural misbinding. Second, behavioral errors should increase when offers have low or high values, compared to medium values, even when controlling for value difference. Together, these results support the idea that the brain uses semi-orthogonal subspaces to bind features.
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