Feng Vankee Lin

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 study identifies early functional connectivity changes in MDD patients treated with antidepressants or placebo, revealing common and distinct treatment effects.

The paper uses fMRI and AI models to show that the medial temporal default mode network encodes visual imagery from autobiographical memories.

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 uses fMRI to show that imagined social and solitary scenarios activate different patterns of the frontoparietal and default mode networks, revealing a gradient that reflects semantic differences in internal cognitive states.

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

This study identifies a functional connectivity signature, ARC, that distinguishes superagers from AD patients and predicts cognitive decline and amyloid-beta accumulation.

The paper develops a method to identify clique subgraphs in structural brain networks for classification, applied to study differences in crystallized cognition between adolescents.