Papers
1
Total Citations
10
H-Index
1
About
Ying Zeng investigates the intersection of affective neuroscience and cognitive engineering, with a primary focus on how depressive emotion (DE) disrupts spatial cognition. In her most cited work, "EEG Network Analysis of Depressive Emotion Interference Spatial Cognition Based on a Simulated Robotic Arm Docking Task" (2023, 10 citations), Zeng pioneers the use of EEG network analysis to uncover the brain network mechanisms underlying DE-induced spatial impairment. This study addresses a critical gap in understanding how subclinical depressive symptoms—those not meeting full diagnostic criteria—alter neural connectivity during complex motor-cognitive tasks. By employing a simulated robotic arm docking paradigm, she bridges real-world human-robot interaction with neurophysiological assessment, offering novel insights into the neural signatures of cognitive interference in affective states. Zeng’s work is notable for its methodological innovation, combining graph theory with ecological task design to reveal how DE disrupts frontoparietal network efficiency. Her findings have implications for early detection of cognitive decline in at-risk populations and for designing adaptive human-machine interfaces. With her research gaining traction in clinical neuroscience and engineering psychology, Zeng is establishing herself as a key voice in understanding how mood states shape neural dynamics during goal-directed behavior.
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