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Journal of Neural Engineering
|
April 27, 2023
Magnetoencephalographic neurofeedback training decreases<i>β</i>-low-<i>γ</i>phase-amplitude coupling of the motor cortex of healthy adults: a double-blinded randomized crossover feasibility study
Nobuyuki Izutsu, Takufumi Yanagisawa, Ryohei Fukuma, et al.
Brain Research Bulletin
|
April 29, 2026
Decreased gamma band power and increased betagamma phaseamplitude coupling are characteristic of brain activity in patients with chronic spinal cord injury
Asaya Nishi, Takufumi Yanagisawa, Ryohei Fukuma, et al.
Journal of Neural Engineering
|
April 6, 2022
Abnormal phase-amplitude coupling characterizes the interictal state in epilepsy
Yuya Fujita, Takufumi Yanagisawa, Ryohei Fukuma, et al.
Communications Biology
|
May 21, 2025
Neurofeedback modulation of insula activity via MEG-based brain-machine interface: a double-blind randomized controlled crossover trial
Yuhao Wang, Ryohei Fukuma, Ben Seymour, et al.
Communications Biology
|
May 18, 2024
Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition
Ryohei Fukuma, Kei Majima, Yoshinobu Kawahara, et al.
Eneuro
|
January 11, 2019
Real-Time Neurofeedback to Modulate β-Band Power in the Subthalamic Nucleus in Parkinson's Disease Patients
Ryohei Fukuma, Takufumi Yanagisawa, Masataka Tanaka, et al.
Neurobiology of Disease
|
December 24, 2025
Wirelessly transmitted subthalamic nucleus signals decode endogenous pain levels in Parkinson's disease patients
Abdi Reza, Takufumi Yanagisawa, Naoki Tani, et al.
Frontiers in Human Neuroscience
|
November 20, 2015
Categorical discrimination of human body parts by magnetoencephalography
Misaki Nakamura, Takufumi Yanagisawa, Yumiko Okamura, et al.
Journal of Neural Engineering
|
April 15, 2020
Neural decoding of electrocorticographic signals using dynamic mode decomposition
Yoshiyuki Shiraishi, Yoshinobu Kawahara, Okito Yamashita, et al.
Frontiers in Neuroscience
|
July 28, 2018
Training in Use of Brain-Machine Interface-Controlled Robotic Hand Improves Accuracy Decoding Two Types of Hand Movements
Ryohei Fukuma, Takufumi Yanagisawa, Hiroshi Yokoi, et al.
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of 4
Search research articles
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Showing results (1-10 of 38) with videos related to
Sort By:
Page
of 4
Journal of Neural Engineering
|
April 27, 2023
Magnetoencephalographic neurofeedback training decreases<i>β</i>-low-<i>γ</i>phase-amplitude coupling of the motor cortex of healthy adults: a double-blinded randomized crossover feasibility study
Nobuyuki Izutsu, Takufumi Yanagisawa, Ryohei Fukuma, et al.
Brain Research Bulletin
|
April 29, 2026
Decreased gamma band power and increased betagamma phaseamplitude coupling are characteristic of brain activity in patients with chronic spinal cord injury
Asaya Nishi, Takufumi Yanagisawa, Ryohei Fukuma, et al.
Journal of Neural Engineering
|
April 6, 2022
Abnormal phase-amplitude coupling characterizes the interictal state in epilepsy
Yuya Fujita, Takufumi Yanagisawa, Ryohei Fukuma, et al.
Communications Biology
|
May 21, 2025
Neurofeedback modulation of insula activity via MEG-based brain-machine interface: a double-blind randomized controlled crossover trial
Yuhao Wang, Ryohei Fukuma, Ben Seymour, et al.
Communications Biology
|
May 18, 2024
Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition
Ryohei Fukuma, Kei Majima, Yoshinobu Kawahara, et al.
Eneuro
|
January 11, 2019
Real-Time Neurofeedback to Modulate β-Band Power in the Subthalamic Nucleus in Parkinson's Disease Patients
Ryohei Fukuma, Takufumi Yanagisawa, Masataka Tanaka, et al.
Neurobiology of Disease
|
December 24, 2025
Wirelessly transmitted subthalamic nucleus signals decode endogenous pain levels in Parkinson's disease patients
Abdi Reza, Takufumi Yanagisawa, Naoki Tani, et al.
Frontiers in Human Neuroscience
|
November 20, 2015
Categorical discrimination of human body parts by magnetoencephalography
Misaki Nakamura, Takufumi Yanagisawa, Yumiko Okamura, et al.
Journal of Neural Engineering
|
April 15, 2020
Neural decoding of electrocorticographic signals using dynamic mode decomposition
Yoshiyuki Shiraishi, Yoshinobu Kawahara, Okito Yamashita, et al.
Frontiers in Neuroscience
|
July 28, 2018
Training in Use of Brain-Machine Interface-Controlled Robotic Hand Improves Accuracy Decoding Two Types of Hand Movements
Ryohei Fukuma, Takufumi Yanagisawa, Hiroshi Yokoi, et al.
Page
of 4