Lack of selectivity for syntax relative to word meanings throughout the language network.

To understand what you are reading now, your mind retrieves the meanings of words and constructions from a linguistic knowledge store (lexico-semantic processing) and identifies the relationships among them to construct a complex meaning (syntactic or combinatorial processing). Do these two sets of processes rely on distinct, specialized mechanisms or, rather, share a common pool of resources? Linguistic theorizing, empirical evidence from language acquisition and processing, and computational modeling have jointly painted a picture whereby lexico-semantic and syntactic processing are deeply inter-connected and perhaps not separable. In contrast, many current proposals of the neural architecture of language continue to endorse a view whereby certain brain regions selectively support syntactic/combinatorial processing, although the locus of such "syntactic hub", and its nature, vary across proposals. Here, we searched for selectivity for syntactic over lexico-semantic processing using a powerful individual-subjects fMRI approach across three sentence comprehension paradigms that have been used in prior work to argue for such selectivity: responses to lexico-semantic vs. morpho-syntactic violations (Experiment 1); recovery from neural suppression across pairs of sentences differing in only lexical items vs. only syntactic structure (Experiment 2); and same/different meaning judgments on such sentence pairs (Experiment 3). Across experiments, both lexico-semantic and syntactic conditions elicited robust responses throughout the left fronto-temporal language network. Critically, however, no regions were more strongly engaged by syntactic than lexico-semantic processing, although some regions showed the opposite pattern. Thus, contra many current proposals of the neural architecture of language, syntactic/combinatorial processing is not separable from lexico-semantic processing at the level of brain regions -- or even voxel subsets -- within the language network, in line with strong integration between these two processes that has been consistently observed in behavioral and computational language research. The results further suggest that the language network may be generally more strongly concerned with meaning than syntactic form, in line with the primary function of language - to share meanings across minds.

/pdf/lack-of-selectivity-for-syntax-relative-to-word-meanings-355c2s0s60.pdf

Lack of selectivity for syntax relative to word meanings throughout the language network

N400 and P600 modulation in presupposition accommodation: The effect of different trigger types

Event-related potentials (ERPs) provide a window into how the brain is processing language. Here, we propose a theory that argues that ERPs such as the N400 and P600 arise as side effects of an error-based learning mechanism that explains linguistic adaptation and language learning. We instantiated this theory in a connectionist model that can simulate data from three studies on the N400 (amplitude modulation by expectancy, contextual constraint, and sentence position), five studies on the P600 (agreement, tense, word category, subcategorization and garden-path sentences), and a study on the semantic P600 in role reversal anomalies. Since ERPs are learning signals, this account explains adaptation of ERP amplitude to within-experiment frequency manipulations and the way ERP effects are shaped by word predictability in earlier sentences. Moreover, it predicts that ERPs can change over language development. The model provides an account of the sensitivity of ERPs to expectation mismatch, the relative timing of the N400 and P600, the semantic nature of the N400, the syntactic nature of the P600, and the fact that ERPs can change with experience. This approach suggests that comprehension ERPs are related to sentence production and language acquisition mechanisms.

Language ERPs reflect learning through prediction error propagation [Invited talk]

When reading a text describing an everyday activity, comprehenders build a model of the situation described that includes prior knowledge of the entities, locations, and sequences of actions that typically occur within the event. Previous work has demonstrated that such knowledge guides the processing of incoming information by making event boundaries more or less expected. In the present ERP study, we investigated whether comprehenders' expectations about event boundaries are influenced by how elaborately common events are described in the context. Participants read short stories in which a common activity (e.g., washing the dishes) was described either in brief or in an elaborate manner. The final sentence contained a target word referring to a more predictable action marking a fine event boundary (e.g., drying) or a less predictable action, marking a coarse event boundary (e.g., jogging). The results revealed a larger N400 effect for coarse event boundaries compared to fine event boundaries, but no interaction with description length. Between 600 and 1000 ms, however, elaborate contexts elicited a larger frontal positivity compared to brief contexts. This effect was largely driven by less predictable targets, marking coarse event boundaries. We interpret the P600 effect as indexing the updating of the situation model at event boundaries, consistent with Event Segmentation Theory (EST). The updating process is more demanding with coarse event boundaries, which presumably require the construction of a new situation model.

/pdf/on-the-predictability-of-event-boundaries-in-discourse-an-8agj7bj3br.pdf

On the predictability of event boundaries in discourse: An ERP investigation.

The ability to efficiently process presuppositions, which contain information that the speaker believes to be in the background to the conversation, is essential for effective communication. To get a deeper understanding of the nature and the time-course of temporal presupposition processing, we examined event-related potential evoked by the word again in two types of sentence contexts. The word again was presented in contexts that supported a presupposition (e.g. Jake had tipped a maid at the hotel once before. Today he tipped a maid at the hotel again … ) or violated it (e.g. Jake had never tipped a maid at the hotel before. Today he tipped a maid at the hotel again … ). The presupposition violation was associated with increased amplitudes of the P3b/P600 but not the N400 component. We argue for the centrality of the P3b/P600 component for presupposition processing. These findings demonstrate rapid integration of lexical presuppositions with contextual knowledge.

/pdf/processing-temporal-presuppositions-an-event-related-5ekchfp7h7.pdf

Processing temporal presuppositions: an event-related potential study

Recent evidence suggests that language processing is well-adapted to noise in the input (e.g., speech errors, mishearing) and readily corrects the input via rational inference over possible intended sentences and probable noise corruptions. However, it remains unclear whether this inference takes the form of an offline re-analysis or a rapid, real-time correction to the representations of the input. We hypothesize that noise inferences happen online during processing and that well-studied ERP components may serve as a useful index of this process. In particular, a reduced N400 effect and increased P600 effect appear to accompany sentences where the probability that the message was corrupted by noise exceeds the probability that it was produced intentionally and perceived accurately. Indeed, semantic violations that are attributable to noise -- for example, in "The storyteller could turn any incident into an amusing antidote", where the implausible word "antidote" is orthographically and phonologically close to the intended "anecdote" -- elicit a reduced N400 effect and larger P600 effect. Further, the magnitude of this P600 effect is shown to relate to the probability that the comprehender will retrieve a plausible alternative. This work thus adds to the growing body of literature that suggests that many aspects of language processing are well-adapted to noise in the input and opens the door to electrophysiologic investigations of these processes.

/pdf/an-erp-index-of-real-time-error-correction-within-a-noisy-3loe1s03ya.pdf

An ERP index of real-time error correction within a noisy-channel framework of human communication

https://escholarship.org/content/qt8f72t5x7/qt8f72t5x7.pdf?t=quefok

An ERP index of real-time error correction within a noisy-channel framework of human communication.

Models that aim to explain electrophysiological responses to linguistic processing (e.g., the N400 and P600 components) typically assume that the representation of linguistic input is error-free. Recent evidence suggests that language processing mechanisms are well-adapted to input corrupted by noise (e.g., speech errors, mishearing) and readily correct for it via rational inference over possible intended sentences and probable noise corruptions. We hypothesize that a P600 ensues whenever the probability that the message was corrupted by noise exceeds the probability that it was produced intentionally and perceived accurately. We show that semantic violations that are attributable to noise—for example, in “The storyteller could turn any incident into an amusing antidote”, the implausible word “antidote” is orthographically and phonologically close to the intended “anecdote”—elicit a P600 (rather than N400). Further, the magnitude of this P600 is shown to relate to the probability that the comprehender will retrieve a plausible alternative.

https://www.biorxiv.org/content/biorxiv/early/2020/02/10/2020.02.08.930214.full.pdf

Laura Stearns

Papers

Processing temporal presuppositions: an event-related potential study

An ERP index of real-time error correction within a noisy-channel framework of human communication

An ERP index of real-time error correction within a noisy-channel framework of human communication.

The P600 ERP component as an index of rational error correction within a noisy-channel framework of human communication