Alexis Hervais-Adelman

Conventional part-of-speech (PoS) labels such as nouns, verbs and adjectives conflate lexical-semantic roots, grammatical functions, and their combinations, making it unclear whether neural sensitivity to PoS reflects either dimension or the way they are combined. We adopted Croft’s typological framework to decompose major PoS classes into semantic root type and grammatical function and define prototypical nouns, verbs, and adjectives through the prototypical mappings between semantic root and grammatical function. We fitted time-resolved encoding models to magnetoencephalography (MEG) data from three participants who each listened to approximately ten hours of narrative speech. We examined the unique predictive contributions of semantic root, grammatical function, their interaction, and a binary prototypicality predictor, and whether the three prototypes exhibited distinct neural response dynamics. Semantic root and grammatical function contributed independently to neural responses during naturalistic language comprehension, with additional contributions from their interaction beyond the main effects. Root effects were predominantly left-lateralized, function effects were more bilateral, and interaction effects were concentrated in the left temporal and temporoparietal cortex, with overlap in left temporal regions. Further analyses revealed significant neural sensitivity to the distinction between prototypical and nonprototypical combinations in two of the three datasets. Prototypical nouns and verbs showed distinct coefficient time courses in all three participants, most consistently in left superior temporal cortex, whereas adjective-related contrasts were less consistent. These within-participant findings support a decompositional account of neural word-class sensitivity involving semantic, grammatical, and the mappings between them within distributed, partially overlapping cortical networks.

A widely accepted framework in multilingual control is the inhibitory control model (ICM, Green, 1998). According to this framework, the level of inhibition required to suppress a language is dependent upon the dominance of that language, such that a more dominant language requires more inhibition. A study by de Bruin and colleagues (2023) evaluated L1 and L3 intrusions in L2 target trials in a speeded trilingual picture naming task, reporting more intrusions from L3 than L1, consistent with lower inhibition of L3. Here, we expand on this and investigate whether patterns of cross-linguistic interference and reaction times (RT) in all three languages can be accounted for by the ICM. Furthermore, we explore how proficiency and age of acquisition (AoA) influence these patterns. Sixty-nine participants with some proficiency in English (NL1=22), French (NL1=21), and German (NL1=26) completed a trilingual speeded picture naming task. Patterns of intrusions did not fully align with a dominance-based inhibitory account: L2 produced more intrusions than (expected) L3 in L1 target trials. Analysis of the role of proficiency and AoA showed that intrusions are more likely between languages with similar proficiencies and AoAs, with an interaction such that languages with mismatched profiles (early AoA/low proficiency or late AoA/high proficiency) are most likely to intrude. RT patterns revealed asymmetric switch costs and a large influence of AoA. The pattern of results points to the need for a more nuanced understanding of the factors influencing how languages are accessed and controlled, beyond the construct of an ordinal dominance hierarchy.

Word classes such as nouns, verbs, and adjectives are fundamental units of language, but their neural encoding remains unclear. Here, we investigate whether word classes are processed as invariant, context-independent lexical categories or depend on sentence context during language processing. We analyse source-localized magnetoencephalography (MEG) data from 200 native Dutch participants who read or listened to sentences and their scrambled counterparts (word lists) from the MOUS dataset. Time-resolved encoding models are used to predict neural responses from major word classes (noun, verb, adjective) and other linguistic variables including word frequency, surprisal, entropy, word length, and ordinal position. Across modalities, we observe a significant interaction between word class and context (sentences vs. word lists), manifest as dynamic modulation of neural responses in a widespread cortical network including bilateral perisylvian, frontal, and midline regions previously implicated in lexicosemantic, structural, and pragmatic processing. This interaction emerges early and reappears later in processing, with distinct temporal profiles for reading and listening. Within-condition effects reveal that word class contributes to neural responses at the level of individual words, but this contribution is context-dependent: it is robust in sentences across modalities and in word-list reading, but absent in auditory word lists. These results indicate that word-class encoding is shaped by the interaction between word-level properties and sentence context during real-time language processing.

During speech comprehension, the brain dynamically infers a hierarchy of increasingly abstract representations from the sensory input. An important step in the inferential hierarchy is the combination of words to form phrases and sentences. Whether this process is driven primarily by statistical patterns in the linguistic input, or by a mechanism that combines words into hierarchical representations, is a subject of considerable debate that has regained importance with the arrival of large language models. This study investigates whether local cortical activity (high gamma power; 70-150 Hz) from intracranial recordings is jointly modulated by lexical probability and syntactic structure; and whether lexical probability affects the inference of syntactic structure. To this end, an open dataset of electrocorticography recordings is analyzed with multivariate temporal response functions and a model comparison approach. The results indicate that high gamma power is sensitive to multi-word estimates of constituency structure and lexical probability estimates, both in isolation and jointly. The temporal response functions suggest that syntactic structure building depends on interregional communication between regions connected through dorsal- and ventral streams. Furthermore, the study provides evidence that bottom-up syntactic information is less likely to be encoded by neural populations that strongly code for lexical probability measures, while top-down syntactic information shares neural resources with lexical uncertainty. We suggest that lexical uncertainty modulates the weighting of anticipatory structural information. With this, the current study supports models that suggest that cues are leveraged flexibly in a feed-forward and feed-back fashion during speech comprehension.

Whether human language evolved via a gestural or a vocal route remains an unresolved and contentious issue. Given the existence of two preconditions—a “language faculty” and the capacity for imitative learning both vocally and manually—there is no compelling evidence for gesture being inherently inferior to vocalization as a mode of linguistic expression; indeed, signed languages are capable of the same expressive range as spoken ones. Here, we revisit this conundrum, championing recent methodological advances in human neuroimaging (specifically, in utero functional magnetic resonance imaging) as a window into the role of the prenatal gestational period in language evolution, a critical, yet currently underexplored environment in which fetuses are exposed to, and become attuned to, spoken language. In this Unsolved Mystery, we outline how, compared to visual sensitivity, the ontogenically earlier development of auditory sensitivity, beginning in utero and persisting for several months post-partum, alongside the relative permeability of the uterine environment to sound, but not light, may constitute a small but significant contribution to the current dominance of spoken language.

This chapter focuses on Magnetic Resonance Imaging (MRI) as a non-invasive method for investigating both brain structure and function. Structural and functional imaging are discussed separately due to their differing requirements and the distinct questions they can address. We begin by introducing the MRI method and relevant concepts. Following this, we provide a brief overview of current MRI studies, with a special emphasis on CTIS. Next, we explore conceptual and practical considerations, including methodological, ethical, and technical aspects, to guide those new to the field. Lastly, we discuss the advantages and disadvantages of MRI. Our overall aim is to emphasize the need for standards that facilitate careful experimental design and meaningful data.

Interpreting, and more narrowly simultaneous interpreting, has over the last two decades become a focus of research for cognitive neuroscientists studying the neural bases of language and multilingualism, as well as those with an interest in the consequences of expertise in language control for cognition. Task-related functional imaging studies have begun to reveal the networks of brain areas engaged during interpreting tasks, while resting-state imaging and structural imaging studies reveal differences between the brains of experienced interpreters and non-interpreter multilingual individuals. Although current results are heterogeneous, they overall indicate that simultaneous interpreting calls not only upon cerebral resources associated with speech comprehension and production, but also in addition to brain structures responsible for the control and coordination of domain-general executive functions. This chapter introduces the methods of cognitive neuroscience of language and reviews the literature on the neuroscience of simultaneous interpreting.

There is a robust positive relationship between reading skills and the time to name aloud an array of letters, digits, objects, or colors as quickly as possible. A convincing and complete explanation for the direction and locus of this association remains, however, elusive. In this study, we investigated rapid automatized naming (RAN) of everyday objects and basic color patches in neurotypical illiterate and literate adults. Literacy acquisition and education enhanced RAN performance for both conceptual categories but this advantage was much larger for (abstract) colors than everyday objects. This result suggests that (a) literacy/education may be causal for serial rapid naming ability of non-alphanumeric items and (b) differences in the lexical quality of conceptual representations can underlie the reading-related differential RAN performance. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Speech elicits brain activity time-locked to its amplitude envelope. The resulting speech-brain synchrony (SBS) is thought to be crucial to speech parsing and comprehension. It has been shown that higher speech-brain coherence is associated with increased speech intelligibility. However, studies depending on the experimental manipulation of speech stimuli do not allow conclusion about the causality of the observed tracking. Here, we investigate whether individual differences in the intrinsic propensity to track the speech envelope when listening to speech-in-quiet is predictive of individual differences in speech-recognition-in-noise, in an independent task. We evaluated the cerebral tracking of speech in source-localized magnetoencephalography, at timescales corresponding to the phrases, words, syllables and phonemes. We found that individual differences in syllabic tracking in right superior temporal gyrus and in left middle temporal gyrus (MTG) were positively associated with recognition accuracy in an independent words-in-noise task. Furthermore, directed connectivity analysis showed that this relationship is partially mediated by top-down connectivity from premotor cortex—associated with speech processing and active sensing in the auditory domain—to left MTG. Thus, the extent of SBS—even during clear speech—reflects an active mechanism of the speech processing system that may confer resilience to noise.