Zhen Liang

This study examines disrupted dynamic structure-function connectivity coupling in euthymic bipolar disorder patients compared to healthy controls, identifying regional and network-level abnormalities.

This study introduces DEFN, a novel approach using dynamic functional connectivity to identify emotion-specific neural signatures, improving classification accuracy for mood disorders.

This study shows that tRNS modulates prestimulus alpha and beta power, affecting visual perception, with alpha having a stronger effect under low fatigue.

This study develops an EEG neurofeedback-guided cognitive reappraisal training protocol for emotion regulation, showing improved performance for low positive valence stimuli with real-time feedback.

This study uses a pre-trained CNN to link video content to brain activations during movie watching, finding associations between CNN layers and specific brain regions.

This study performs a brain-wide GWAS to identify genetic loci associated with structural and functional brain phenotypes of pain sensitivity, finding candidate loci in the right insula and CYP2D6 gene.

The paper uses fMRI to decode sustained emotional states during naturalistic movie viewing and identifies specific functional connectivity patterns associated with happiness and sadness.

The paper introduces a large-scale EEG database and competition to study EEG commonality and variability across subjects, sessions, and tasks, aiming to improve machine learning algorithms for EEG-based biometrics.

This study investigates how EEG microstates are modulated by emotion dynamics and multimedia stimulation during video watching, revealing specific microstate patterns associated with different emotional states and content types.

This study evaluates ERP test-retest reliability in adolescents, finding that stronger group effects do not guarantee higher individual reliability and that latency jitter and trial variability influence this relationship.