Yuanlong Gao

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About

Yuanlong Gao investigates the intersection of affective neuroscience and cognitive engineering, with a primary focus on how depressive emotion (DE) impacts spatial cognition and brain network dynamics. In his most-cited work, "EEG Network Analysis of Depressive Emotion Interference Spatial Cognition Based on a Simulated Robotic Arm Docking Task" (2023, 10 citations), Gao employs EEG-based network analysis to uncover the neural mechanisms by which subclinical depressive symptoms disrupt spatial processing during a complex motor-cognitive task. This research is notable for bridging the gap between mood disorders and real-world performance, using a simulated robotic arm docking paradigm to reveal how DE alters functional connectivity in the brain. By targeting individuals with depressive symptoms who do not meet full diagnostic criteria, Gao addresses an often-overlooked population, offering insights that could inform early intervention strategies. His work has been cited in emerging studies on affective computing and neuroergonomics, establishing him as a rising voice in understanding how emotional states shape cognitive-motor integration.