Christophe Pallier

This study uses fMRI to identify two distinct cortical networks in the human brain for syntactic and semantic processing during language tasks.

This study investigates how the brain encodes elementary mathematical concepts using fMRI and MEG, finding semantic similarity in neural activations across arithmetic and geometry domains.

This study uses fMRI to identify distinct brain networks for language, mathematics, and social knowledge, showing similar activation patterns across written and spoken modalities.

The paper uses fMRI to study how brain regions respond to noun and verb phrases of varying lengths, finding greater activation for verb phrases.

The paper identifies category-preferring patches in the human orbitofrontal cortex using fMRI, showing similar organization and function to the ventral occipitotemporal cortex.

This study uses 7T fMRI to investigate whether bilingual readers have distinct cortical patches for different languages, finding overlapping but specialized regions for English-French and additional patches for English-Chinese.

This study uses graph theoretical analysis to show how the left ventral occipito-temporal cortex adapts its connectivity in brain networks during different speech processing tasks.

The paper introduces a multilingual fMRI corpus using the audiobook The Little Prince to study cross-linguistic differences in language processing.

The paper investigates neural correlates of semantic number across three languages, finding common activation patterns for plural vs. singular nouns.

The paper identifies shared genetic influences between cognitive performance and brain activation in language and math tasks using the HCP dataset.