Angela Tam

The paper shows that brain network features predicting internalizing and externalizing traits differ between children and adults, with more similarity within categories in children and distinct features in adults.

This study assesses white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease by analyzing signal measures from different MRI contrasts and their associations with clinical variables.

This study compares the ability of anatomical, diffusion, and functional MRI to predict individual behavioral measures, finding that functional connectivity provides the best predictions, especially for cognition.

The paper identifies functional connectivity subtypes associated with ASD diagnosis and shows their generalizability across independent data.

Brain-behaviour correlations in ABCD are tiny (median |r|=0.01), so samples of typical size (N=25) give inflated, irreproducible results; estimates only stabilise around N⪆2,000.

The paper identifies shared and unique brain network features that predict cognition, personality, and mental health in children using resting and task-state functional connectivity.

The paper identifies a functional connectivity endophenotype that significantly increases ASD diagnosis risk and generalizes across independent data.

The paper identifies a predictive signature of cognition and brain atrophy for progression to Alzheimer’s dementia using machine learning, validated in two MCI cohorts with high positive predictive value.

The paper identifies subtypes of functional brain connectivity in older adults linked to Alzheimer's disease symptoms and risk factors.

This study reviews and analyzes functional connectivity changes in Alzheimer's disease and mild cognitive impairment using resting-state fMRI, finding consistent alterations in key networks.

The paper identifies consistent functional connectivity differences between normal aging and mild cognitive impairment across varied imaging protocols.