ArticleScience advances2025
A detailed theory of thalamic and cortical microcircuits for predictive visual inference.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Inferential planning in the frontal cortex.Cell reports · 2026Article
- Modeling attention and binding in the brain through bidirectional recurrent gating.Nature communications · 2026Article
- Feedforward extraction of behaviorally significant information by neocortical columns.Frontiers in neural circuits · 2025Article
- Integrated world modeling theory expanded: Implications for the future of consciousness.Frontiers in computational neuroscience · 2022Article
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Authors and funding
6 authors.
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Abstract
Understanding cortical microcircuitry requires theoretical models that can tease apart their computational logic from biological details. Although Bayesian inference serves as an abstract framework of cortical computation, precisely mapping concrete instantiations of computational models to biology under real-world tasks is necessary to produce falsifiable neural models. On the basis of a recent generative model, recursive cortical networks, that demonstrated excellent performance on vision benchmarks, we derive a theoretical cortical microcircuit by placing the requirements of the computational model within biological constraints. The derived model suggests precise algorithmic roles for the columnar and laminar feed-forward, feedback, and lateral connections, the thalamic pathway, blobs and interblobs, and the innate lineage-specific interlaminar connectivity within cortical columns. The model also explains several visual phenomena, including the subjective contour effect and neon-color spreading effect, with circuit-level precision. Our model and methodology provides a path forward in understanding cortical and thalamic computations.
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