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Syntactic Processing Engages the Semantic Control Network

Chang, Q.; Jefferies, E.; Jackson, R. L.

2025-11-01 neuroscience
10.1101/2025.10.31.685882 bioRxiv
Show abstract

The relationship between semantics and syntax is highly contested. Neuroimaging evidence has offered conflicting views on whether these domains are neurally separable, in part because prior work has not distinguished two key components of semantic cognition: semantic representation and semantic control. In this study, we conducted an activation likelihood estimation (ALE) meta-analysis to identify regions consistently engaged by more versus less demanding syntactic processing, and compared these directly with regions recruited by demanding versus less demanding semantic processing. Demanding syntactic processing engaged regions across the semantic control network (SCN), including the inferior frontal gyrus (IFG) and insula (particularly on the left), left posterior temporal cortex (posterior superior temporal sulcus and middle temporal gyrus), and bilateral dorsomedial prefrontal cortex. No regions outside the SCN responded significantly more to syntactic demands than semantic control. Within the SCN, there was significantly less reliable activation for syntactic than semantic control demands in some anterior (pars triangularis) and ventral (pars orbitalis) portions of the left IFG and a region in posterior fusiform and inferior temporal gyrus. Greater involvement for syntax than semantic control was identified in a small region of posterior left IFG (pars opercularis) within the SCN. Moreover, both controlled semantic and syntactic processing showed multimodal responses to auditory and visual stimuli in the left IFG and posterior temporal cortex. Together, these findings suggest that syntactic processing is distinct from semantic representation, yet demanding syntax engages portions of the SCN, reflecting a shared need to access and manipulate stored semantic knowledge for flexible, context-sensitive use.

Published in Imaging Neuroscience (predicted rank #10) · training set

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