Yasunori Aoki | Electroencephalography | Research Excellence Award

Dr. Yasunori Aoki | Electroencephalography | Research Excellence Award

Nippon Life Hospital | Japan

Dr. Yasunori Aoki, MD, PhD, is a physician–scientist specializing in psychiatry and clinical neuroscience, currently affiliated with the Department of Psychiatry at Osaka University Graduate School of Medicine, Japan. With a strong interdisciplinary foundation, he was initially trained in physics before completing his medical education and advanced clinical neuroscience training, allowing him to integrate quantitative scientific approaches into clinical research. His academic and professional work centers on the clinical application of neurophysiological methods, particularly electroencephalography and magnetoencephalography, to better understand brain function and dysfunction. Dr. Aoki’s doctoral research focused on advanced EEG and neuronal activity topography analyses to predict treatment outcomes in neurological and psychiatric disorders, reflecting his commitment to translational research that bridges neuroscience and patient care. His research interests span psychiatry, cognitive neuroscience, and clinical neurophysiology, with particular emphasis on schizophrenia, dementia, epilepsy, autism, depression, and neurodevelopmental and neurodegenerative conditions. He is especially interested in brain oscillations, endophenotypes, resting-state networks, event-related potentials, and neuromodulation techniques such as transcranial magnetic stimulation. Through his work, Dr. Aoki aims to advance objective biomarkers and neurophysiological tools to improve diagnosis, prognosis, and therapeutic strategies in psychiatry and neurology.

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Featured Publications


PyCaret machine learning library with three preprocessing steps after eLORETA source estimation predicts Alzheimer’s disease

– NeuroImage: Reports

EEG Oscillatory Activity and Resting-State Networks Associated with Neurocognitive Function in Mild Traumatic Brain Injury

– Clinical EEG and Neuroscience

Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

– JMIR AI

Normalized Power Variance: A New Field Orthogonal to Power in EEG Analysis

– Clinical EEG and Neuroscience

Cortical electrical activity changes in healthy aging using EEG-eLORETA analysis

– NeuroImage: Reports