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Tsukasa Kimura, Ph.D.

Assistant Professor

 

Graduate School of Human Sciences, Osaka University

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1-2 Yamadaoka, Suita, Osaka, 565-0871, Japan

 

E-mail: t-kimura.hus[xxx]osaka-u.ac.jp

(please replace [xxx] with @)

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Google scholar citations

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Research Topics

Prediction, Sense of agency, Sensory attenuation

Multimodal interaction, Visuotactile processing

Event-related brain potential (ERP)

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Education

2018

　Ph.D., Psychology, Kwansei Gakuin University, Japan

2013-2016

　Ph.D. program in Department of Psychological Science, Kwansei Gakuin University, Japan

2011-2013

　M.A. Department of Psychological Science, Kwansei Gakuin University, Japan

2007-2011

　B.S. Department of Psychology, Teikyo University, Japan

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Publications

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International Journal

  1. Kimura, T. & Katayama, J. (2023). Visual stimuli in the peripersonal space facilitate the spatial prediction of tactile events—A comparison between approach and nearness effects. Frontiers in Human Neuroscience, 17, 1203100. (Open access)

  2. Kimura, T. & Kawashima, T. (accepted). The influence of peripheral information on a proactive process during multitasking. Quarterly Journal of Experimental Psychology. (author's final version)

  3. Kimura, T.*, Mizumoto, T.*, Torii, Y., Ohno, M., Higashino, T., & Yagi, Y. (2023). Comparison of the effects of indoor and outdoor exercise on creativity: an analysis of EEG alpha power. Frontiers in Psychology, 14, 1161533. (Open access; *equal contribution)

  4. Kimura, T. (2023). Efficient use of peripheral information for temporal prediction​. Biological Psychology, 177, 108484. (Open access)

  5. Emsawas, T., Morita, T., Kimura, T., Fukui, K., & Numao, M. (2022). Multi-Kernel Temporal and Spatial Convolution for EEG-Based Emotion Classification. Sensors, 22, 8250. (Open access)

  6. Liu, W., Dempo, A., Kimura, T., Kawashima, T., & Shinohara, K. (2022). Effects of the presence of a cell phone and exposure to natural environments on remote associates task performance. Scientific reports, 12, 9507. (Open access)

  7. Dempo, A., Kimura, T., & Shinohara, K. (2022). Perceptual and cognitive processes in augmented reality – comparison between binocular and monocular presentations. Attention, Perception, & Psychophysics, 84(2), 490-508. (Open access)

  8. Kimura, T., Yamada, T., Hirokawa, Y., & Shinohara, K. (2021). Brief and Indirect Exposure to Natural Environment Restores the Directed Attention for the Task. Frontiers in Psychology, 12, 2725. (Open access)

  9. Kimura, T. (2021). Approach of visual stimuli facilitates the prediction of tactile events and suppresses beta band oscillations around the primary somatosensory area. Neuroreport, 32(7), 631-635. (Open access) (Cover of this issue)

  10. Kimura, T. (2021). Multiple Spatial Coordinates Influence the Prediction of Tactile Events Facilitated by Approaching Visual Stimuli​. Multisensory Research, 34(5), 531-551. (Open access)

  11. Hagad, J. L., Kimura, T., Fukui, K., & Numao, M. (2021). Learning Subject-Generalized Topographical EEG Embeddings Using Deep Variational Autoencoders and Domain-Adversarial Regularization. Sensors, 21, 1792. (Open access)

  12. Kimura, T., Takemura, N., Nakashima, Y., Kobori, H., Nagahara, H., Numao, M., & Shinohara, K. (2020). Warmer Environments Increase Implicit Mental Workload Even If Learning Efficiency Is Enhanced. Frontiers in Psychology, 11, 568. (Open access)

  13. Kimura, T., & Katayama, J. (2020). Congruency of intervening events and self-induced action influence prediction of final results. Experimental Brain Research, 238, 575-586. (Open access)

  14. ​Kimura, T., & Katayama, J. (2018). The approach of visual stimuli influences expectations about stimulus types for subsequent somatosensory stimuli. Experimental Brain Research, 236, 1563-1571.

  15. Kimura, T., & Katayama, J. (2017). Visual stimuli approaching toward the body influence temporal expectations about subsequent somatosensory stimuli. Brain Research, 1664, 95-101.

  16. Kimura, T., & Katayama, J. (2017). Regularity of approaching visual stimuli influences spatial expectations for subsequent somatosensory stimuli. Experimental Brain Research, 235, 1657-1663.

  17. Kimura, T., & Katayama, J. (2015). Approach of visual stimuli modulates spatial expectations for subsequent somatosensory stimuli. International Journal of Psychophysiology, 96 (3), 176-182.

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International Conference Proceedings

  1. Chen, Y., Morita, T., Kimura, T., Kato, T., Numao, M., & Fukui, K. (2023). Gated Variable Selection Neural Network for Multimodal Sleep Quality Assessment. Proc. 32nd International Conference on Artificial Neural Networks (ICANN2023), 288-299.

  2. Ding, K., Kimura, T., Fukui, K., & Numao, M. (2021). EEG emotion Enhancement using Task-specific Domain Adversarial Neural Network. Proc. 2021 International Joint Conference on Neural Networks (IJCNN), 1-8.

  3. Verma, M., Nakashima, Y., Kobori, H., Takaoka, R., Takemura, N., Kimura, T., Nagahara., H., Numao, M., & Shinohara, K. (2021). Learners’ Efficiency Prediction Using Facial Behavior Analysis. Proc. 2021 IEEE International Conference on Image Processing (ICIP2021), 1084-1088.

  4. Ding, K., Kimura, T., Fukui, K., & Numao, M. (2021). Cross-phase Emotion Recognition using Multiple Source Domain Adaptation. Proc. of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC2021), 150-157

  5. Boonprakong, N., Kimura, T., Fukui, K., Okada, K., Ito, M., Maruyama, H., & Numao, M. (2020). Towards Multimodal Office Task Performance Estimation. Proc. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC2020), 2695-2701.

  6. Thammasan, N., Uesaka, A., Kimura, T., Fukui, K., & Numao, M. (2020). Feasibility study of magnetoencephalographic inter-subject synchrony during music listening. Proc. 12th International Conference on Methods and Techniques in Behavioral Research and 6th Seminar on Behavioral Methods (Measuring Behavior 2020-21), 1, 52-55.

  7. Emsawas, T., Kimura, T., Fukui, K., & Numao, M. (2020). Comparative Study of Wet and Dry Systems on EEG-Based Cognitive Tasks. Proc. The 13th International Conference on Brain Informatics 2020 (BI 2020), 309-318.

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