Giulia Lara Poerio

This study examines brain-thought relationships during movie-watching, finding that sensory-related neural signatures are consistent across films, while memory-related processes vary with context and modeling approaches.

The paper examines the relationship between task context, thought patterns, and neural activity, finding that thought reliability varies with task context and is associated with MDN activity.

This study uses experience sampling to measure daily thought patterns and links them to mental health, finding an 'Intrusive Distraction' pattern associated with anxiety and linked to social connectedness.

The paper develops a method to map thought patterns onto brain activity during movie-watching and finds sensory and association cortex play key roles in engagement and distraction.

This study uses real-world experience sampling to analyze how daily activities influence thought patterns, finding that socializing and environmental factors shape ongoing thought.

This study identifies two distinct neural states during wakeful rest using machine learning and links them to specific psychological features like problem-solving and negative rumination.

The paper examines the role of the default mode network (DMN) in off-task thought by analyzing neural activity and self-reported experiences, finding no strong association with self or social content but suggesting a role in representing ongoing thought.

This study links neural state transitions during wakeful rest to patterns of ongoing thought and well-being.