Biology subjects

Pallier, C.

Publications and source records attributed to Pallier, C..

9 recordsLinked to original sources

bioRxiv2026

Distinct cortical patches for syntactic and semantic composition in the human brain

Although the brain areas for language processing are well delimited, whether lexical-semantic and syntactic processes are spatially segregated remains debated. To clarify this issue, we conducted two experiments using 7-Tesla functional MRI in 20 participants performing: a functional localizer involving reading sequences of words of increasing linguistic complexity; and a presentation of short, semantically impoverished three-word mini-sentences, flashed in a single glance (e.g., "he does it"), whose grammaticality and syntactic complexity was manipulated through syntactic movement. Our results reveal two functionally dissociable sets of cortical patches within the language system: one sensitive to syntactic structure even in the absence of meaning, and the other involved in semantic composition. This dual-network architecture was consistently observed in the majority of participants, although its precise anatomical localization varied. The two types of voxels coexisted even within a given brain region of the Glasser atlas. Results were confirmed using subject-specific analyses and region-by-condition interactions, as voxels in those two systems displayed markedly different responses to mini-sentences. Thus, high-resolution functional imaging reveals a division of labor between syntactic and semantic composition within the classical language network.

neuroscience↗

bioRxiv2026

Cortical localization and dynamics of elementary mathematical concepts

How the brain encodes abstract concepts remains poorly understood. Current theories propose that, in brains and computers alike, word meanings are represented by vectors of neural activation whose similarities reflect semantic relationships. Here, we tested whether this hypothesis also applies to abstract concepts of elementary mathematics. We collected behavioral, 7 Tesla functional MRI and magneto-encephalography (MEG) data and used representational similarity analysis to ask where, when and how fifteen concepts of integers, fractions, and geometric shapes are encoded in the adult brain. Behavioral similarity ratings revealed a rich conceptual structure characterized by both categorical distinctions (numbers vs shapes, integers vs fractions), a numerical distance effect for integers, and systematic correspondences between items involving the same number (e.g. three, third, triangle). Functional MRI identified a bilateral cortical network whose neural encodings of concepts correlated with their semantic similarity, overlapping with classic math-responsive regions and encompassing IPS and ITG as well as dorsolateral prefrontal cortex (dlPFC). A double dissociation was observed, with a preference for arithmetic in the right anterior intraparietal sulcus (IPS), and for geometry in left inferior temporal gyrus (ITG) and bilateral posterior IPS. MEG revealed that a semantic neural code common to written words and symbols is activated by about 230 ms, again primarily distinguishing integers, fractions and geometry concepts. Together, these findings suggest that mathematical concepts are organized in the brain along both categorical and numerical dimensions, with overlapping but partially distinct sites supporting arithmetic and geometry domains.

neuroscience↗

bioRxiv2025

Languages of the brain: fMRI dissection of the amodal networks for language, mathematics, and social knowledge

The ability to compose complex mental representations by recombining simpler primitives is a characteristic of the human brain that manifests itself in a variety of domains such as spoken or written language, mathematics, or social reasoning. While it is known that these domains rest on partially distinct brain networks, they are rarely investigated together in the same paradigm. Here, we present a systematic functional MRI study of written and spoken word and sentence processing in each of these domains. In a true-false judgment task, adult participants were presented with a hierarchy of meaningless and meaningful stimuli bearing on various domains of general semantic knowledge and mathematics. The results show that distinct brain regions are activated by (1) syntax and semantics; (2) math versus non-math knowledge; (3) different domains of mathematics, such as geometry versus arithmetic; (4) social knowledge versus other knowledge. All of these regions are activated essentially identically in the written and spoken modalities. The results were replicated in a group of adolescents. Our experiments show that the human brain comprises distinct amodal networks for various domains of linguistic and semantic knowledge, and provide a simple paradigm to dissect them within a short fMRI session.

neuroscience↗

bioRxiv2025

An fMRI study of composition in noun and verb phrases

How do the language areas of the human brain combine multiple words into meaningful phrases and sentences remains ill-understood. Here, to address this question, we determined the response profile of temporal and inferior frontal language areas to the composition of up to four words into phrases. We tested whether brain activity increases with the number of merged words, and whether this profile differs for noun and verb phrases. To this aim, we used fMRI to quantify the brain responses to individual noun and verb phrases of varying length and to tightly matched word lists. Increasing phrase length was associated to an increase in activation in all regions of the temporo-frontal language network. The effect was more pronounced for phrases built around verbs than for phrases built around nouns, suggesting that verbs involve a more complex syntactic tree structure than nouns. Even with word lists, several regions, notably the inferior frontal gyrus (IFG) pars triangularis and opercularis and the posterior superior temporal sulcus showed clear increases in activity with the length of sequences, although the words could not be merged into phrases. By contrast, other regions (IFG pars orbitalis, anterior temporal lobe, temporo-parietal junction) did not react to scrambled word lists. Those different functional response profiles inform theories of how composition is implemented in the human brain.

neuroscience↗

bioRxiv2022

Does the visual word form area split in bilingual readers? A millimeter-scale 7T fMRI study

In expert readers, a brain region known as the visual word form area (VWFA) is highly sensitive to written words, exhibiting a posterior-to-anterior gradient of increasing sensitivity to orthographic stimuli whose statistics match those of real words. Using high-resolution 7T fMRI, we ask whether, in bilingual readers, distinct cortical patches specialize for different languages. In 21 English-French bilinguals, unsmoothed 1.2 mm fMRI revealed that the VWFA is actually composed of several small cortical patches highly selective for reading, with a posterior-to-anterior word similarity gradient, but with near-complete overlap between the two languages. In 10 English-Chinese bilinguals, however, while most word-specific patches exhibited similar reading specificity and word-similarity gradients for reading in Chinese and English, additional patches responded specifically to Chinese writing and, surprisingly, to faces. Our results show that the acquisition of multiple writing systems can indeed tune the visual cortex differently in bilinguals, sometimes leading to the emergence of cortical patches specialized for a single language.

neuroscience↗

bioRxiv2022

Graph theoretical analysis reveals the adaptive role of the left ventral occipito-temporal cortex in the brain networks during speech processing

The left ventral occipito-temporal cortex (left-vOT) plays a key role in reading. Several studies have also reported its activation during speech processing, suggesting that it may play a role beyond written word recognition. Here, we adopt a graph theoretical analysis to investigate the functional role of this area in the whole-brain network while participants processed spoken sentences in different tasks. We find that its role and interactions with other areas changes in an adaptive manner. In a low-level speech perception task, the left-vOT is part of the visual network and acts as a connector that supports the communication with other cognitive systems. When speech comprehension is required, the area becomes a connector within the sensorimotor-auditory network typically recruited during speech processing. However, when comprehension is compromised due to degradation of speech input, the area disengages from the sensorimotor-auditory network. It becomes part of the visual network again and turns from connector into a simple peripheral node. These varying connectivity patterns are coherent with the Interactive Account considering the left-vOT as a convergent zone with multiple functions and interaction patterns that depend on task demands and the nature of sensory input.

neuroscience↗

bioRxiv2021

Le Petit Prince: A multilingual fMRI corpus using ecological stimuli

Neuroimaging using more ecologically valid stimuli such as audiobooks has advanced our understanding of natural language comprehension in the brain. However, prior naturalistic stimuli have typically been restricted to a single language, which limited generalizability beyond small typological domains. Here we present the Le Petit Prince fMRI Corpus (LPPC-fMRI), a multilingual resource for research in the cognitive neuroscience of speech and language during naturalistic listening (Open-Neuro: ds003643). 49 English speakers, 35 Chinese speakers and 28 French speakers listened to the same audiobook The Little Prince in their native language while multi-echo functional magnetic resonance imaging was acquired. We also provide time-aligned speech annotation and word-by-word predictors obtained using natural language processing tools. The resulting timeseries data are shown to be of high quality with good temporal signal-to-noise ratio and high inter-subject correlation. Data-driven functional analyses provide further evidence of data quality. This annotated, multilingual fMRI dataset facilitates future re-analysis that addresses cross-linguistic commonalities and differences in the neural substrate of language processing on multiple perceptual and linguistic levels.

neuroscience↗

bioRxiv2021

Neural correlates of semantic number: A cross-linguistic investigation

One aspect of natural language comprehension is understanding how many of what or whom a speaker is referring to. While previous work has documented the neural correlates of general number comprehension and quantity comparison, we investigate semantic number from a cross-linguistic perspective with the goal of identifying cortical regions involved in distinguishing plural from singular nouns. We use three fMRI datasets in which Chinese, French, and English native speakers listen to an audiobook of a childrens story in their native language. We select these three languages because they differ in their number semantics. While Chinese lacks nominal pluralization, French and English nouns are overtly marked for number. We find a number of known semantic processing regions in common, including dorsomedial prefrontal cortex and the pars orbitalis, in which cortical activation is greater for plural than singular nouns and posit a cross-linguistic role for number in semantic comprehension.

neuroscience↗

bioRxiv2018

Shared genetic aetiology between cognitive performance and brain activations in language and math tasks

Cognitive performance is highly heritable. However, little is known about common genetic influences on cognitive ability and brain activation when engaged in a cognitive task. The Human Connectome Project (HCP) offers a unique opportunity to study this shared genetic etiology with an extended pedigree of 785 individuals. To investigate this common genetic origin, we took advantage of the HCP dataset, which includes both language and mathematics activation tasks. Using the HCP multimodal parcellation, we identified areals in which inter-individual functional MRI (fMRI) activation variance was significantly explained by genetics. Then, we performed bivariate genetic analyses between the neural activations and behavioral scores, corresponding to the fMRI task accuracies, fluid intelligence, working memory and language performance. We observed that several parts of the language network along the superior temporal sulcus, as well as the angular gyrus belonging to the math processing network, are significantly genetically correlated with these indicators of cognitive performance. This shared genetic etiology provides insights into the brain areas where the human-specific genetic repertoire is expressed. Studying the association of polygenic risk scores, using variants associated with human cognitive ability and brain activation, would provide an opportunity to better understand where these variants are influential.

neuroscience↗