The language network responds robustly to sentences across diverse tasks

A network of left frontal and temporal brain areas supports language comprehension and production, implementing computations related to word retrieval and combinatorial linguistic processing. Here, we ask: are computations over linguistic input driven in a bottom-up way, by the input, or in a top-down way, by task demands? Participants (n=52) read sentences and nonword lists under six task conditions, including passive reading, reading with a memory probe at the end, and tasks that require deep semantic engagement. The sentences>nonwords contrast isolated the same set of language-responsive voxels across all tasks; the locations of those voxels were participant-specific, highlighting the value of individual-specific functional localization. We therefore conclude that language localization is robust to task variation. We then examined responses to each task in these language-responsive voxels (the language network) and in the domain-general multiple demand (MD) network, known to respond to task demands. The language network responded robustly to sentences across all tasks, with somewhat higher responses to semantically engaging tasks. In contrast, the MD network responded to both sentences and nonwords in the presence of a demanding task, which warrants caution when examining brain responses to language tasks accompanied by task demands, as such tasks engage two independent systems. A multivariate analysis revealed that stimulus information is more easily decodable in the language network, whereas task information is more decodable in the MD network. These results suggest that the language and MD networks perform complementary functions during task-driven language comprehension, with the language network primarily extracting information from linguistic input and the MD network determining the appropriate response to the task.