Abstract linguistic structure correlates with temporal activity during naturalistic comprehension

• We evaluate the role of hierarchical syntax in every-day language comprehension.
• We correlate word-by-word parsing predictions with fMRI data during passive listening.
• Surprisal from Markov models predictive in frontal and temporal ROIs.
• Surprisal from phrase-structure grammar predictive in temporal and parietal lobes.
• Minimalist Grammar node-count predictive only in left temporal lobes.

Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations.