Lin Wang

This paper uses GPT-3 to quantify global vs. local context sensitivity in speech from schizophrenia patients and finds disorganized speech shows insensitivity to global context, predicting positive thought disorder.

This paper proposes a predictive coding model to explain the N400 event-related potential by framing it as lexico-semantic prediction error during language comprehension.

The paper uses MEG and ERPs to study how the brain processes expected, unexpected, and implausible words during language comprehension, interpreting results through a predictive coding framework.

The paper proposes a pipelining mechanism using alpha oscillations to coordinate visual exploration and reading by timing saccades, visual recognition, and previewing within a 150ms window.

The paper uses MEG and EEG with RSA to show that brain activity patterns differ when predicting animate versus inanimate nouns during language comprehension, indicating semantic prediction of coarse-grained features.

The paper investigates whether specific semantic representations are pre-activated in the brain before encountering predicted words in sentences, finding similar neural patterns when the same words are predicted.