Decoding words during sentence production: Syntactic role encoding and structure-dependent dynamics revealed by ECoG

Abstract

Sentence production is the uniquely human ability to transform complex thoughts into strings of words. Despite the importance of this process, language production research has primarily focused on single words. However, it remains a largely untested assumption that the principles of word production generalize to more naturalistic utterances like sentences. Here, we investigate this using high-resolution neurosurgical recordings (ECoG) and an overt production experiment where patients produced six words in isolation (picture naming) and in sentences (scene description). We trained machine learning classifiers to identify the unique brain activity patterns for each word during picture naming, and used these patterns to decode which words patients were processing while they produced sentences. Our findings confirm that words share cortical representations across tasks, but reveal a division of labor within the language network. In sensorimotor cortex, words were consistently activated in the order in which they were said in the sentence. However, in inferior and middle frontal gyri (IFG and MFG), the order in which words were processed depended on the syntactic structure of the sentence. Deeper analysis of this pattern revealed a spatial code for representing a word's position in the sentence, with subjects selectively encoded in IFG and objects in MFG. Finally, we argue that the processes we observe in prefrontal cortex may impose a subtle pressure on language evolution, explaining why nearly all the world's languages position subjects before objects.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* This version offers longer discussions of previous models of word production, and shifts the focus of the findings to emphasize (1) an interpretation of our findings in prefrontal cortex as a mechanism for top-down control of sentence production and (2) the encoding of syntactic roles -- specifically, the representation of subjects in IFG and objects in MFG.

* https://github.com/flinkerlab/decoding_words_in_sentences