Gina R. Kuperberg

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.

This study shows that domain-general conflict monitoring predicts both behavioral and neural responses to linguistic errors during reading comprehension.

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 distinct neural responses to fulfilled and violated predictions at different levels of representation during language comprehension, identifying specific ERP components associated with each.

The paper investigates how saccadic eye movements influence cortical activity during a word recognition task, finding left-lateralized effects beyond visual stimulation alone.

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.