Masa aki Sato

Summary

Affiliation: ATR Computational Neuroscience Laboratories
Country: Japan

Publications

  1. pmc Brain activity underlying auditory perceptual learning during short period training: simultaneous fMRI and EEG recording
    Ana Cláudia Silva de Souza
    Universidade Federal de Sao Joao del Rei, Ouro Branco, Brazil
    BMC Neurosci 14:8. 2013
  2. ncbi request reprint Hierarchical Bayesian estimation for MEG inverse problem
    Masa aki Sato
    ATR Computational Neuroscience Laboratories, 2 2 2 Hikaridai, Seika, Soraku, Kyoto 619 0288, Japan
    Neuroimage 23:806-26. 2004
  3. doi request reprint Evaluation of hierarchical Bayesian method through retinotopic brain activities reconstruction from fMRI and MEG signals
    Taku Yoshioka
    National Institute of Information and Communications Technology, Soraku, Kyoto 619 0288, Japan
    Neuroimage 42:1397-413. 2008
  4. doi request reprint Reduction of global interference of scalp-hemodynamics in functional near-infrared spectroscopy using short distance probes
    Takanori Sato
    Nagaoka University of Technology, 1603 1 Kamitomioka, Nagaoka, Niigata 940 2188, Japan ATR Brain Information Communication Research Lab Group, 2 2 2 Hikaridai, Keihanna Science City, Kyoto 619 0288, Japan
    Neuroimage 141:120-32. 2016
  5. doi request reprint Cortical current source estimation from electroencephalography in combination with near-infrared spectroscopy as a hierarchical prior
    Takatsugu Aihara
    ATR Computational Neuroscience Laboratories, Kyoto 619 0288, Japan
    Neuroimage 59:4006-21. 2012
  6. doi request reprint Premotor cortex mediates perceptual performance
    Daniel Callan
    ATR Computational Neuroscience Laboratories, Kyoto, Japan
    Neuroimage 51:844-58. 2010
  7. pmc Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns
    Okito Yamashita
    ATR Computational Neuroscience Laboratories, Japan
    Neuroimage 42:1414-29. 2008
  8. doi request reprint Multi-subject and multi-task experimental validation of the hierarchical Bayesian diffuse optical tomography algorithm
    Okito Yamashita
    Neural Information Analysis Laboratories, ATR, 2 2 2 Hikaridai, Keihanna Science City, Kyoto 619 0288, Japan Brain Functional Imaging Technologies Group, CiNet, 1 4 Yamadaoka, Suita City, Osaka 565 0871, Japan Electronic address
    Neuroimage 135:287-99. 2016
  9. doi request reprint Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography
    Takeaki Shimokawa
    ATR Neural Information Analysis Laboratories, Kyoto 619 0288, Japan
    Opt Express 20:20427-46. 2012
  10. doi request reprint A hierarchical Bayesian method to resolve an inverse problem of MEG contaminated with eye movement artifacts
    Yusuke Fujiwara
    Graduate School of Information Science, Nara Institute of Science and Technology, Nara 630 0192, Japan
    Neuroimage 45:393-409. 2009

Collaborators

Detail Information

Publications16

  1. pmc Brain activity underlying auditory perceptual learning during short period training: simultaneous fMRI and EEG recording
    Ana Cláudia Silva de Souza
    Universidade Federal de Sao Joao del Rei, Ouro Branco, Brazil
    BMC Neurosci 14:8. 2013
    ..We investigated whether the practice effects are determined solely by activity in stimulus-driven mechanisms or whether high-level attentional mechanisms, which are linked to the perceptual task, control the learning process...
  2. ncbi request reprint Hierarchical Bayesian estimation for MEG inverse problem
    Masa aki Sato
    ATR Computational Neuroscience Laboratories, 2 2 2 Hikaridai, Seika, Soraku, Kyoto 619 0288, Japan
    Neuroimage 23:806-26. 2004
    ..Simulation results demonstrate that our method appropriately resolves the inverse problem even if fMRI data convey inaccurate information, while the Wiener filter method is seriously deteriorated by inaccurate fMRI information...
  3. doi request reprint Evaluation of hierarchical Bayesian method through retinotopic brain activities reconstruction from fMRI and MEG signals
    Taku Yoshioka
    National Institute of Information and Communications Technology, Soraku, Kyoto 619 0288, Japan
    Neuroimage 42:1397-413. 2008
    ..These results indicate the potential capability for the hierarchical Bayesian method combining MEG with fMRI to improve the spatiotemporal resolution of noninvasive brain activity measurement...
  4. doi request reprint Reduction of global interference of scalp-hemodynamics in functional near-infrared spectroscopy using short distance probes
    Takanori Sato
    Nagaoka University of Technology, 1603 1 Kamitomioka, Nagaoka, Niigata 940 2188, Japan ATR Brain Information Communication Research Lab Group, 2 2 2 Hikaridai, Keihanna Science City, Kyoto 619 0288, Japan
    Neuroimage 141:120-32. 2016
    ..These results suggest that combining measurements from four Short-channels with a GLM provides robust estimation of cerebral activity at a low cost. ..
  5. doi request reprint Cortical current source estimation from electroencephalography in combination with near-infrared spectroscopy as a hierarchical prior
    Takatsugu Aihara
    ATR Computational Neuroscience Laboratories, Kyoto 619 0288, Japan
    Neuroimage 59:4006-21. 2012
    ..The results suggest that VBMEG with NIRS prior performs well, even with as few as 19 EEG sensors. These findings indicate the potential value of clinically applying VBMEG using a combination of EEG and NIRS...
  6. doi request reprint Premotor cortex mediates perceptual performance
    Daniel Callan
    ATR Computational Neuroscience Laboratories, Kyoto, Japan
    Neuroimage 51:844-58. 2010
    ....
  7. pmc Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns
    Okito Yamashita
    ATR Computational Neuroscience Laboratories, Japan
    Neuroimage 42:1414-29. 2008
    ..We conclude that SLR provides a robust method for fMRI decoding and can also serve as a stand-alone tool for voxel selection...
  8. doi request reprint Multi-subject and multi-task experimental validation of the hierarchical Bayesian diffuse optical tomography algorithm
    Okito Yamashita
    Neural Information Analysis Laboratories, ATR, 2 2 2 Hikaridai, Keihanna Science City, Kyoto 619 0288, Japan Brain Functional Imaging Technologies Group, CiNet, 1 4 Yamadaoka, Suita City, Osaka 565 0871, Japan Electronic address
    Neuroimage 135:287-99. 2016
    ..Compared with the current gold-standard method, the new method showed fewer false positives, which resulted in improved spatial-pattern similarity, although the localization errors of the main activity clusters were comparable. ..
  9. doi request reprint Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography
    Takeaki Shimokawa
    ATR Neural Information Analysis Laboratories, Kyoto 619 0288, Japan
    Opt Express 20:20427-46. 2012
    ..This discrimination ability was possible even if the depths of the two absorbers were different from each other. These results show the high spatial resolution of the proposed method in both depth and horizontal directions...
  10. doi request reprint A hierarchical Bayesian method to resolve an inverse problem of MEG contaminated with eye movement artifacts
    Yusuke Fujiwara
    Graduate School of Information Science, Nara Institute of Science and Technology, Nara 630 0192, Japan
    Neuroimage 45:393-409. 2009
    ..Our method should be widely applicable to MEG data obtained in tasks with non-negligible eye movements...
  11. doi request reprint Estimating repetitive spatiotemporal patterns from resting-state brain activity data
    Yusuke Takeda
    Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, 2 2 2 Hikaridai, Seika cho, Soraku gun, Kyoto 619 0288, Japan Electronic address
    Neuroimage 133:251-65. 2016
    ..Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. ..
  12. doi request reprint Estimation of hyper-parameters for a hierarchical model of combined cortical and extra-brain current sources in the MEG inverse problem
    Ken ichi Morishige
    Department of Intelligent Systems Design Engineering, Toyama Prefectural University, 5180 Kurokawa, Imizu shi, Toyama 939 0398, Japan Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, 2 2 2 Hikaridai, Keihanna Science City, Kyoto 619 0288, Japan Electronic address
    Neuroimage 101:320-36. 2014
    ..Furthermore, we applied our proposed method to measured MEG data during covert pursuit of a smoothly moving target and confirmed its effectiveness. ..
  13. doi request reprint A generalized method to estimate waveforms common across trials from EEGs
    Yusuke Takeda
    ATR Computational Neuroscience Laboratories, 2 2 2 Hikaridai, Keihanna Science City, Kyoto 619 0288, Japan
    Neuroimage 51:629-41. 2010
    ..This method can be used in general situations where the number and the delays of EEG waveforms common across trials are unknown...
  14. doi request reprint Single-trial reconstruction of finger-pinch forces from human motor-cortical activation measured by near-infrared spectroscopy (NIRS)
    Isao Nambu
    ATR Computational Neuroscience Laboratories, Kyoto, Japan
    Neuroimage 47:628-37. 2009
    ..These data demonstrate the potential for reconstructing different levels of external loads (forces) from those of the internal loads (activation) in the human brain using NIRS...
  15. ncbi request reprint The effects of feature attention on prestimulus cortical activity in the human visual system
    Kazuhisa Shibata
    Nara Institute of Science and Technology, Graduate School of Information Science, 8916 5 Takayama cho, Ikoma shi, Nara 630 0101, Japan
    Cereb Cortex 18:1664-75. 2008
    ..These results suggest that, although both spatial and feature attention modulate prestimulus activity within specific visual areas, neural mechanisms underlying these effects might be different...
  16. ncbi request reprint A Bayesian missing value estimation method for gene expression profile data
    Shigeyuki Oba
    Graduate School of Information Science, Nara Institute of Science and Technology, 8916 5 Takayama, Ikoma 630 0192, Japan
    Bioinformatics 19:2088-96. 2003
    ....