PROFILE

I am an assistant project scientist at Swartz Center for Computational Neuroscience (SCCN), Institute for Nueral Computation, University of California San Diego (UCSD), La Jolla, CA, USA. I received Ph.D (Engineering) from Keio University, Kanagawa, Japan in 2014. My research interests include biological signal processing and machine learning toward real-world applications of brain-computer interfaces.

CV / Google Scholar Citations

RESEARCH

Brain-computer interface

Biological signal processing

Clinical application

Publications

  1. Facilitating calibration in high-speed BCI spellers via leveraging cross-device shared latent responses

    M. Nakanishi, Y. -T. Wang, C. -S. Wei, K. -J. Chiang and T. -P. Jung
    IEEE Trans. Biomed. Eng., vol.67, no.4, pp.1105-1113, 2020.
    [DOI: 10.1109/TBME.2019.2929745]

  2. Robustness analysis of decoding SSVEPs in humans with head movements using a moving visual flicker

    S. Kanoga, M. Nakanishi, A. Murai, M. Tada, and A. Kanemura
    J. Neural Eng., vol.17, 016009, 2020.
    [DOI: 10.1088/1741-2552/ab5760]

  3. Enhancing detection of SSVEPs for a high-speed brain speller using task-related component analysis

    M. Nakanishi, Y. Wang, X. Chen, Y. -T. Wang, X. Gao, and T. -P. Jung
    IEEE Trans. Biomed. Eng., vol.65, no.1, pp.104-112, 2018. (Impact Factor: 2.468)
    [DOI: 10.1109/TBME.2017.2694818], [MATLAB]

  4. Detecting glaucoma with a portable brain-computer interface for objective assessment of visual function loss

    M. Nakanishi, Y. -T. Wang, T. -P. Jung, J. K. Zao, Y. -Y. Chien, A. Diniz-Filho, F. B. Daga, Y. P. Lin, Y. Wang, and F. A. Medeiros
    JAMA Ophthalmol., 2017. (Impact Factor: 4.340)
    [DOI: 10.1001/jamaophthalmol.2017.0738]

  5. An online brain-computer interface based on SSVEPs measured from non-hair-bearing areas

    Y. -T. Wang*, M. Nakanishi*, C. -S. Wei, Y. Wang, C. -K., Cheng, and T. -P. Jung (*Equal contribution)
    IEEE Trans. Neural Syst. Rehabil. Eng., vol.25, no.1, pp.11-18, 2017. (Impact factor: 3.188)
    [DOI: 10.1109/TNSRE.2016.2573819]

  6. Unsupervised frequency recognition method of SSVEPs using a filter bank implementation of binary subband CCA

    M. R. Islam, M. K. I. Molla, M. Nakanishi, and T. Tanaka
    J. Neural Eng., vol.14, 026007, 2017. (Impact factor: 4.551)
    [DOI: 10.1088/1741-2552/aa5847]

  7. Fast detection of covert visuospatial attention using hybrid N2pc and SSVEP features

    M. Xu, Y. Wang, M. Nakanishi, Y. -T. Wang, H. Qi, T. -P. Jung and D. Ming
    J. Neural Eng., vol.13, 066003, 2016. (Impact factor: 4.551)
    [DOI: 10.1088/1741-2560/13/6/066003]

  8. Assessing the effects of voluntary and involuntary eyeblinks in independent components of electroencephalogram

    S. Kanoga, M. Nakanishi, and Y. Mitsukura
    Neurocomp., vol.193, pp.20-32, 2016. (Impact factor: 4.551)
    [DOI: 10.1016/j.neucom.2016.01.057]

  9. Glaucoma and driving risk under fog conditions

    A. Diniz-Filho, E. R. Boer, A. Elhosseiny, Z. Wu, M. Nakanishi, and F. A. Medeiros
    Transl. Vis. Sci. Technol., vol.5, no.6, 15, 2016. (Impact factor: 2.339)
    [DOI: 10.1167/tvst.5.6.15]

  10. High-speed spelling with a noninvasive brain-computer interface

    X. Chen, Y. Wang, M. Nakanishi, X. Gao, T. -P. Jung, and S. Gao
    Proc. Natl. Acad. Sci. U. S. A., vol.112, no.44, E6058-E6067, 2015. (Impact Factor: 9.674)
    [DOI: 10.1073/pnas.1508080112]

  11. A high-speed brain speller using steady-state visual evoked potentials

    M. Nakanishi, Y. Wang, Y. -T. Wang, Y. Mitsukura, and T. -P. Jung
    Int. J. Neural Syst., vol.24, no.6, 1450019, 2014. (Impact Factor: 6.507)
    [DOI: 10.1142/S0129065714500191]

  12. A comparison study of canonical correlationi analysis based methods for detecting steady-state visual evoked potentials

    M. Nakanishi, Y. Wang, Y. -T. Wang, and T. -P. Jung
    PLoS ONE, vol.10, no.10, e140703, 2015. (Impact Factor: 3.234)
    [DOI: 10.1371/journal.pone.0140703], [DATASET]

  13. Generating visual flickers for eliciting robust steady-state visual evoked potentials at flexible frequencies using monitor refresh rate

    M. Nakanishi, Y. Wang, Y. -T. Wang, Y. Mitsukura, and T. -P. Jung
    PLoS ONE, vol.9, no.6, e99235, 2014. (Impact Factor: 3.234)
    [DOI: 10.1371/journal.pone.0099235]

  14. Experimental verification for driving control of a powered wheelchair by voluntary eye blinking and with environmental recognition

    K. Okugawa, M. Nakanishi, Y. Mitsukura, and M. Takahashi
    Trans. Jpn. Soc. Mech. Eng., vol.80, no.813, DR0125, 2014.
    [DOI: 10.1299/transjsme.2014dr0125]

  15. Driving control of a powered wheelchair by voluntary eye blinking and with environment recognition

    K. Okugawa, M. Nakanishi, Y. Mitsukura, and M. Takahashi
    Appl. Mechanics Mater., vol.490, pp.1764-1768, 2014.
    [DOI: 10.4028/www.scientific.net/AMM.490-491.1764]

  16. Voluntary eye blink detection using electrooculogram for controlling powered wheelchairs considering environmental information

    M. Nakanishi, K. Okugawa, M. Takahashi, and Y. Mitsukura
    IEEJ Trans. Electron. Inform. Syst., vol.133, no.10, pp.1969-1975, 2013.
    [DOI: 10.1541/ieejeiss.133.1969]

  1. EEG-based brain-computer interfaces

    Y. Wang, M. Nakanishi, and D. Zhang
    in X. Zheng (Ed.): Neural Interface: Frontiers and Applications, Springer, pp.41-65, 2019.
    [DOI: 10.1007/978-981-13-2050-7_2], [Online ISBN: 978-981-13-2050-7]

  2. Spatial filtering techniques for improving template-based SSVEP detection

    M. Nakanishi, Y, Wang, and T. -P. Jung
    in T. Toshihisa and A. Mahnaz (Eds.): Signal Processing and Machine Learning for Brain-Computer Interfaces, Institute of Engineering and Technology (IET), pp.219-242, 2018.
    [DOI: 10.1049/PBCE114E_ch11], [Online ISBN: 978-1-785-61399-9]

  3. Session-to-session transfer in detecting steady-state visual evoked potentials with individual traning data

    M. Nakanishi, Y, Wang, and T. -P. Jung
    in D. D. Schmorrow and C. M. Fidopiastis (Eds.): Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience, Springer, vol.9742, pp.253-260, 2016.
    [DOI: 10.1007/978-3-319-39955-3_24], [Online ISBN: 978-3-319-39955-3]

  1. Statistically optimized spatial filtering in decoding steady-state visual evoked potentials based on task-related component analysis

    K. -J. Chiang, M. Nakanishi, and T. -P. Jung
    Proc. 42nd Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., Montreal, Quebec, Canada, July 2020. (Accepted)

  2. Cross-subject transfer learning improves the practicality of real-world applications of brain-computer interfaces

    K. -J. Chiang, C. -S. Wei, M. Nakanishi, and T. -P. Jung
    Proc. 9th Int. IEEE EMBS Neural Eng. Conf., pp.424-427, San Fransisco, CA, USA, Mar. 2019.
    [DOI: 10.1109/NER.2019.8716958]

  3. EEG-based user authentication using a convolutional neural network

    T. Yu, C. -S. Wei, K. -J. Chiang, M. Nakanishi, and T. -P. Jung
    Proc. 9th Int. IEEE EMBS Neural Eng. Conf., pp.1011-1014, San Fransisco, CA, USA, Mar. 2019.
    [DOI: 10.1109/NER.2019.8716965]

  4. Optimizing phase intervals for phase-coded SSVEP-based BCIs with template-based algorithm

    M. Nakanishi, Y. -T. Wang, and T. -P. Jung
    Proc. IEEE Int. Conf. Syst. Man Cybern., pp.650-655, Miyazaki, Japan, Oct. 2018.
    [DOI: 10.1109/SMC.2018.00119]

  5. Exploring variability in steady-state visual evoked potentials toward high-speed BCI speller

    C. -S. Wei, M. Nakanishi, K. -J. Chiang, and T. -P. Jung
    Proc. IEEE Int. Conf. Syst. Man Cybern., pp.474-479, Miyazaki, Japan, Oct. 2018.
    [DOI: 10.1109/SMC.2018.00090]

  6. Transferring shared responses across electrode montages for facilitating calibration in highーspeed brain spellers

    M. Nakanishi, Y. -T. Wang, and T. -P. Jung
    Proc. 40th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.89-92, Honolulu, HI, USA, Jul. 2018.
    [DOI: 10.1109/EMBC.2018.8512269]

  7. Evaluating the performance of non-hair SSVEP-based BCIs featuring template-based decoding methods

    W. -H. Chan, K. -J. Chiang, M. Nakanishi, Y. -T. Wang, and T. -P. Jung
    Proc. 40th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.1972-1975, Honolulu, HI, USA, Jul. 2018.
    [DOI: 10.1109/EMBC.2018.8512662]

  8. Semi-simulation experiments for quantifying the performance of SSVEP-based BCI after reducing artifacts from trapezius muscles

    S. Kanoga, M. Nakanishi, A. Murai, M. Tada, and A. Kanemura
    Proc. 40th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.4924-4827, Honolulu, HI, USA, Jul. 2018.
    [DOI: 10.1109/EMBC.2018.8513180]

  9. Waveform-based multi-stimulus coding for brain-computer interfaces based on steady-state visual evoked potentials

    Y. Tanji, K. Suefusa, M. Nakanishi, and T. Tanaka
    Proc. 42nd IEEE Int. Conf. Acoust. Speech Sig. Process., pp.821-825, Calgary, Alberta, Canada, Apr. 2018.
    [DOI: 10.1109/ICASSP.2018.8462246]

  10. Independent component analysis-based spatial filtering improves template-based SSVEP detection

    M. Nakanishi, Y. Wang, S. -H. Hsu, Y. -T. Wang, and T. -P. Jung
    Proc. 39th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.3620-3623, Jeju Island, Korea, Jul. 2017.
    [DOI: 10.1109/EMBC.2017.8037641]

  11. Does frequency resolution affect the classification performance of steady-state visual evoked potentials?

    M. Nakanishi, Y. Wang, Y. -T. Wang, and T. -P. Jung
    Proc. 8th Int. IEEE EMBS Neural Eng. Conf., pp.341-344, Shanghai, China, May 2017.
    [DOI: 10.1109/NER.2017.8008360]

  12. Frequency recognition of steady-state visual evoked potentials using binary subband CCA with reduced dimension of reference signals

    M. R. Islam, T. Tanaka, M. Nakanishi, and M. K. I. Molla
    Proc. 41st IEEE Int. Conf. Acoust. Speech Sig. Process., pp.769-773, Shanghai, China, Mar. 2016.
    [DOI: 10.1109/ICASSP.2016.7471779]

  13. A dynamic stopping method for improving performance of steady-state visual evoked potential based brain-computer interfaces

    M. Nakanishi, Y. Wang, Y. -T. Wang, and T. -P. Jung
    Proc. 37th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.1057-1060, Milano, Italy, Aug. 2015.
    [DOI: 10.1109/EMBC.2015.7318547]

  14. Developing an online steady-state visual evoked potential-based brain-computer interface system using EarEEG

    Y. -T. Wang, M. Nakanishi, S. L. Kappel, P. Kidmose, D P. Mandic, Y. Wang, C. K. Cheng, and T. -P. Jung
    Proc. 37th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.2271-2274, Milano, Italy, Aug. 2015.
    [DOI: 10.1109/EMBC.2015.7318845]

  15. Enhancing unsupervised canonical correlation analysis-based frequency detection of SSVEPs by incorporating background EEG

    M. Nakanishi, Y. Wang, Y. -T. Wang, and T. -P. Jung
    Proc. 36th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.3053-3056, Chicago, IL, USA, Aug. 2014.
    [DOI: 10.1109/EMBC.2014.6944267]

  16. Enhancing detection of steady-state visual evoked potentials using individual training data

    Y. Wang, M. Nakanishi, Y. -T. Wang, and T. -P. Jung
    Proc. 36th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.3037-3040, Chicago, IL, USA, Aug. 2014.
    [DOI: 10.1109/EMBC.2014.6944263]

  17. Hybrid frequency and phase coding for a high-speed SSVEP-based BCI speller

    X. Chen, Y. Wang, M. Nakanishi, T. -P. Jung, and X. Gao
    Proc. 36th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.3993-3996, Chicago, IL, USA, Aug. 2014.
    [DOI: 10.1109/EMBC.2014.6944499]

  18. Integrating interference frequency components elicited by monitor refresh rate to enhance frequency detection of SSVEPs

    M. Nakanishi, Y. Wang, Y. -T. Wang, Y. Mitsukura, and T. -P. Jung
    Proc. 6th Int. IEEE EMBS Neural Eng. Conf., pp.1092-1095, San Diego, CA, USA, Nov. 2013.
    [DOI: 10.1109/NER.2013.6696127]

  19. An approximation approach for rendering visual flickers in SSVEP-based BCI using monitor refresh rate

    M. Nakanishi, Y. Wang, Y. -T. Wang, Y. Mitsukura, and T. -P. Jung
    Proc. 35th Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., pp.2176-2179, Osaka, Japan, Jul. 2013.
    [DOI: 10.1109/EMBC.2013.6609966]

  20. Wheelchair control system using electrooculogram signal processing

    M. Nakanishi, and Y. Mitsukura
    Proc. 19th Korea-Japan Joint Workshop Front. Comp. Vis., pp.137-142, Incheon, Korea, Jan. 2013.
    [DOI: 10.1109/FCV.2013.6485476]

  21. Online voluntary eye blink detection method using electrooculogram

    M. Nakanishi, Y. Mitsukura, Y. Wang, Y. -T. Wang, and T. -P. Jung
    Proc. 2012 Int. Symp. Nonlin. Theory its Appl., pp.114-117, Majorca, Spain, Oct. 2012.

  22. Periodicity detection for BCI based on periodic code modulation visual evoked potentials

    M. Nakanishi, and Y. Mitsukura
    Proc. 37th IEEE Int. Conf. Acoust. Speech Sig. Process., pp.665-668, Kyoto, Japan, Mar. 2012.
    [DOI: 10.1109/ICASSP.2012.6287971]

  23. Recognizing facial actions using RBF network

    K. Takahashi, M. Nakanishi, and Y. Mitsukura
    Proc. 2011 Int. Symp. Nonlin. Theory its Appl., pp.298-301, Kobe, Japan, Sep. 2011.

  24. “EEG analysis for acoustic quality evaluation using PCA and FDA

    M. Nakanishi, Y. Mitsukura, and A. Hara
    Proc. 20th IEEE Int. Symp. Robot Hum. Interactive Commun., pp.321-324, Atlanta, GA, USA, Aug. 2011.
    [DOI: 10.1109/ROMAN.2011.6005291]