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Reseacher

Name TANAKA Hirokazu
Official Title Professor
Affiliation Intelligent Systems, Information Technology
E-mail htanaka@tcu.ac.jp
Web
  1. http://www.risys.gl.tcu.ac.jp/Main.php?action=profile&type=detail&tchCd=5002155
Profile I studied theoretical physics for graduate training, notably string theory, at the Yukawa Institute of Theoretical Physics of Kyoto University and obtained a Ph.D. in 2000. I then switched my scientific interest to neuroscience, especially a computational understanding of the brain mechanisms in sensory processing and motor control. My professional expertise includes computational modeling of brain functions, biological signal processing, and behavioral analysis.
Research Field(Keyword & Summary)
  1. (1) Computational neuroscience

    Computational neuroscience pursues an algorithmic and representational understanding of brain functions through computational modeling. I construct sensory processing, motor control, and decision-making models that explain both neural activities and behavioral laws. Theoretical models employ optimal control and optimal estimation in systems engineering. Computation modeling reveals how the brain represents and processes its internal information representations to interact with external environments and generate ethologically meaningful behaviors.

  2. (2) Biological signal processing.

    Biological and signals are inherently non-stationary and noisy, hence signal processing methods are of prime importance. I apply and develop advanced signal processing techniques for removing artifacts from data and extracting relevant neural signals. I also contribute to brain-computer interfaces as an engineering application of biological signal processing.

  3. (3) Behavioral analysis.

    Animal and human behaviors manifest the brain's information processing strategies. Computational analysis of behaviors aims to unravel the brain's information processing principles hidden behind noisy behavioral data. I employ machine learning and statistical modeling methods for analyzing a range of behavioral data in motor control, sensory perception, and decision making tasks.
Representative Papers
  1. (1) Tanaka, H., Ishikawa, T., Lee, J., & Kakei, S. (2020). The cerebro-cerebellum as a locus of forward model: a review. Frontiers in Systems Neuroscience, 14, 19.
  2. (2) Tanaka, H. (2020). Group task-related component analysis (gTRCA): A multivariate method for inter-trial reproducibility and inter-subject similarity maximization for EEG data analysis. Scientific Reports, 10(1), 1-17.
  3. (3) Tanaka, H., Ishikawa, T., & Kakei, S. (2019). Neural evidence of the cerebellum as a state predictor. The Cerebellum, 18(3), 349-371.
  4. (4) Tanaka, H., & Miyakoshi, M. (2019). Cross-correlation task-related component analysis (xTRCA) for enhancing evoked and induced responses of event-related potentials. NeuroImage, 197, 177-190.
  5. (5) Tanaka, H., Miyakoshi, M., & Makeig, S. (2018). Dynamics of directional tuning and reference frames in humans: A high-density EEG study. Scientific Reports, 8(1), 1-18.
  6. (6) Tanaka, H. (2016). Modeling the motor cortex: Optimality, recurrent neural networks, and spatial dynamics. Neuroscience Research, 104, 64-71.
  7. (7) Tanaka, H., Katura, T., & Sato, H. (2014). Task-related oxygenation and cerebral blood volume changes estimated from NIRS signals in motor and cognitive tasks. NeuroImage, 94, 107-119.
  8. (8) Tanaka, H., & Sejnowski, T. J. (2013). Computing reaching dynamics in motor cortex with Cartesian spatial coordinates. Journal of neurophysiology, 109(4), 1182-1201.
  9. (9) Tanaka, H., Katura, T., & Sato, H. (2013). Task-related component analysis for functional neuroimaging and application to near-infrared spectroscopy data. NeuroImage, 64, 308-327.
  10. (10) Tanaka, H., Krakauer, J. W., & Sejnowski, T. J. (2012). Generalization and multirate models of motor adaptation. Neural Computation, 24(4), 939-966.
Award Excellent Research Award, the Japanese Neural Network Society (2018).
Best Presentation Award, 6th Motor Control Meeting (2012).
Grant-in-Aid for Scientific Research Support: Japan Society for Promotion of Science (JSPS) https://nrid.nii.ac.jp/ja/nrid/1000000332320/
Recruitment of research assistant(s) N/A
Affiliated academic society (Membership type) (1) Society for Neuroscience
(2) The Japan Neuroscience Society
(3) The Japanese Neural Network Society
Education Field (Undergraduate level) Physics
Education Field (Graduate level) Theoretical physics

Affiliation