| ENGLISH | JAPANESE |
 

HIDEAKI SHIMAZAKI, Ph.D.


 

shimazaki

 

Program-specific Associate Professor at Kyoto University / Senior Scientist at Honda Research Institute Japan

Researcher at RIKEN BSI (2012-2016) full CV
Visiting researcher at RIKEN BSI / MIT (2008-2011)
JSPS Research Fellow (2006/4-2008/3, 2008/4-2011/3)

Ph.D. (Physics), 2007 Dept. of Physics, Kyoto University, Japan
M.A. (Neuroscience), 2004 Dept. of Neuroscience, Johns Hopkins University
B.E., 2000 Dept. of Applied Physics and Physico-Informatics, Keio University, Japan

Email: h.shimazakii.kyoto-u.ac.jp

 

 

| Histogram Optimization | Kernel Optimization | Estimating Time-varying Neural Interactions |
| Point process and state-space models | Group Photos |



| Research | Publications | Conferences | Awards | Curriculum Vitae |
  Updates
 

Recent publications


2017 Jul 22 A co-authored paper published MaBouDi H, Shimazaki H, Giurfa M, Chittka L. Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities. PLoS Computational Biology (2017) 13(6): e1005551. [link]

2017 Jan 13 A paper published. Donner, Obermeyer, Shimazaki, Approximate Inference for Time-varying Interactions and Macroscopic Dynamics of Neural Populations. PLoS Computational Biology (2017) 13(1): e1005309 [link]


2016 May 26 A co-authored paper was published. Mochizuki et al. Similarity in Neuronal Firing Regimes across Mammalian Species. Journal of Neuroscience (2016) 36:5736-5747. [link]

2016 Apr 1 A co-authored paper was published. Chou et al. Social conflict resolution regulated by two dorsal habenular subregions in zebrafish. Science, Vol. 352, Issue 6281, pp. 87-90 [link]


2015 Dec 24 I uploaded my recent thought on neural dynamcis. Shimazaki H, Neurons as an Information-theoretic Engine. arXiv:1512.07855 [pdf, link]

2015 May 15 A paper by HaDi MaBouDi was accepted for publication in Vision Research. MaBouDi H, Shimazaki H, Amari S, Soltanian-Zadeh H, "Representation of Higher-order Statistical Structures in Natural Scenes via Spatial Phase Distributions." pdf

2015 May Our optimization mehtod for kernel density estimation is being used in labs of leading neuroscientists. Hill, Fried & Koch J Neurophysiol2015. Ito, Zhang, Witter, Moser & Moser Nature 2015. Manita, Suzuki, ..., Larkum & Murayama Neuron 2015.


2015 Mar 19 Our paper uncovering the role of silence in characterizing neural population activity has been accepted. Shimazaki, H., Sadeghi, K., Ishikawa, T., Ikegaya, Y. & Toyoizumi, T. Simultaneous silence organizes structured higher-order interactions in neural populations. Scientific Reports 5, 9821 (2015) [link, preprint]


2014 April Japanese edtition of Principle of Neural Science was published.
kandelI translated the section, "Appendix F, Theoretical Approaches to Neuroscience: Examples from SingleNeurons to Networks" by Abbott, Fusi, and Miller. [link]

 


 

Lecture information


Upcoming lectures

2016 Feb An introduction to the statistical analysis of point process networks An extension lecture at Institute of Statistics and Mathematics with Prof. Shinsuke Koyama. link


2014, 2015 Winter, Statistical Physics at International Christian University

  • Link to a syllabus.
  • Link to online training site (Moodle).

2015 Dec 7 and 14 RIKEN Brain Science Training Program: Statistics for Neuroscience I and II


Past lectures

2013 Mar 3-12, Introduction to statistical models of neural spike train data
Two weeks lecture courses at the Institute for Research in Fundamental Sciences.



 
| Research | Publications | Conferences | Awards | Curriculum Vitae |

Research

 

Multiple Neurons: Dynamics of neural interactions and behavior

Classical neurophysiological studies are based on the idea that stimulus and behavioral information is encoded in the firing rates of single neurons. At the same time, precise spike coordination in the spikes of neuronal population is discussed as an indication of coordinated network activity relevant for information processing. Thus accurate assessment of neural correlations is a key to understand their coding principles.

Statistical structure of neural correlations may change while an animal is engaged in behavioral tasks. We suggest estimating the dynamics of neural correlations using a state-space method, and further developed a method to test their significance. With this method, we are investigating behavior-dependent interactions in neural populations.

 

A sample web application is available from here.

[Web Application]

 

  • Paper and proceedings
    • Shimazaki H., Amari S., Brown E. N., and Gruen S., State-space Analysis of Time-varying Higher-order Spike Correlation for Multiple Neural Spike Train Data. PLoS Comput Biol 8(3): e1002385 (2012) link pdf
    • Shimazaki H., Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study. J. Phys.: Conf. Ser. (2013) pdf
    • Shimazaki H., Amari S., Brown E. N., and Gruen S. State-space Analysis on Time-varying Correlations in Parallel Spike Sequences, Proc. IEEE ICASSP2009, 3501-3504. pdf
  • Invited talks
    • ICSG2013. ELC International Meeting on ''Inference, Computation, and Spin Glasses'', Sapporo, Japan.
    • NIPS2008 Workshop. "Statistical Analysis and Modeling of Response Dependencies in Neural Populations:, Whistler, Canada
    • IEEE ICASSP2009. Special Session on 'Signal Processing for Neural Spike Trains', Taipei, Taiwan
  • Selected posters
    • Neuro2014, Sharp, Shimazaki, Isomura and Fukai. Behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement, Yokohama, Japan.
    • Cosyne2009. Shimazaki, Amari, Brown and Gruen. Detection of non-stationary higher-order spike correlation. [abstract]
  • Press
  • Award
    • Japanese Neural Network Society Research Award 2009 to Shimazaki H., Amari S., Brown E. N., and Gruen S. Title: `State-space Model of Dynamic Correlation'. JNNS2009.

 


Single Neurons: Optimizing Spike-rate Estimation

imgNeurons process sensory information using event sequences called action potentials or spikes. Much of the neurophysiological literature relies on the interpretation of the spike data by making a histogram or kernel density estimation of the spike-rate.

However, the quality of rate estimation is critically determined by the choice of bin-width or kernel bandwidth. We theoretically investigated accuracy and limitation in estimating the time-dependent spike-rate from finite samples, and developed methods to optimize the histogram bin-width and kernel bandwidth under objective error criteria.

 

Histogram Optimization

The optimal bin width of a histogram is obtained as a minimizer of the formula,

Here, k and v are mean and variance of the number of samples in the bins.

[Web Application]

    • [1] Shimazaki and Shinomoto, A method for selecting the bin size of a time histogram, Neural Computation (2007) Vol. 19, No. 6, 1503-1527. pdf
    • [2] Shimazaki and Shinomoto: A recipe for optimizing a time-histogram. Advances in NIPS 2007 Vol. 19, 1289-1296. pdf
    • Award Japanese Neural Network Society Young Researcher Award 2007

 

Kernel Optimization

The optimal bandwidth is obtained as a minimizer of the formula,

Here and are a kernel function with bandwidth and the data.

[Web Application]

    • [3] Shimazaki and Shinomoto: Kernel Bandwidth Optimization in Spike Rate Estimation Journal of Computational Neuroscience (2010) Vol. 29 (1-2) 171-182. pdf
    • [4] Shimazaki and Shinomoto: Kernel Width Optimization in the Spike-rate Estimation. Neural Coding 2007 Abstract p120-123, Montevideo, Uruguay. pdf
    • [5] Spike-rate Estimation with Locally Adaptive Kernel Method. JNNS2008 p186-187 in Japanese.
    • Award Best Poster Award at Neural Coding 2007
   
| Research | Publications | Conferences | Awards | Curriculum Vitae |
  Publications

 

In Preparation Under Review Published / In Press

[Google Scholor Citation Index] [ResearcherID] [ORCID]

Papers and Proceedings

Kass RE, Amari S, Arai K, Diekman CO, Diesmann M, Doiron B, Fairhall A, Fiddyment GM, Fukai T, Grün S, Harrison MT, Helias M, Nakahara H, Teramae J, Thomas PJ, Reimers M, Rodu J, Rotstein HG, Shea-Brown E, Shimazaki H, Shinomoto S, Yu BM, Kramer MA. Computational Neuroscience: Mathematical and Statistical Perspectives. Annual Review of Statistics and Its Application. in press [link]

MaBouDi H, Shimazaki H, Giurfa M, Chittka L. Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities. PLoS Computational Biology (2017) 13(6): e1005551. [link]

MaBouDi H, Shimazaki H, Soltanian-Zadeh H, Amari S. Learning Complex Representations from Spatial Phase Statistics of Natural Scenes. bioRxiv (2017) doi: https://doi.org/10.1101/112813

Donner C, Obermeyer K, Shimazaki H. Approximate Inference for Time-varying Interactions and Macroscopic Dynamics of Neural Populations. PLoS Computational Biology (2017) 13(1): e1005309 [link, code]

Donner C and Shimazaki H. Approximate inference method for dynamic interactions in larger neural populations. The 23rd International Conference on Neural Information Processing (ICONIP 2016) LNCS (2016) 9949, 104–110

Mochizuki Y, Onaga T, Shimazaki H, Shimokawa T, Tsubo Y, Kimura R, Saiki A, Sakai Y, Isomura Y, Fujisawa S, Shibata K, Hirai D, Furuta T, Kaneko T, Takahashi S, Nakazono T, Ishino S, Sakurai Y, Kitsukawa T, Lee JW, Lee H, Jung MW, Babul C, Maldonado PE, Takahashi K, Arce-McShane FI, Ross CF, Sessle BJ, Hatsopoulos NG, Brochier T, Riehle A, Chorley P, Gruen S, Nishijo H, Ichihara-Takeda S, Funahashi S, Shima K, Mushiake H, Yamane Y, Tamura H, Fujita I, Inaba N, Kawano K, Kurkin S, Fukushima K, Kurata K, Taira M, Tsutsui K, Ogawa T, Komatsu H, Koida K, Toyama K, Richmond BJ, and Shinomoto S. Similarity in Neuronal Firing Regimes across Mammalian Species. Journal of Neuroscience (2016) 36:5736-5747. [link]

Chou M.Y., Amo R., Kinoshita M., Cherng B.W., Shimazaki H., Agetsuma M., Shiraki T., Aoki T., Takahoko M., Yamazaki M., Higashijima S., and Okamoto H. Social conflict resolution regulated by two dorsal habenular subregions in zebrafish. Science, (2016) Vol. 352(6281) 87-90 [link]

MaBouDi H, Shimazaki H, Amari S, Soltanian-Zadeh H, Representation of higher-order statistical structures in natural scenes via spatial phase distributions. Vision Research (2016) 120, 61–73 [pdf, link]

Shimazaki H, Neurons as an Information-theoretic Engine. arXiv:1512.07855 (2015) [pdf, link]

Shimazaki H, Sadeghi K, Ishikawa T, Ikegaya Y, Toyoizumi T, Simultaneous silence organizes structured higher-order interactions in neural populations. Scientific Reports (2015) 5, 9821. [link]

Shimazaki H, Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study. J. Phys.: Conf. Ser. (2013) 473 012009. [link, pdf]

Shimazaki H, Amari S, Brown EN, and Gruen S, State-space analysis of time-varying higher-order spike correlation for multiple neural spike train data. PLOS Computational Biology (2012) 8(3): e1002385. [link, pdf, support page]

Shimazaki H, Analysis of multiple neural spike train data using the log-linear model : From stationary to time-varying spike correlation. The Brain & neural networks (2011) 8(4) 194-203 (In Japanese) [link, pdf]

Shimazaki H and Shinomoto S, Kernel bandwidth optimization in spike rate estimation. Journal of Computational Neuroscience (2010) Vol. 29 (1-2) 171-182 [link, pdf, support page]

Shimazaki H, Amari S, Brown EN, and Gruen S, State-space analysis on time-varying correlations in parallel spike sequences. Proc. IEEE ICASSP2009 (2009) 3501-3504 [link]

Shimazaki H and Shinomoto S, A method for selecting the bin size of a time histogram, Neural Computation (2007) Vol. 19(6), 1503-1527 [link, pdf, support page]

Shimazaki H and Shinomoto S, A recipe for optimizing a time-histogram, Advances in Neural Information Processing Systems (2007) Vol. 19, 1289-1296 [pdf, support page]

Shimazaki H and Niebur E, Correlated multiplicative modulation in coupled oscillator systems: a model of selective attention, Progress of Theoretical Physics Supplement (2006) No.161 336-339 [link]

Shimazaki H and Niebur E, Phase transitions in multiplicative competitive processes, Physical Review E (2005) 72(1), 011912 [link, pdf]

Tsukada M, Aihara T, Kobayashi Y, Shimazaki H., Spatial analysis of spike-timing-dependent LTP and LTD in the CA1 area of hippocampal slices using optical imaging, Hippocampus (2005) 15(1), 104-109. [link]

Kobayashi Y, Shimazaki H., Aihara T, Tsukada M. Spatial Distributions of Hippocampal LTP/LTD Induced Electrically from Schaffer Collaterals and Stratum Oriens with Relative Timing, The Brain & neural networks (2001) Vol8,No.2 p.57-64. (In Japanese) [link]


| Research | Publications | Conferences | Awards | Curriculum Vitae |

Conference, Workshop, Seminar

Seminar, Conference, Workshop in 2015

Christian Donner and Hideaki Shimazaki. Approximation methods for inferring time-varying interactions of a large neural population. NIPS 2015 Workshop on `Statistical Methods for Understanding Neural Systems'. Montreal, Canada. Dec 11, 2015 POSTER [link1, link2]

島崎秀昭 神経回路網活動の熱力学的考察 数理モデリング研究会 滋賀 2015年11月28,29日 TALK [link]

Shimazaki H. Simultaneous silence explains structured higher-order interactions of neural populations. Juelich Research Center. Juelich, Germany. May 5, 2015 Seminar TALK [link]

Shimazaki H. Simultaneous silence explains structured higher-order interactions of neural populations. Bernstein Center of Computational Neuroscience Berlin. Berlin, Germany. Apr 28, 2015 TALK [link]

島崎秀昭 Simultaneous silence explains structured higher-order interactions of neural populations. 第16回ノンパラメトリック統計解析とベイズ統計 慶應義塾大学 2015年3月25日 TALK

島崎秀昭 神経細胞の集団活動の高次統計とメカニズム 第3回ヘテロ・ニューロ・アナリシス研究会 玉川大学 2015年3月18日 TALK

 

Seminar, Conference, Workshop in 2014

Thomas Sharp, Hideaki Shimazaki, Yoshikazu Isomura and Tomoki Fukai. State-space analysis of behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement. Society for Neuroscience (SfN) 2014, Washinton DC, USA. Nov 16, 2014 POSTER

Thomas Sharp, Hideaki Shimazaki, Yoshikazu Isomura and Tomoki Fukai. Behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement, Neuro2014, Yokohama, Japan. Sep 11, 2014 POSTER

Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S Nader Rasuli. Theoretical study on spike-timing probability in a pair of pre-post synaptic neurons. Neuro2014, Yokohama, Japan. Sep 11, 2014 POSTER

Shimazaki H. Simultaneous silence explains structured higher-order interactions of neural populations. June 3 11:00-12:00 Place: CiNet 1F Conference Room A, TALK

Shimazaki H. Simultaneous silence explains structured higher-order interactions of neural populations. 京都大学セミナー, June 2 TALK

Tom Sharp*, Hideaki Shimazaki, Yoshikazu Isomura and Tomoki Fukai. Behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement. Workshop on data mining in neuroscience. National Institute of Informatics, Tokyo, Japan. May 28-29, 2014 TALK

HaDi MaBouDi, Hideaki Shimazaki, Hamid Soltanian-Zadeh, Shun-ichi Amari. Bimodal Distributions of Local Phase Variables in Natural Images. The 2014 VSS Annual Meeting, St. Pete Beach, Florida. May 18, 2014 POSTER

HaDi MaBouDi, Hideaki Shimazaki, Mehdi Abouzari, Shun-ichi Amari, Hamid Soltanian-Zadeh, Statistical inference for directed phase coupling in neural oscillators. Computational and Systems Neuroscience (Cosyne) 2014. Feb 27 Salt Lake City, USA. POSTER

島崎秀昭. State-space analysis of higher-order interactions in parallel event sequences 第15回ノンパラメトリック統計解析とベイズ統計 慶応義塾大学三田キャンパス 2014年3月19日 TALK

島崎秀昭. 高次相関を伴う神経回路網活動:局所回路の計算原理を求めて. 神経科学と統計科学の対話4. 統計数理研究所 2013年3月17日 TALK

Shimazaki H., Sadeghi K., Ikegaya Y., Toyoizumi T. Structured higher-order interactions explain the simultaneous silence of neural populations. 脳と心のメカニズム 第14回 冬のワークショップ 2014年1月8日(水)-10日(金) ポスター発表

島崎秀昭「留学という選択」 大学院留学・ポスドク留学・語学留学・サマースクールなど異なるタイプの留学についてお話します.また日本に来る留学生への対応や海外での講義体験などの国際交流についてもご紹介します.脳科学若手の会 2014年1月25日(日)

 

Seminar, Conference, Workshop in 2013

Shimazaki H., Sadeghi K., Ikegaya Y., Toyoizumi T., The simultaneous silence of neurons explains structured higher-order interactions in ensemble spiking activity, SfN2013. POSTER

Shimazaki H., TBA, ELC International Meeting on ''Inference, Computation, and Spin Glasses'' (ICSG2013), Sapporo, Japan. July 28-30, 2013 TALK (Invited)

Shimazaki H., Higher-order interactions in population activity of hippocampal CA3 neurons, Workshop on statistical analysis of neurophysiological and clinical data, Kyoto, Japan. TALK

Shimazaki H., Estimating Time-varying Higher-order Neuronal Interactions in Awake Behaving Animals, Modeling Neural Activity: Statistics, Dynamical Systems, and Networks, Lihue, Hawaii, USA. 2013 June 26-28 TALK (Selected)

Shimazaki H., Sadeghi K., Ikegaya Y., Toyoizumi T., The simultaneous silence of neurons explains higher-order interactions in ensemble spiking activity, Neuro2013, Kyoto, Japan. Jun. 20 POSTER

Shimazaki H. Estimating dynamic neural interactions in awake behaving animals. The 3rd Mathematical Neuroscience Workshop in School of Mathematics, Institute for Research in Fundamental Sciences (IPM). Tehran, Iran. Mar. 13 TALK (Invited)

Shimazaki H. The Simultaneous Silence of Neurons Explains Higher-Order Interactions in Ensemble Spiking Activity. The 3rd Mathematical Neuroscience Workshop in School of Mathematics, Institute for Research in Fundamental Sciences (IPM). Tehran, Iran. Mar. 13 TALK (Invited)

島崎秀昭. 高次相関を伴う神経回路網の活動と情報コーディング 玉川大学脳科学若手の会 第88回談話会 Feb 22 TALK (Invited)

Shimazaki H., Sadeghi K., Ikegaya Y., Toyoizumi T. The simultaneous silence of neurons explains structured higher-order interactions in spontaneous spiking activity. 神経科学と統計科学の対話3. 統計数理研究所 Feb 18-19 TALK

 

Seminar, Conference, Workshop in 2012

Shimazaki H., Kolia Sadeghi, Yuji Ikegaya, Taro Toyoizumi. Joint inactivation statistics of population spiking activities. RIKEN BSI Retreat 2012, Nov 12-13, Karuizawa, Japan

Shimazaki H. The simultaneous silence of neurons explains structured higher-order interactions in ensemble spiking activity. BSI Lunch Seminar 2012 Nov. 8

Shimazaki H., Kolia Sadeghi, Yuji Ikegaya, Taro Toyoizumi. Joint inactivation statistics of population spiking activities. Workshop on statistical aspects of neural coding. Nov 1-2. Kyoto University & Ritsumeikan University.

Shimazaki H. Tracking Dynamic Neural Interactions in Awake Behaving Animals. Workshop on neural information flow, Kyoto University, Kyoto Jun 20 2012 TALK (Invited)

島崎秀昭, 篠本滋. ヒストグラム・カーネル密度推定の神経スパイクデータへの適用:理論と実践 第13回ノンパラメトリック統計解析とベイズ統計 2012年3月29・30日 慶應義塾大学三田キャンパス TALK (Invited)

Shimazaki H., Kolia Sadeghi, Yuji Ikegaya, Taro Toyoizumi, The simultaneous silence of neurons explains higher-order interactions in ensemble spiking activity. Computational and Systems Neuroscience (Cosyne) 2012. Salt Lake City, USA. 2012 Feb 23-26 POSTER (Reviewed)

Shimazaki H. 非線形セミナー 神経細胞の高次スパイク相関:状態空間モデルによる解析. 京都大学理学部物理学第一教室 2012 Feb 2 TALK (Invited)

 

Seminar, Conference, Workshop in 2011

島崎秀昭, 小山慎介. 神経スパイク解析における状態空間モデル,GLMの応用. 統計科学と神経科学の対話2 2011年 12月26-27日 [TALK, Invited]

Shimazaki H., Amari S., Brown E. N., and Gruen S. Dynamics of Higher-order Spike Correlation in an Awake Behaving Monkey: Analysis by a State-space Model. RIKEN BSI Retreat, Karuizawa, Japan. Oct 31 POSTER

Shimazaki H., Ikegaya Y., and Toyoizumi T. A New Sparse Log-linear Model for Simultaneously Active and Inactive Neurons. RIKEN BSI Retreat, Karuizawa, Japan. Oct 31 POSTER

Shimazaki H. and Brown E.N. Copula-based Mixture Time-series Model of Continuous and Point Processes for Synthetic Analysis of Neural Signals. RIKEN BSI Retreat, Karuizawa, Japan. Oct 31 POSTER

島崎秀昭 脳の高次機能と動的高次スパイク相関:状態空間モデルによる解析, 統計神経科学ミニワークショップ 統計数理研究所 9月8日 [TALK, Invited]

Shimazaki H. and Brown E. N. Constructing a joint time-series model of continuous and Bernoulli/Poisson processes using a copula Computational and Systems Neuroscience 2011 Salt Lake City, USA. Feb 24-27 POSTER (Reviewed)

 

Seminar, Conference, Workshop in 2010

Shimazaki H. Analysis of Dynamic Neural Spike Data: From Firing Rates to Spike Correlations. Neurostatistics Working Group Seminar, Dept. of Biostatistics, Harvard University, Dec 1 [TALK, Invited] link

Shimazaki H. Detection of dynamic cell assemblies by the Bayes Factor. Workshop on spatio-temporal neuronal computation, Kyoto University, Japan Sep 6-7 [TALK, Invited]

Shinomoto S*, Shimazaki H, and Shimokawa T. Characterizing neuronal firing with the rate and the irregularity. Neuro2010, Kobe, Japan Sep. 2 S3-10-1-3 [abst]

Shimazaki H., Gruen S., and Amari S. Analysis of subsets of higher-order correlated neurons based on marginal correlation coordinates. Cosyne 2010, Salt Lake City, USA. 1-63 Feb 25-28 [abst]

 

Seminar, Conference, Workshop in 2009

Shimazaki H., Amari S., Brown E. N., and Gruen S. State-space Model of Dynamic Spike Correlation. Japanese Neural Network Society 2009. Sendai, Japan. Sept. 24-26. Talk+Poster [Japanese Neural Network Society 2009 Distinguished Research Award]

Shimazaki H. Analysis of Dynamic Spike Data: From Spike Rate to Multiple Neuron Spike Correlation. The 6th Brain Lunch Seminar. RIKEN Brain Science Institute, Saitama, Japan. Sep. 8. TALK

Shimazaki H., Amari S., Brown E. N., and Gruen S. Bayes Factor Analysis for Detection of Time-dependent Higher-order Spike Correlations. CNS2009 in Berlin, Germany. Jul 18-23 P99 POSTER [abstract]

Shimazaki H. and Shinomoto S. Histogram binwidth and kernel bandwidth selection for the Spike-rate estimation. CNS2009. Berlin, Germany. Jul 18-23 P116 POSTER [abstract]

Shimazaki H., Amari S., Brown E. N., and Gruen S. Estimating time-varying spike correlations from parallel spike sequences, German-Japanese Workshop "Computational and Systems Neuroscience", Berlin, May 25-28, 2009 POSTER

Shimazaki H., Amari S., Brown E. N., and Gruen S. State-space Analysis on Time-varying Correlations in Parallel Spike Sequences. IEEE ICASSP2009 Special Session on `Signal Processing for Neural Spike Trains', Taipei, Taiwan. Apr 24 SS-L10.4 [LECTURE (Invited)]

Shimazaki H., Amari S., Brown E. N., and Gruen S. Detection of non-stationary higher-order spike correlation. Cosyne 2009, Salt Lake City, USA. Feb 26 -Mar 3 POSTER II-62 [abstract]

 

Seminar, Conference, Workshop in 2008

Shimazaki H., Amari S., Brown E. N., and Gruen S. State-space Analysis on Time-varying Higher-order Spike Correlations. NIPS2008 Workshop on `Statistical Analysis and Modeling of Response Dependencies in Neural Populations', Whistler, Canada Dec 13, 17:00-17:30 [abstract] [TALK (Invited)]

Shimazaki H. and Gruen S. Selecting a state-space model of higher-order correlations in parallel spike trains from competing hierarchical log-linear models. RIKEN BSI Retreat 2008, Karuizawa, Japan. Nov 4-5 POSTER

Shimazaki H. and Gruen S. IBIS, Sendai, Japan. Oct 29 Poster. in Japanese.

Shimazaki H. and Shinomoto S. Spike-rate Estimation with Locally Adaptive Kernel Method . Japanese Neural Network Society 2008. Sep 24-26 Tsukuba, Japan. PS3-4, p186-187 pdf in Japanese. [Spotlight Poster]

Shimazaki H. Smoothing methods for spike data: From single neurons rate estimation to multiple neurons correlation analysis. Joint Journal Club at RIKEN BSI. Jun 17

Shimazaki H. and Gruen S. Estimating time-dependent higher-order interactions in parallel spike trains. Neuro2008, Tokyo, Japan. Jul 9-11 POSTER P1-w04 [abstract]

Shimazaki H., Brown E. N. and Gruen S. State-space Analysis on Time-dependent Correlation in Parallel Spike Trains. Statistical Analysis of Neuronal Data (SAND4), Pittsburgh, PA, USA. May 29-31 POSTER [abstract]

 

Seminar, Conference, Workshop in 2007

Shimazaki H. and Gruen S. Estimation of Time-dependent Higher-Order Interactions in Parallel Spike Trains. Riken BSI Retreat, Karuizawa, Japan. Nov 26-28 POSTER

Shimazaki H. and Shinomoto S. Kernel Width Optimization in the Spike-rate Estimation. Neural Coding 2007, Montevideo, Uruguay. Nov 7 POSTER [pdf] [Best Poster Award]

Shimazaki H. and Shinomoto S. Optimization of a Histogram of Spike Data. Neuro2007, Yokohama, Japan. Sep 11 POSTER P2-k22

Shimazaki H. A Recipe for Optimizing a Time Histogram of Spike Data. Riken BSI Forums at RIKEN Brain Science Institute, Wako, Japan. Host: Sonja Gruen Apr 17 TALK

Shimazaki H. A recipe for constructing a Peri-stimulus Time Histogram. The Boadian Seminar at Mind/Brain Institute, Johns Hopkins University. Host: Ernst Niebur. Mar 1 TALK

Shimazaki H. and Shinomoto S. A recipe for optimizing a time-histogram with variable bin sizes. Computational and Systems Neuroscience 2007, Salt Lake City, Feb 22-27 POSTER

 

Seminar, Conference, Workshop in 2006

Shimazaki H. and Shinomoto S. A recipe for optimizing a time-histogram Neural Information Processing Systems Dec 4-9, Whistler, B. C. POSTER [pdf] [Spotlight Poster]

Shimazaki H. A method to optimize a time histogram by correcting onset latencies of spike sequences Japanese Neural Network Society JNNS2006 Sep 1-21 Nagoya, Japan O4-1 ORAL+POSTER [Japanese Neural Network Society 2007 Young Researcher Award]

Shimazaki H. Self-organized criticality by natural selection. Frontiers in Dynamics: Physical and Biological Systems Tokyo, Japan, May 22-24, 2006, Poster [abstract]

Shimazaki H. and Shinomoto S. Recipes for constructing an optimal time histogram. Statistical Analysis of Neuronal Data (SAND3), Pittsburgh, PA, May 12-13, 2006, Poster [abstract]

 

 

| Research | Publications | Conferences | Awards | Curriculum Vitae |

Award, Grant & Financial Aid
 

Award

Japanese Neural Network Society 2009 Research Award

Japanese Neural Network Society 2007 Young Researcher Award

 

Grant and Stipend

2010-2011 Excellent Young Researchers Overseas Visit Program by JSPS, Stipend

2008-2011 Research Fellowship for Young Scientists by JSPS*, Stipend and Research Grant

2006-2008 Research Fellowship for Young Scientists by JSPS*, Stipend and Research Grant

2004-2006 Japan Student Services Organization, Stipend

2002-2004 Johns Hopkins University, Dept. of Neuroscience (Solo Snyder Foundation), Tuition and Stipend

2000-2002 Murata Overseas Scholarship, Tuition, Stipend, and Research Grant

* JSPS: Japan Society for the Promotion of Science

 

Letter

Letter of Appreciation from the RIKEN president Ryoji Noyori (2009/10)

 

Travel Award

2006/12 The 21st Century COE Center for Diversity and Universality in Physics. NIPS2006 Travel Aid

2006/5 Tamura Memorial Foundation, Frontiers in Dynamics: Physical and Biological Systems. Travel Aid

2006/1 Japanese Neural Network Society. Travel Aid

 

 

| Research | Publications | Conferences | Awards | Curriculum Vitae |
 

Curriculum Vitae

Please click here for my full CV.