Linguistic input drives brain network configuration during language comprehension.

Assessing the synchrony and interplay between distributed neural regions is critical to understanding how language is processed. Here, we investigated possible neuro-functional links between form and meaning during sentence comprehension combining a classical whole-brain approach, which characterizes patterns of brain activation resulting from our experimental manipulation, and a novel multivariate network-based approach, which uses graph-theory measures to unravel the architectural configuration of the language system. Capitalizing on the Spanish gender agreement system, we experimentally manipulated formal and conceptual factors: whether the noun-adjective grammatical gender relationship was congruent or not and whether the noun gender type was semantically informative or strictly formal. Left inferior and middle frontal gyri, as well as left MTG/STG emerged as critical areas for the computation of grammatical relations. We demonstrate how the interface between formal and conceptual features depends on the synergic articulation of brain areas divided in three subnetworks that extend beyond the classical left-lateralized perisylvian language circuit. Critically, we isolated a subregion of the left angular gyrus showing a significant interaction between gender congruency and gender type. The functional interplay between the angular gyrus and left perisylvian language-specific circuit proves crucial for constructing coherent and meaningful messages. Importantly, using graph theory we show that this complex system is functionally malleable: the role each node plays within the network changes depending on the available linguistic cues. Significance StatementNeural networks can be described as graphs comprising distributed and interconnected nodes. These nodes share functional properties but also differ in terms of functional specialization and the number of interconnections mediating the efficient transfer of information. Previous work has shown functional connectivity differences based on graph-theory properties between typical and atypical samples. However, here we have used concepts from graph theory to characterize connectivity during language processing using task-related fMRI. This approach allowed us to demonstrate how linguistic input drives brain network configuration during language comprehension. This is the first evidence of functional flexibility in language networks: the communicative capacity of each hub changes depending on whether the linguistic input grants access to meaning or is purely formal.