Testing limits: ERP evidence for word form preactivation during speeded sentence reading

A predictive coding model of the N400

The N400 event-related component has been widely used to investigate the neural mechanisms underlying real-time language comprehension. However, despite decades of research, there is still no unifying theory that can explain both its temporal dynamics and functional properties. In this work, we show that predictive coding - a biologically plausible algorithm for approximating Bayesian inference - offers a promising framework for characterizing the N400. Using an implemented predictive coding computational model, we demonstrate how the N400 can be formalized as the lexico-semantic prediction error produced as the brain infers meaning from the linguistic form of incoming words. We show that the magnitude of lexico-semantic prediction error mirrors the functional sensitivity of the N400 to various lexical variables, priming, contextual effects, as well as their higher-order interactions. We further show that the dynamics of the predictive coding algorithm provides a natural explanation for the temporal dynamics of the N400, and a biologically plausible link to neural activity. Together, these findings directly situate the N400 within the broader context of predictive coding research. More generally, they raise the possibility that the brain may use the same computational mechanism for inference across linguistic and non-linguistic domains.

Neurophysiological signatures of prediction in language: A critical review of anticipatory negativities

Recent event-related potential (ERP) studies in language comprehension converge in finding anticipatory negativities preceding words or word segments that can be pre-activated based on either sentence contexts or phonological cues. We review these findings from different paradigms in the light of evidence from other cognitive domains in which slow negative potentials have long been associated with anticipatory processes and discuss their potential underlying mechanisms. We propose that this family of anticipatory negativities captures common mechanisms associated with the pre-activation of linguistic information both within words and within sentences. Future studies could utilize these anticipatory negativities in combination with other, well-established ERPs, to simultaneously track prediction-related processes emerging at different time intervals (before and after the perception of pre-activated input) and with distinct time courses (shorter-lived and longer-lived cognitive operations).

Dissociating the pre-activation of word meaning and form during sentence comprehension: Evidence from EEG representational similarity analysis

During language comprehension, the processing of each incoming word is facilitated in proportion to its predictability. Here, we asked whether anticipated upcoming linguistic information is actually pre-activated before new bottom-up input becomes available, and if so, whether this pre-activation is limited to the level of semantic features, or whether extends to representations of individual word-forms (orthography/phonology). We carried out Representational Similarity Analysis on EEG data while participants read highly constraining sentences. Prior to the onset of the expected target words, sentence pairs predicting semantically related words (financial "bank" - "loan") and form-related words (financial "bank" - river "bank") produced more similar neural patterns than pairs predicting unrelated words ("bank" - "lesson"). This provides direct neural evidence for item-specific semantic and form predictive pre-activation. Moreover, the semantic pre-activation effect preceded the form pre-activation effect, suggesting that top-down pre-activation is propagated from higher to lower levels of the linguistic hierarchy over time.

Sentence-final completion norms for 2925 Mexican Spanish sentence contexts

Sentence-final completion tasks serve as valuable tools in studying language processing and the associated predictive mechanisms. There are several established sentence-completion norms for languages like English, Portuguese, French, and Spanish, each tailored to the language it was designed for and evaluated in. Yet, cultural variations among native speakers of the same language complicate the claim of a universal application of these norms. In this study, we developed a corpus of 2925 sentence-completion norms specifically for Mexican Spanish. This corpus is distinctive for several reasons: Firstly, it is the most comprehensive set of sentence-completion norms for Mexican Spanish to date. Secondly, it offers a substantial range of experimental stimuli with considerable variability in terms of the predictability of word sentence completion (cloze probability/surprisal) and the level of uncertainty inherent in the sentence context (entropy). Thirdly, the syntactic complexity of the sentences in the corpus is varied, as are the characteristics of the final word nouns (including aspects of concreteness/abstractness, length, and frequency). This paper details the generation of the sentence contexts, explains the methodology employed for data collection from a total of 1470 participants, and outlines the approach to data analysis for the establishment of sentence-completion norms. These norms provide a significant contribution to fields such as linguistics, cognitive science, and machine learning, among others, by enhancing our understanding of language, predictive mechanisms, knowledge representation, and context representation. The collected data is accessible through the Open Science Framework (OSF) at the following link: https://osf.io/js359/?view_only=bb1b328d37d643df903ed69bb2405ac0 .

Developmental Language Disorder as Syntactic Prediction Impairment

We provide evidence that children with Developmental Language Disorder (DLD) are impaired in predictive syntactic processing. In the current study, children listened passively to auditorily-presented sentences, where the critical condition included an unexpected "filled gap" in the direct object position of the relative clause verb. A filled gap is illustrated by the underlined phrase in "The zebra that the hippo kissed the camel on the nose…", rather than the expected "the zebra that the hippo kissed [e] on the nose", where [e] denotes the gap. Brain responses to the filled gap were compared to a control condition using adverb-relative clauses with identical substrings: "The weekend that the hippo kissed the camel on the nose [e]…". Here, the same noun phrase is not unexpected because the adverb gap occurs later in the structure. We hypothesized that a filled gap would elicit a prediction error brain signal in the form of an early anterior negativity, as we have previously observed in adults. We found an early (bilateral) anterior negativity to the filled gap in a control group of children with Typical Development (TD), but the children with DLD exhibited no brain response to the filled gap during the same early time window. This suggests that children with DLD fail to predict that a relativized object should correspond to an empty position after the relative clause verb, suggesting an impairment in predictive processing. We discuss how this lack of a prediction error signal can interact with language acquisition and result in DLD.