Knowledge needs space: A feedback loop model for cortical surface expansion and gyrification during learning, integrating functional and structural changes.

The expansion and gyrification of the human cerebral cortex, are crucial for the emergence of higher cognition, as they increase the available space for the topologically complex configuration of the connectome. These phenomena emerge during a developmental trajectory shaped by genetic, biochemical, mechanical and environmental factors. Beyond the expansion and folding observed during development, transient or permanent changes in the cortical surface area and folding patterns have also been observed during certain learning tasks in adulthood. In this essay, we propose a multi-staged qualitative model, for the expansion and potential convolution of cortical surface during learning in adults. The model integrates existing knowledge about the mechanisms responsible for developmental cortical surface area expansion and folding, with recent advancements in the understanding of learning-induced microstructural changes and growth. The primary driver of cortical surface area expansion in hypothesized to be learning-induced growth of transcolumnar dendrites and their supportive structures in the neuropil. This growth serves as a critical link between functional dynamics and structural organization across multiple spatial and temporal scales. Thus, the model incorporates feedback loops between the different stages of surface expansion and network growth. It connects information flow, adaptive network reconfiguration and growth, mechanical phenomena during network growth, cortical surface expansion and their impact on the preceding stages of the model. Finally, we discuss the potential implications of this model for research on the neurobiology of knowledge acquisition, the rate of learning new tasks and explore potential research directions.