EDUCATION

- BS. (Aug. 2006), University of Science, HCMC, Vietnam

- MS. (Sep. 2011), Japan Advanced Institute of Science and Technology, Ishikawa, Japan

- Ph.D (Sep. 2015), Ritsumeikan University, Shiga, Japan

RESEARCH INTERESTS

- Computational modeling of the cerebellum

- Developing tools for analyzing neural data, e.g spiking data, Calcium imaging data...

AWARDS

- JSPS Research Fellowship for Young Scientists (Apr. 2014 - Mar. 2016)

PUBLICATIONS

[11] Huu Hoang*, Shinichiro Tsutsumi, Masanori Matsuzaki, Masanobu Kano, Keisuke Toyama, Kazuo Kitamura & Mitsuo Kawato (2023) Negative reward-prediction errors of climbing fiber inputs for cerebellar reinforcement learning algorithm, bioRxiv, doi: https://doi.org/10.1101/2023.03.13.532374

[10] Huu Hoang*, Shinichiro Tsutsumi, Masanori Matsuzaki, Masanobu Kano, Mitsuo Kawato, Kazuo Kitamura & Keisuke Toyama (2022) Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional modules reduces dimensions for reinforcement learning, bioRxiv, doi: https://doi.org/10.48550/arXiv.2208.08478

[9] Huu Hoang*, Masa-aki Sato*, Shigeru Shinomoto, Shinichiro Tsutsumi, Miki Hashizume, Tomoe Ishikawa, Masanobu Kano, Yuji Ikegaya, Kazuo Kitamura, Mitsuo Kawato & Keisuke Toyama (2019) Improved hyperacuity estimation of spike timing from calcium imaging, Scientific Reports 10(17844), doi: https://doi.org/10.1038/s41598-020-74672-y

[8] Huu Hoang, Eric J. Lang, Yoshito Hirata, Isao T. Tokuda, Kazuyuki Aihara, Keisuke Toyama, Mitsuo Kawato & Nicolas Schweighofer (2020) Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons, PLOS Computational Biology 16(7):e1008075. doi: https://doi.org/10.1371/journal.pcbi.1008075

[7] Mitsuo Kawato, Shogo Ohmae, Huu Hoang & Terry Sanger (2020) 50 years since the Marr, Ito, and Albus models of the cerebellum, Neuroscience (in press), doi: https://doi.org/10.1016/j.neuroscience.2020.06.019

[6] Isao T. Tokuda*, Huu Hoang* & Mitsuo Kawato (2017) New Insights into Olivo-Cerebellar Circuits for Learning from a Small Training Sample, Current Opinion in Neurobiology, 46:58-67.

[5] Huu Hoang & Isao T. Tokuda (2015) Verification of parameter estimation techniques from spike train data, Proceedings of the 2015 International Symposium on Nonlinear Theory and its Applications, NOLTA2015, Kowloon, Hong Kong, China.

[4] Huu Hoang & Isao T. Tokuda (2015) Validation of a minimum error method for estimating model parameters from neural spike train data, Journal of Signal Processing, 19(4): 111-114.

[3] Huu Hoang, Okito Yamashita, Isao T. Tokuda, Mitsuo Kawato, Masa-aki Sato & Keisuke Toyama (2015) Segmental Bayesian estimation of gap-junctional and inhibitory conductance of IO neurons from spike trains with complicated dynamics, Frontiers in Computational Neuroscience 9:56. doi: 10.3389/fncom.2015.00056.

[2] Miho Onizuka*, Huu Hoang*, Mitsuo Kawato*, Isao T. Tokuda, Nicolas Schweighofer, Yuichi Katori, Kazuyuki Aihara, Eric J. Lang & Keisuke Toyama (2013) Solution to the inverse problem of estimating gap-junctional and inhibitory conductance in inferior olive neurons from spike trains by network model simulation, Neural Networks, 47: 51-63.

[1] Isao T. Tokuda, Huu Hoang, Nicolas Schweighofer & Mitsuo Kawato (2013) Adaptive coupling of inferior olive neurons in cerebellar learning, Neural Networks, 47: 42-50.