Meishan Ai

This study benchmarks foundation models for resting-state fMRI time series in cognitive aging, finding mixed results on their utility for cognitive assessment and prediction.

This paper replicates and extends Puccetti et al. (2021) by examining age-related differences in affect and amygdala connectivity using fMRI and diary data.

This paper evaluates rsfMRI foundation models for identifying robust neural patterns predicting cognitive intervention outcomes in aging, showing improved performance over conventional methods.

This study finds bilingualism is linked to better executive function but not episodic memory in Mandarin-speaking older adults, with stronger benefits for those with cognitive impairments.

The paper develops and validates a Facial Signature Score (FSS) from facial dynamics during cognitive interventions to predict executive function response in older adults.

The paper investigates brain connectivity patterns associated with long-term smoking behavior change in older adults at risk for Alzheimer's disease.