Aug 2026· Science Advances· Vol 12· 0 citations· 148 references
Medicine
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 noninvasive 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 nonoverlapping. Most notably, higher-order linguistic information showed an unexpected dissociation from local activity magnitude. This result establishes an operational dissociation between activity magnitude and information content, pointing toward a potentially distinct neural coding scheme for higher-order language, with important implications for the neurobiology of language.
Neuroimaging dissociates specialized language regions from the domain-general multiple-demand (MD) network, yet the functional contribution of MD regions to language processing remains unresolved. Because MD recruitment during linguistic tasks is conventionally attributed to domain-general cognitive load, prior researc...
Miriam Havin, Meir Meshulam, Taelin Karidi et al.· bioRxiv· 0 citations
Human language processing can be studied through both behavior and brain activity, yet it remains unclear whether these two data types reflect sensitivity to the same information. One influential view holds that both behavioral and neural responses are largely determined by processing effort, often estimated by word su...
Andrea Gregor de Varda, Yevgeni Berzak, Evelina Fedorenko et al.· bioRxiv· 0 citations
Making meaningful inferences about the functional architecture of the language system requires the ability to refer to the same neural units across individuals and studies. Traditional brain imaging approaches align and average brains together in a common space. However, lateral frontal and temporal cortices, where the...
Mathias Huybrechts, R. Bruffaerts, Alvincé L. Pongos et al.· Journal of Neurophysiology· 1 citation
The spatial representation of numbers is a central focus in numerical cognition. While previous studies demonstrate that the processing of cardinal and ordinal semantics underlies spatial-numerical associations (SNAs), it remains unclear whether these two distinct semantic types share common neural representations. To...
Understanding speech requires listeners to integrate incoming input with prior linguistic and thematic knowledge to access meaning, a task greatly aided by prediction. Surprisal and related phenomena (e.g., next word prediction) tend to be associated with broad activation of language regions during listening. A major c...
Ryan M. O'Leary, Hailey C. Smith, Emily B. Myers et al.· bioRxiv· 0 citations
Abstract representations allow the brain to extract shared structure across different experiences and generalize knowledge beyond individual situations. Although previous studies have shown that representational geometry plays a critical role in supporting abstraction, it remains unclear how the composition of neuronal...