Functional dissociation of the language network and other cognition in early childhood

Is language distinct from other cognition during development? Does neural machinery for language emerge from general-purpose neural mechanisms, becoming tuned for language after years of experience and maturation? Answering these questions will shed light on the origins of domain-specificity in the brain. We address these questions using precision fMRI and found young children (35 months-9 years) show domain-specific, left-lateralized language activation, and the language network is not responsive to domain-general cognitive load. Additionally, the cortically adjacent multiple demand network is selective to cognitive load, but not to language. These networks show higher within vs. between-network functional connectivity. This connectivity is stable across ages (examined cross-sectionally and longitudinally), whereas language responses increase with age and across-time within subject, reflecting a domain-specific developmental change. Overall, these findings suggest that domain-specificity, even for uniquely human cognition like language, develops early and distinctly from mechanisms that presumably support other human cognition. Significance StatementThis study provides evidence of a double dissociation between neural processors for language and domain-general cognition (specifically, cognitive load) in young children. These results refute previous claims that linguistic function emerges from domain-general mechanisms supporting non-linguistic, higher-order cognition, and with both cross-sectional and longitudinal analyses, show that the continued development of linguistic specialization is also unrelated to domain-general mechanisms that support cognitive flexibility and executive function. This work emphasizes the importance of single-subject fMRI analyses with multiple tasks to explicitly dissociate cognitive constructs, and the importance of longitudinal research for scientific rigor, even in toddlers and preschoolers who are difficult to image with fMRI.