HAGIO, Shota Associate Professor
|Graduate School Department /Course /Field||Human Coexistence/Cognitive and Behavioral Sciences/Behavioral Physiology|
|Undergraduate School||Division of Cognitive and Information Sciences|
|Research areas||Motor Control, Neurophysiology|
|Keywords||Motor Learning, Motor Control, Synergy, Neural Network Model|
|Major publications||Hagio S et al. Muscle synergies of multi-directional postural control in astronauts on Earth after a long-term stay in space. Journal of Neurophysiology, in press.
Hagio S, Nakazato M, Kouzaki M. Modulation of spatial and temporal modules in lower limb muscle activations during walking with simulated reduced gravity. Scientific Reports, 11(1), 2021.
Hagio S, Kouzaki M. Visuomotor Transformation for the Lead Leg Affects Trail Leg Trajectories During Visually Guided Crossing Over a Virtual Obstacle in Humans. Frontiers in Neuroscience, 14, 2020.
Hagio S, Kouzaki M. Modularity speeds up motor learning by overcoming mechanical bias in musculoskeletal geometry. Journal of Royal Society Interface, 15(147), 2018.
Hagio S, Kouzaki M. Action direction of muscle synergies in three-dimensional force space. Frontiers in Bioengineering and Biotechnology, 3(187), 2015.
Hagio S, Kouzaki M. Recruitment of muscle synergies is associated with endpoint force fluctuations during multi-directional isometric contractions. Experimental Brain Research, 233(6): 1811-1823, 2015.
Hagio S, Fukuda M, Kouzaki M. Identification of muscle synergies associated with gait transition in humans. Frontiers in Human Neuroscience, 9(48):1-12, 2015.
Hagio S, Kouzaki M. The flexible recruitment of muscle synergies depends on the required force generating capability. Journal of Neurophysiology, 112(2): 316-327, 2014.
Hagio S, Nagata K, Kouzaki M. Region specificity of rectus femoris muscle for force vectors in vivo. Journal of Biomechanics, 45(1): 179-182, 2012.
|Professional societies/Research and synergic activities||・Society for Neuroscience
・International Society of Electrophysiology and Kinesiology