Théo Desbordes

This study uses MEG to investigate when and where modality-independent semantic representations emerge for images and words during encoding tasks.

The paper introduces geometric measures to analyze temporal changes in neural representations, showing they reveal dynamics not captured by traditional decoding methods.

The paper investigates how neural representations of sentences evolve, finding that meaningful sentences have higher dimensionality and specific dynamic patterns in both human brains and deep language models.