Biology subjects

Hervais-Adelman, A.

Publications and source records attributed to Hervais-Adelman, A..

10 recordsLinked to original sources

bioRxiv2026

Decomposing Parts of Speech: Neural Encoding of Semantic and Grammatical Dimensions and Their Combinational Structure

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.

neuroscience↗

bioRxiv2026

Cerebral Encoding of Word Classes is Distributed and Context-Dependent

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.

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bioRxiv2026

Linguistic structure and probability are jointly encoded in high gamma power

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.

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bioRxiv2023

Auditory cortex anatomy reflects multilingual phonological experience

This study explores the relationship between the anatomy of the auditory cortex and multilingual experience, shedding light on the complex mechanisms of auditory processing in humans. Integrating previous research on auditory information processing and the impact of bi- and multilingualism on brain structure, we investigate how the morphology of auditory brain regions reflects individuals language experience and, more specifically, their phonological repertoire. Leveraging two distinct samples comprising over 200 participants, each exposed to between 1 and 7 languages encompassing 36 different languages, we explore whether the morphological variability of auditory brain regions reflects individual language experience, specifically focusing on the phonological repertoire. Additionally, we examine the potential influence of typological distances between languages spoken by multilingual individuals on the neural signatures of multilingualism within the auditory cortex. Our findings revealed a relationship between the average thickness of the left and right second transverse temporal gyrus (TTG) and participants language experience. Model comparisons demonstrated that the inclusion of phoneme-level information in the language experience index accounted for the greatest variance in average TTG thickness (bilaterally). The direction of this effect was negative, indicating that a more extensive and more phonologically diverse language experience was associated with thinner cortices in the second TTG. Across two independent datasets, we provide robust evidence linking the degree of language experience and typological distance between languages to cortical thickness in early auditory brain regions. We propose that this phenomenon may reflect experience-driven pruning and neural efficiency, warranting further investigation through longitudinal studies of language acquisition. Moreover, our findings support the notion that experiences with typologically similar languages differ from those with typologically distant languages, offering valuable insights into the intricate relationship between language diversity and brain structure. Our findings also indicate that early auditory regions seem to represent phoneme-level cross-linguistic information, contrary to the most established models of language processing in the brain, which suggest that phonological processing happens in more lateral posterior STG and STS.

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bioRxiv2021

Categorical encoding of speech sounds: beyond auditory cortices

Which processes in the human brain lead to the categorical perception of speech sounds? Investigation of this question is hampered by the fact that categorical speech perception is normally confounded by acoustic differences in the stimulus. By using ambiguous sounds, however, it is possible to dissociate acoustic from perceptual stimulus representations. Twenty-seven normally hearing individuals took part in an fMRI study in which they were presented with an ambiguous syllable (intermediate between /da/ and /ga/) in one ear and with disambiguating acoustic feature (third formant, F3) in the other ear. Multi-voxel pattern searchlight analysis was used to identify brain areas that consistently differentiated between response patterns associated with different syllable reports. By comparing responses to different stimuli with identical syllable reports and identical stimuli with different syllable reports, we disambiguated whether these regions primarily differentiated the acoustics of the stimuli or the syllable report. We found that BOLD activity patterns in left perisylvian regions (STG, SMG), left inferior frontal regions (vMC, IFG, AI), left supplementary motor cortex (SMA/pre-SMA), and right motor and somatosensory regions (M1/S1) represent listeners syllable report irrespective of stimulus acoustics. Most of these regions are outside of what is traditionally regarded as auditory or phonological processing areas. Our results indicate that the process of speech sound categorization implicates decision-making mechanisms and auditory-motor transformations. HighlightsO_LIAmbiguous dichotic syllables elicit distinct percepts of identical stimuli C_LIO_LIMultivariate searchlight analysis reveals syllabic-category sensitive brain areas C_LIO_LICategorical responses arise in non-auditory cortical areas including motor areas C_LIO_LISMA is a possible locus for transforming sensory signals into perceptual decisions C_LI

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bioRxiv2021

How does literacy affect speech processing? Not by enhancing cortical responses to speech, but by promoting connectivity of acoustic-phonetic and graphomotor cortices.

Previous research suggest that literacy, specifically learning alphabetic letter-to-phoneme mappings, modifies online speech processing, and enhances brain responses to speech in auditory areas associated with phonological processing (Dehaene et al., 2010). However, alphabets are not the only orthographic systems in use in the world, and hundreds of millions of individuals speak languages that are not written using alphabets. In order to make claims that literacy per se has broad and general consequences for brain responses to speech, one must seek confirmatory evidence from non-alphabetic literacy. To this end, we conducted a longitudinal fMRI study in India probing the effect of literacy in Devanagari, an abubgida, on functional connectivity and cerebral responses to speech in 91 variously literate Hindi-speaking individuals. Twenty-two completely illiterate participants underwent six months of reading and writing training. Devanagari literacy increases functional connectivity between acoustic-phonetic and graphomotor brain areas, but we find no evidence that literacy changes the way speech is processed, either in cross-sectional or longitudinal analyses. These findings shows that a radical reconfiguration of the neurofunctional substrates of online speech processing is not a universal result of learning to read, and raise the possibility that writing, not only reading, may be instrumental in moulding literate speech perception. Significance StatementIt has come to be accepted that a consequence of being able to read is enhanced auditory processing of speech, reflected by increased cortical responses in areas associated with phonological processing. Here we find no relationship between literacy and the magnitude of brain response to speech stimuli in individuals who speak Hindi, which is written using a non-alphabetic script, Devanagari - an abugida. We propose that the exact nature of the script under examination must be considered before making sweeping claims about the consequences of literacy for the brain. Further, we find evidence that literacy enhances functional connectivity between auditory processing areas and graphomotor areas, suggesting a mechanism whereby learning to write, not only to read, might influence speech perception.

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bioRxiv2019

The Noise-Resilient Brain: Resting-State Oscillatory Activity Predicts Words-In-Noise Recognition

The role of neuronal oscillations in the processing of speech has recently come to prominence. Since resting-state (RS) brain activity has been shown to predict both task-related brain activation and behavioural performance, we set out to establish whether inter-individual differences in spectrally-resolved RS-MEG power are associated with variations in words-in-noise recognition in a sample of 88 participants made available by the Human Connectome Project. Positive associations with resilience to noise were observed with power in the range 21 and 29Hz in a number of areas along the left temporal gyrus and temporo-parietal association areas peaking in left posterior superior temporal gyrus (pSTG). Significant associations were also found in the right posterior superior temporal gyrus in the frequency range 30 to 40Hz. We propose that individual differences in words-in-noise performance are related to baseline excitability levels of the neural substrates of phonological processing. HighlightsO_LIPower of resting MEG activity predicts Words-In-Noise recognition performance C_LIO_LISignificant associations in higher beta and lower gamma frequency band C_LIO_LIStrongest in left-lateralised perisylvian cluster peaking in posterior STG C_LIO_LIEffects are spectrally and spatially consistent with phoneme-level processing C_LI

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bioRxiv2019

Resolving the connectome - Spectrally-specific functional connectivity networks and their distinct contributions to behaviour

The resting brain exhibits spontaneous patterns of activity that reflect features of the underlying neural substrate. Examination of inter-areal coupling of resting state oscillatory activity has revealed that the brains resting activity is composed of functional networks, whose topographies differ depending upon oscillatory frequency, suggesting a role for carrier frequency as a means of creating multiplexed, or functionally segregated, communication channels between brain areas. Using canonical correlation analysis, we examined spectrally resolved resting-state connectivity patterns derived from MEG recordings to determine the relationship between connectivity intrinsic to different frequency channels and a battery of over a hundred behavioural and demographic indicators, in a group of 89 young healthy participants. We demonstrate that each of the classical frequency bands in the range 1-40Hz (delta, theta, alpha, beta and gamma) delineates a subnetwork that is behaviourally relevant, spatially distinct, and whose expression is either negatively or positively predictive of individual traits, with the strongest link in the alpha band being negative and networks oscillating at different frequencies, such as theta, beta and gamma carrying positive function.

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bioRxiv2017

Gating by induced α-γ asynchrony in selective attention

Visual selective attention operates through top-down mechanisms of signal enhancement and suppression, mediated by -band oscillations. The effects of such top-down signals on local processing in primary visual cortex (V1) remain poorly understood. In the present work, we characterize the interplay between large-scale interactions and local activity changes in V1 that orchestrates selective attention, using Granger-causality and phase-amplitude coupling (PAC) analysis of EEG source signals. The task required participants to either attend to or ignore oriented gratings. Results from time-varying, directed connectivity analysis revealed frequency specific effects of attentional selection: bottom-up {gamma}-band influences from visual areas increased rapidly in response to attended stimuli while distributed top-down -band influences originated from parietal cortex in response to ignored stimuli. Importantly, the results revealed a critical interplay between top-down parietal signals and -{gamma} PAC in visual areas. Parietal -band influences disrupted the -{gamma} coupling in visual cortex, which in turn reduced the amount of {gamma}-band outflow from visual areas. Our results are a first demonstration of how directed interactions affect cross-frequency coupling in downstream areas depending on task demands. These findings suggest that parietal cortex realizes selective attention by disrupting cross-frequency coupling at target regions, which prevents them from propagating task-irrelevant information.

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bioRxiv2017

Beyond Bilingualism: multilingual experience correlates with caudate volume

The multilingual brain must implement mechanisms that serve to select the appropriate language as a function of the communicative environment. Engaging these mechanisms on a regular basis appears to have consequences for brain structure and function. Studies have implicated the caudate nuclei as important nodes in polyglot language control processes, and have also shown structural differences in the caudate nuclei in bilingual compared to monolingual populations. However, the majority of published work has focused on the categorical differences between monolingual and bilingual individuals, and little is known about whether these findings extend to multilingual individuals, who have even greater language control demands. In the present paper, we present an analysis of the volume and morphology of the caudate nuclei in 75 multilingual individuals who speak three or more languages. Volumetric analyses revealed a significant relationship between multilingual experience and right caudate volume, as well as a marginally-significant relationship with left caudate volume. Vertexwise analyses revealed a significant enlargement of dorsal and anterior portions of the left caudate nucleus having connectivity to executive brain regions, as a function of multilingual expertise. These results suggest that multilingual expertise might exercise a continuous impact on the brain, and that as additional languages beyond a second are acquired, the additional demands for control result in modifications to brain structures associated with language management processes.

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