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

To study a core component of human intelligence---our ability to combine the meaning of words---neuroscientists look for neural correlates of meaning composition, such as brain activity proportional to the difficulty of understanding a sentence. However, little is known about the product of meaning composition---the combined meaning of words beyond their individual meaning. We term this product ``supra-word meaning99 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.