ArticleScientific reports2023
Foundations of human spatial problem solving.
Article in Scientific reports, 2023. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- The cost of unmodeled biological complexity in artificial neural networks.Patterns (New York, N.Y.) · 2025Review
- Therapeutic Metaphors Enhance Memory Systems in Mental Health Contexts.Brain and behavior · 2025Article
- Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research.Brain : a journal of neurology · 2023Review
- The whole prefrontal cortex is premotor cortex.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
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Authors and funding
2 authors.
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Abstract
Despite great strides in both machine learning and neuroscience, we do not know how the human brain solves problems in the general sense. We approach this question by drawing on the framework of engineering control theory. We demonstrate a computational neural model with only localist learning laws that is able to find solutions to arbitrary problems. The model and humans perform a multi-step task with arbitrary and changing starting and desired ending states. Using a combination of computational neural modeling, human fMRI, and representational similarity analysis, we show here that the roles of a number of brain regions can be reinterpreted as interacting mechanisms of a control theoretic system. The results suggest a new set of functional perspectives on the orbitofrontal cortex, hippocampus, basal ganglia, anterior temporal lobe, lateral prefrontal cortex, and visual cortex, as well as a new path toward artificial general intelligence.
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Registered trials
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