Reverse-engineering the cortical architecture for controlled semantic cognition

Rebecca L. Jackson (), Timothy T. Rogers and Matthew A. Lambon Ralph ()
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Rebecca L. Jackson: University of Cambridge
Timothy T. Rogers: University of Wisconsin–Madison
Matthew A. Lambon Ralph: University of Cambridge

Nature Human Behaviour, 2021, vol. 5, issue 6, 774-786

Abstract: Abstract We employ a reverse-engineering approach to illuminate the neurocomputational building blocks that combine to support controlled semantic cognition: the storage and context-appropriate use of conceptual knowledge. By systematically varying the structure of a computational model and assessing the functional consequences, we identified the architectural properties that best promote some core functions of the semantic system. Semantic cognition presents a challenging test case, as the brain must achieve two seemingly contradictory functions: abstracting context-invariant conceptual representations across time and modalities, while producing specific context-sensitive behaviours appropriate for the immediate task. These functions were best achieved in models possessing a single, deep multimodal hub with sparse connections from modality-specific regions, and control systems acting on peripheral rather than deep network layers. The reverse-engineered model provides a unifying account of core findings in the cognitive neuroscience of controlled semantic cognition, including evidence from anatomy, neuropsychology and functional brain imaging.

Date: 2021
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DOI: 10.1038/s41562-020-01034-z

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