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bioRxiv · 10.1101/2024.06.20.599931

A low-activity cortical network selectively encodes syntax

Morgan, A. M.·Devinsky, O.·Doyle, W.·Dugan, P.·Friedman, D.·Flinker, A.
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Abstract

Humans are the only species with the ability to systematically combine words to convey an unbounded number of complex meanings. This process is guided by combinatorial processes whose underlying neural mechanisms remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover distinct cortical networks encoding word-level and higher-order information. These networks exhibited a hybrid spatial organization: broadly distributed across traditional language areas, but with focal concentrations of sensitivity to semantic and structural contrasts in canonical language regions. In contrast to previous comprehension-based findings, we find that these networks are largely non-overlapping. Most strikingly, our data re-veal an unexpected property of higher-order linguistic information: it is encoded independent of neural activity levels. These results show that activity magnitude and information content are dissociable, with important implications for studying the neurobiology of language. Teaser"Brain recordings during speech reveal complex linguistic information throughout cortex, independent of neural activity levels."

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Morgan, A. M., Devinsky, O., Doyle, W., Dugan, P., Friedman, D., Flinker, A.. 2024-06-20. A low-activity cortical network selectively encodes syntax. https://doi.org/10.1101/2024.06.20.599931

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