SYNTACTIC REPRESENTATIONS IN THE HUMAN BRAIN: BEYOND EFFORT-BASED METRICS

Abstract

We are far from having a complete mechanistic understanding of the brain computations involved in language processing and of the role that syntax plays in those computations. Most language studies do not computationally model syntactic structure and most studies that do model syntactic processing use effort-based metrics. These metrics capture the effort needed to process the syntactic information given by every word (Brennan et al., 2012; Hale et al., 2018; Brennan et al., 2016). They can reveal where in the brain syntactic processing occurs, but not what features of syntax are processed by different brain regions. Here, we move beyond effort-based metrics and propose explicit features capturing the syntactic structure that is incrementally built while a sentence is being read. Using these features and functional Magnetic Resonance Imaging (fMRI) recordings of participants reading a natural text, we study the brain representation of syntax. We find that our syntactic structure-based features are better than effort-based metrics at predicting brain activity in various parts of the language system. We show evidence of the brain representation of complex syntactic information such as phrase and clause structures. We see that regions well-predicted by syntactic features are distributed in the language system and are not distinguishable from those processing semantics. Our results call for a shift in the approach used for studying syntactic processing.

1. INTRODUCTION

Neuroscientists have long been interested in how the brain processes syntax. To date, there is no consensus on which brain regions are involved in processing it. Classically, only a small number of regions in the left hemisphere were thought to be involved in language processing. More recently, the language system was proposed to involve a set of brain regions spanning the left and right hemisphere (Fedorenko & Thompson-Schill, 2014) . Similarly, some findings show that syntax is constrained to specific brain regions (Grodzinsky & Friederici, 2006; Friederici, 2011) , while other findings show syntax is distributed throughout the language system (Blank et al., 2016; Fedorenko et al., 2012; 2020) . The biological basis of syntax was first explored through studies of the impact of brain lesions on language comprehension or production (Grodzinsky, 2000) and later through non-invasive neuroimaging experiments that record brain activity while subjects perform language tasks, using methods such as functional Magnetic Resonance Imaging (fMRI) or electroencephalography (EEG). These experiments usually isolate syntactic processing by contrasting the activity between a difficult syntactic condition and an easier one and by identifying regions that increase in activity with syntactic effort (Friederici, 2011) . An example of these conditions is reading a sentence with an object-relative clause (e.g. "The rat that the cat chased was tired"), which is more taxing than reading a sentence with a subject-relative clause (e.g. "The cat that chased the rat was tired"). In the past decade, this approach was extended to study syntactic processing in naturalistic settings such as when reading or listening to a story (Brennan et al., 2012; Hale et al., 2018; Willems et al., 2015) . Because such complex material is not organized into conditions, neuroscientists have instead devised effort-based metrics capturing the word-by-word evolving syntactic demands required to understand the material. Brain regions with activity correlated with those metrics are suggested to be involved in processing syntax. We use the term effort-based metrics to refer to uni-dimensional measures capturing word-by-word syntactic demands. A standard approach for constructing a syntactic effort-based metric is to assume 1

