Dimensionality reduction and neural network modelling reveal a distributed cortico-cerebellar network for cognitive recombination.
Human cognition depends on the ability to flexibly recombine existing knowledge in new ways. Although this capacity for compositionality has traditionally been attributed to cortical networks, its broader neural basis remains unclear. Here, we combined dimensionality reduction of task-based fMRI with recurrent neural network modelling to dissociate two processes underlying compositional cognition: the recruitment of specialised components; and the more general process of recombination. Across 87 participants performing a well-established compositional task, component processes were supported by domain-selective cortical and anterior cerebellar regions, whereas recombination engaged a distributed cortico-cerebellar network that was low-dimensional, highly integrated, and generalised across contexts. Similar functional signatures were also observed in recurrent neural networks trained to perform multiple cognitive tasks, suggesting that low-dimensional recombination is a general solution for flexible compositional cognition. Our findings revise existing models of compositional cognition by highlighting cortico-cerebellar interactions as a mechanism for flexible, integrative task generalisation.
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Tan et al. (2025) studied this question.
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