Uehara , Kazumasa
|Department of Computer Science and Engineering
|Fields of Research
|Ph.D. (Hiroshima University)
|Japanese Neural Network Society, Japan Neuroscience Society, Japanese Society of Clinical Neurophysiology, Japan Society of Exercise and Sports Physiology, Society for Neuroscience, Japanese Society for Motor Control
Please append "tut.jp" to the end of the address above.
|Laboratory website URL
|Researcher information URL（researchmap）
ResearchOur lab conducts neuroscience research to elucidate the neural substrates underlying neural information processing for sensorimotor and cognitive control, as well as flexible decision-making. The actions and cognition we experience in our daily lives are based on the utilization of various neural information mechanisms, with myriad neurons in the brain. Despite scientific advancements, there remain many unknowns about the complex neural systems and the body. By combining psychophysics experiments, recordings of neural activity (MRI, EEG, Brain stimulation), and neuroinformatics, our lab aims to understand brain function. Based on our empirical findings, we develop apparatuses to support physical education and rehabilitation.
Theme1：Understanding neural substrates underlying cognitive motor control
Our lab conducts studies to understand the key components, including neural information dynamics, that play a role in cognitive and motor control. For instance, we have developed a model of speed-accuracy tradeoff and perceptual decision-making using neural signals obtained from fMRI and EEG. Additionally, we employ simultaneous EEG-TMS recordings to reveal causal relationships between our behavior and neural activity.
Selected publications and works
Uehara et al. (2022) Modulation of cortical beta oscillations influences motor vigor: A rhythmic TMS-EEG study. Human Brain Mapping, 1-15
Uehara et al. (2022) Precise motor rhythmicity relies on motor network responsivity. Cerebral Cortex, 1-16
Theme2：Understanding neural substrates underlying skilled movement
Through the use of psychophysical measurements, brain imaging, and neurophysiological approaches, we aim to clarify why top athletes, musicians, and other skilled performers are able to produce exceptional skills. This project will further our understanding of neural plasticity.
Selected publications and works
Uehara et al. (2023) Brain network flexibility as a predictor of skilled musical performance. Cerebral Cortex. 1-12
Uehara et al. (2019) Distinct roles of brain activity and somatotopic representation in pathophysiology of focal dystonia. Human Brain Mapping 40, 1738-1749
Furuya*, Uehara* et al. (2018) Aberrant cortical excitability explains the loss of hand dexterity in musician’s dystonia. The Journal of Physiology, 596, 2397-2411 *equally contributed author
We test the trustworthiness of Explainable AI (XAI) based on a causal approach via the human body. Using biological signals such as cortical neural activity and muscle activity obtained during human cognitive or motor tasks, AI (Deep Learning) identifies the most important biological features that play a crucial role in the given tasks. Using this feature extraction, we manipulate human cortical neural activity using non-invasive brain stimulation and manipulate electromyogram signals using the cyber-space during the tasks. This project will extend from laboratory research to clinical research to build a prototype system of XAI.
Title of class
Intelligent Information Mathematics, Computer Programming 1A, X Reality and Psychology Ⅱ