Laboratory for Computational Neuroscience

  • Welcome to Laboratory for Computational Neuroscience

  • Finger Coordination

    Hierarchical modeling of finger movements for advanced motor prostheic applications

  • Changes in Neural Dynamics

    Time-varying nonlinear modeling of local neural circuits during development and learning for neurologic disease treatment and prothesis

  • EEG Applications

    Development of novel EEG platform for education and entertainment

  • Ph.D. Students

    We are currently seeking Ph.D. applicants who are interested in computational neuroscience and next generation technology.

  • Identification of time-varying neural dynamics from spike train data using multiwavelet basis functions

    Song Xu, Yang Li, Qi Guo, Xiao-Feng Yang, and Rosa H. M. Chan, Journal of Neuroscience Methods, vol. 278, pp. 46-56, 2017.

  • Evaluating the Small-World-Ness of a Sampled Network: Functional Connectivity of Entorhinal-Hippocampal Circuitry

    Qi She, Guanrong Chen, and Rosa H. M. Chan, Scientific Reports, 6: 21468, 2016.

  • Heterogeneous feature subset selection using mutual information-based feature transformation

    Min Wei, Tommy W. S. Chow, and Rosa H. M. Chan, Neurocomputing, vol. 168, pp. 706-718, 2015.

  • Naming Game on Networks: Let Everyone be Both Speaker and Hearer

    Yuan Gao, Guanrong Chen, and Rosa H. M. Chan, Scientific Reports, 4 : 6149 , 2015.

  • ARIS 2014 Best Conference Paper Award – Excellent Award

    Rosa H. M. Chan, Savio W. H. Wong, and Joseph N. Mak “Evaluating the Ease of Use of Surgical Robotics Through EEG,” International Conference on Advanced Robotics and Intelligent Systems, Robotics Society of Taiwan, 2014