Graded sensitivity to structure and meaning throughout the human language network

Abstract

Human language has a remarkable capacity to encode complex ideas. This capacity arises because language is compositional: the form and arrangement of words in sentences (structure) determine the conceptual relations that hold between the words referents (meaning). A foundational question in human cognition is whether the brain regions that support language are similarly factored into structure-selective and meaning-selective areas. In an influential study, Pallier et al. (2011, PNAS) used fMRI to investigate the brain response to sequences of real words and pseudowords and reported a sharp dissociation between structure-selective and meaning-selective brain regions. In the present study, we argue that no such dissociation emerges when individual differences in brain anatomy are considered. We report three experiments (including a close conceptual replication of Pallier et al.s original study) that use precision fMRI methods to capture separation or overlap of function in the brains of individual participants. Our results replicate Pallier et al.s finding that the brains response is modulated by the sequential structure of language but paint a different picture with respect to the structure-meaning relationship. Instead of distinct structure-selective and meaning-selective brain areas, we find distributed sensitivity to both linguistic structure and meaning throughout a broad frontotemporal brain network. Our results join a growing body of evidence for an integrated network for language in the human brain within which internal specialization is primarily a matter of degree rather than kind, in contrast with influential proposals that advocate distinct specialization of different brain areas for different types of linguistic functions. Significance StatementUsing fMRI, we show that a broad network of frontal and temporal areas in the left hemisphere of the human brain is sensitive to both the structure of language and the meaning that it encodes. This finding challenges many current theories of the neurobiology of language, which propose a sharp separation between areas that encode structure and areas that encode meaning. Instead, results support a broad distribution of word- and sentence-level processing across an integrated brain network for language. This PDF file includes: Main Text Figures 1 to 3 Tables 1 to 1