Yuelu Liu

This study uses EEG and fMRI with machine learning to show that affective pictures evoke valence-specific neural representations in retinotopic visual cortex, influenced by limbic and frontal connectivity.

This study shows that fear conditioning leads to sparser neural representations of threat cues in primary visual cortex, associated with changes in alpha oscillations and BOLD signals.

The paper uses machine learning to analyze fMRI data and identifies reward-related brain activity changes in MDD patients after dopaminergic enhancement.

The paper develops machine learning models using multimodal data to predict transdiagnostic psychiatric symptom severity, achieving high variance explanation and revealing key predictors.

The paper identifies transdiagnostic features shared across schizophrenia, bipolar disorder, and ADHD using machine learning on self-reported data, showing high predictive power for distinguishing patients from controls.