Jinsong Wu

The paper investigates how human temporal cortex integrates facial and acoustic cues during speech, revealing distinct frequency-dependent integration regimes in different regions.

The paper develops population-specific brain charts for Chinese individuals, revealing distinct neurodevelopmental patterns compared to Western populations and showing better performance in predicting brain phenotypes.

This paper investigates the neural coding of articulatory dynamics during speech imagery and production, revealing a hierarchical spatiotemporal organization and developing a model to decode speech from neural signals.

This study uses deep neural networks to model neural coding in the human auditory pathway and finds that DNN representations align with biological auditory processing.

The paper identifies four low-dimensional states of resting-state language networks, showing domain-separated dynamics and cognitive relevance.