Refael Tikochinski

This study uses fMRI to show that sentence boundaries during speech comprehension elicit a distinct neural response beyond speech properties, supporting active sentence segmentation.

This paper introduces Dementia Language Models (DeLMs) that generate patient-like narratives and predict cognitive impairment, validated by neurologists and MMSE scores.

This study shows that the multiple-demand network encodes content-sensitive linguistic representations during naturalistic comprehension, independent of cognitive demand.

The paper shows humans prefer semantic information that strengthens the small-world topology of knowledge, enhancing cognitive processing and valuation in the brain.

This study compares how LLMs and the brain process narrative context, introducing an incremental LLM that better predicts DMN neural activity.

This paper uses fine-tuned deep language models to model differences in narrative interpretation based on listeners' perspectives, showing alignment with neural responses and cognitive networks.