Combining computational controls with natural text reveals new aspects of meaning composition

Abstract

AbstractTo study a core component of human intelligence—our ability to combine the meaning of words—neuroscientists look for neuralcorrelatesof meaning composition, such as brain activity proportional to the difficulty of understanding a sentence. However, little is known about theproductof meaning composition—the combined meaning of words beyond their individual meaning. We term this product “supra-word meaning” and devise a computational representation for it by using recent neural network algorithms and a new technique to disentangle composed-from individual-word meaning. Using functional magnetic resonance imaging, we reveal that hubs that are thought to process lexical-level meaning also maintain supra-word meaning, suggesting a common substrate for lexical and combinatorial semantics. Surprisingly, we cannot detect supra-word meaning in magnetoencephalography, which suggests that composed meaning is maintained through a different neural mechanism than synchronized firing. This sensitivity difference has implications for past neuroimaging results and future wearable neurotechnology.