The scaffolding of individual variability in language processing by domain-general neural networks

Language processing is supported by distributed neural systems. Yet most research examines these systems at the population-average level, obscuring how individual cognitive differences shape language-related brain activity. In this study, we combined comprehensive cognitive assessments and task-based fMRI in a large sample of healthy adults (N = 205) to examine how variability in linguistic knowledge, working memory, processing speed, and non-verbal reasoning influenced neural responses in four language tasks: lexical decision, picture naming, sentence comprehension, and sentence production. All tasks engaged canonical left-lateralized language regions. However, individual differences in cognitive skills were not associated with modulations within commonly activated regions, but rather with modulations in domain-general systems outside traditional perisylvian language areas, mainly the default mode and dorsal attention networks. Notably, activations in these domain-general regions were predominantly negatively correlated with cognitive skills, indicating that individuals with lower cognitive skills draw on these broader neural resources more than higher-skilled individuals, possibly as a compensatory mechanism. These results reveal that while canonical language regions are consistently engaged during language tasks, the recruitment of domain-general systems acts as a variable resource modulated by individuals’ cognitive skills. Overall, our findings demonstrate that individual cognitive profiles determine how distributed brain systems are dynamically engaged to scaffold language processing.