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Shimazaki, Hideaki

Graduate School of Informatics, Department of Informatics Associate Professor

Shimazaki, Hideaki
list
    Last Updated :2024/02/21

    Basic Information

    Faculty

    • Faculty of Engineering

    Email Address

    • Email Address

      shimazaki.hideaki.8xkyoto-u.ac.jp

    Professional Memberships

    • Society for Neuroscience
    • 日本神経科学学会
    • 日本神経回路学会

    Academic Degree

    • 24 Nov. 2003
      ジョンズ・ホプキンス大学修士(Neuroscience)
    • 23 Mar. 2007
      京都大学博士(理学)

    Academic Resume (Graduate Schools)

    • 京都大学, 大学院理学研究科博士後期課程物理学・宇宙物理学専攻, 修了
    • ジョンズ・ホプキンス大学, 大学院医学系研究科神経科学専攻, 修了

    Academic Resume (Undergraduate School/Majors)

    • 慶應義塾大学, 理工学部物理情報工学科, 卒業

    Research History

    • From Oct. 2022, To Present
      Kyoto University, Graduate School of Informatics, Associate Professor
    • From Apr. 2020, To Sep. 2022
      Hokkaido University, Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Associate Professor (Specially-appointed)
    • From Apr. 2017, To Mar. 2020
      Kyoto University, Graduate School of Informatics Department of Intelligence Science and Technology, Project-specific Associate Professor
    • From Apr. 2016, To Mar. 2020
      Honda Research Institute, Senior Scientist

    Profile

    • Profile

      Hideaki Shimazaki is a specially-appointed associate professor at the Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) of Hokkaido University in Japan. Before that, he took joint positions in industry and academia as a senior scientist at Honda Research Institute Japan Co., Ltd. and an associate professor at the Graduate School of Informatics in Kyoto University. His research focuses on uncovering the intelligence of organisms and machines using physics, statistics, and machine learning methods, emphasizing data analysis on spiking neural activities. He received M.A. in neuroscience at Johns Hopkins University in 2003 and Ph.D. in physics at Kyoto University in 2007. After his Ph.D., he pursued postdoctoral training in computational neuroscience at RIKEN Brain Science Institute and MIT Department of Brain and Cognitive Sciences.

    ID,URL

    researchmap URL

    list
      Last Updated :2024/02/21

      Research

      Research Interests

      • Information Theory
      • Machine Learning
      • Statistical Physics
      • Neural Coding

      Research Areas

      • Life sciences, Basic brain sciences
      • Natural sciences, Applied mathematics and statistics
      • Informatics, Statistical science

      Papers

      • Zebrafish capable of generating future state prediction error show improved active avoidance behavior in virtual reality
        Makio Torigoe; Tanvir Islam; Hisaya Kakinuma; Chi Chung Alan Fung; Takuya Isomura; Hideaki Shimazaki; Tazu Aoki; Tomoki Fukai; Hitoshi Okamoto
        Nature Communications, 29 Sep. 2021
      • Neural engine hypothesis
        Shimazaki, H.
        Dynamic Neuroscience: Statistics, Modeling, and Control, 2017
      • A projected nonlinear state-space model for forecasting time series signals
        Christian Donner; Anuj Mishra; Hideaki Shimazaki
        arXiv, 23 Dec. 2023, Last author, Corresponding author
      • Alternating shrinking higher-order interactions for sparse neural population activity
        Ulises Rodríguez-Domínguez; Hideaki Shimazaki
        arXiv, Aug. 2023, Last author, Corresponding author
      • Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model
        Miguel Aguilera; Masanao Igarashi; Hideaki Shimazaki
        Nature Communications, 23 Jun. 2023, Peer-reviewed, Last author
      • Uncovering hidden network architecture from spiking activities using an exact statistical input-output relation of neurons.
        Safura Rashid Shomali; Seyyed Nader Rasuli; Majid Nili Ahmadabadi; Hideaki Shimazaki
        Communications biology, 15 Feb. 2023, Peer-reviewed, Last author, Corresponding author
      • Optimization and inference of bin widths for histogramming inelastic neutron scattering spectra
        Kazuyoshi Tatsumi; Yasuhiro Inamura; Maiko Kofu; Ryoji Kiyanagi; Hideaki Shimazaki
        Journal of Applied Crystallography, 01 Jun. 2022, Peer-reviewed, Last author
      • Canonical neural networks perform active inference
        Takuya Isomura; Hideaki Shimazaki; Karl J. Friston
        Communications Biology, 14 Jan. 2022, Peer-reviewed
      • Future state prediction errors guide active avoidance behavior by adult zebrafish.
        Makio Torigoe; Tanvir Islam; Hisaya Kakinuma; Chi Chung Alan Fung; Takuya Isomura; Hideaki Shimazaki; Tazu Aoki; Tomoki Fukai; Hitoshi Okamoto
        Nature Communications, 29 Sep. 2021, Peer-reviewed
      • A unifying framework for mean field theories of asymmetric kinetic Ising systems
        Miguel Aguilera; S. Amin Moosavi; Hideaki Shimazaki
        Nature Communications, 19 Jan. 2021, Peer-reviewed, Last author
      • Hunger Potentiates the Habenular Winner Pathway for Social Conflict by Orexin-Promoted Biased Alternative Splicing of the AMPA Receptor Gene.
        Haruna Nakajo; Ming-Yi Chou; Masae Kinoshita; Lior Appelbaum; Hideaki Shimazaki; Takashi Tsuboi; Hitoshi Okamoto
        Cell reports, 23 Jun. 2020, Peer-reviewed
      • Bayesian and thermodynamic view on dynamics of learning and recognition in organisms
        Hideaki Shimazaki
        The Brain & Neural Networks, Sep. 2019
      • Online estimation of multiple dynamic graphs in pattern sequences
        Hideaki Shimazaki
        2019 International Joint Conference on Neural Networks (IJCNN), 19 Jan. 2019, Peer-reviewed
      • State-space analysis of an ising model reveals contributions of pairwise interactions to sparseness, fluctuation, and stimulus coding of monkey V1 neurons
        Gaudreault, J.; Shimazaki, H.
        Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Oct. 2018, Peer-reviewed, Last author
      • The principles of adaptation in recognition and behavior
        Hideaki Shimazaki
        The Brain & Neural Networks, Sep. 2018
      • How does transient signaling input affect the spike timing of postsynaptic neuron near the threshold regime: an analytical study
        Safura Rashid Shomali; Majid Nili Ahmadabadi; Hideaki Shimazaki; Seyyed Nader Rasuli
        Journal of Computational Neuroscience, 01 Apr. 2018, Peer-reviewed
      • Computational Neuroscience: Mathematical and Statistical Perspectives
        Robert E. Kass; Shun-Ichi Amari; Kensuke Arai; Emery N. Brown; Casey O. Diekman; Markus Diesmann; Brent Doiron; Uri T. Eden; Adrienne L. Fairhall; Grant M. Fiddyment; Tomoki Fukai; Sonja Grün; Matthew T. Harrison; Moritz Helias; Hiroyuki Nakahara; Jun-Nosuke Teramae; Peter J. Thomas; Mark Reimers; Jordan Rodu; Horacio G. Rotstein; Eric Shea-Brown; Hideaki Shimazaki; Shigeru Shinomoto; Byron M. Yu; Mark A. Kramer
        Annual Review of Statistics and Its Application, 07 Mar. 2018, Peer-reviewed
      • 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
        HaDi MaBouDi; Hideaki Shimazaki; Martin Giurfa; Lars Chittka
        PLOS COMPUTATIONAL BIOLOGY, Jun. 2017, Peer-reviewed
      • Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations
        Christian Donner; Klaus Obermayer; Hideaki Shimazaki
        PLOS COMPUTATIONAL BIOLOGY, Jan. 2017, Peer-reviewed, Last author
      • Similarity in Neuronal Firing Regimes across Mammalian Species
        Yasuhiro Mochizuki; Tomokatsu Onaga; Hideaki Shimazaki; Takeaki Shimokawa; Yasuhiro Tsubo; Rie Kimura; Akiko Saiki; Yutaka Sakai; Yoshikazu Isomura; Shigeyoshi Fujisawa; Ken-ichi Shibata; Daichi Hirai; Takahiro Furuta; Takeshi Kaneko; Susumu Takahashi; Tomoaki Nakazono; Seiya Ishino; Yoshio Sakurai; Takashi Kitsukawa; Jong Won Lee; Hyunjung Lee; Min Whan Jung; Cecilia Babul; Pedro E. Maldonado; Kazutaka Takahashi; Fritzie I. Arce-McShane; Callum F. Ross; Barry J. Sessle; Nicholas G. Hatsopoulos; Thomas Brochier; Alexa Riehle; Paul Chorley; Sonja Gruen; Hisao Nishijo; Satoe Ichihara-Takeda; Shintaro Funahashi; Keisetsu Shima; Hajime Mushiake; Yukako Yamane; Hiroshi Tamura; Ichiro Fujita; Naoko Inaba; Kenji Kawano; Sergei Kurkin; Kikuro Fukushima; Kiyoshi Kurata; Masato Taira; Ken-Ichiro Tsutsui; Tadashi Ogawa; Hidehiko Komatsu; Kowa Koida; Keisuke Toyama; Barry J. Richmond; Shigeru Shinomoto
        JOURNAL OF NEUROSCIENCE, May 2016, Peer-reviewed
      • Social conflict resolution regulated by two dorsal habenular subregions in zebrafish
        Ming-Yi Chou; Ryunosuke Amo; Masae Kinoshita; Bor-Wei Cherng; Hideaki Shimazaki; Masakazu Agetsuma; Toshiyuki Shiraki; Tazu Aoki; Mikako Takahoko; Masako Yamazaki; Shin-ichi Higashijima; Hitoshi Okamoto
        SCIENCE, Apr. 2016, Peer-reviewed
      • Representation of higher-order statistical structures in natural scenes via spatial phase distributions
        HaDi MaBouDi; Hideaki Shimazaki; Shun-ichi Amari; Hamid Soltanian-Zadeh
        VISION RESEARCH, Mar. 2016, Peer-reviewed
      • Approximate Inference Method for Dynamic Interactions in Larger Neural Populations
        Christian Donner; Hideaki Shimazaki
        NEURAL INFORMATION PROCESSING, ICONIP 2016, PT III, 2016, Peer-reviewed
      • Neurons as an Information-theoretic Engine
        Hideaki Shimazaki
        arXiv, Dec. 2015
      • Simultaneous silence organizes structured higher-order interactions in neural populations
        Hideaki Shimazaki; Kolia Sadeghi; Tomoe Ishikawa; Yuji Ikegaya; Taro Toyoizumi
        Scientific Reports, Apr. 2015, Peer-reviewed
      • Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: A simulation study
        Hideaki Shimazaki
        Journal of Physics: Conference Series, 2013, Peer-reviewed, Invited
      • State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data
        Hideaki Shimazaki; Shun-ichi Amari; Emery N. Brown; Sonja Gruen
        PLOS COMPUTATIONAL BIOLOGY, Mar. 2012, Peer-reviewed
      • Kernel bandwidth optimization in spike rate estimation
        Hideaki Shimazaki; Shigeru Shinomoto
        JOURNAL OF COMPUTATIONAL NEUROSCIENCE, Aug. 2010, Peer-reviewed
      • STATE-SPACE ANALYSIS ON TIME-VARYING CORRELATIONS IN PARALLEL SPIKE SEQUENCES
        Hideaki Shimazaki; Shun-ichi Amari; Emery N. Brown; Sonja Gruen
        2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, 2009, Peer-reviewed, Invited
      • A method for selecting the bin size of a time histogram
        Hideaki Shimazaki; Shigeru Shinomoto
        NEURAL COMPUTATION, Jun. 2007, Peer-reviewed
      • A recipe for optimizing a time-histogram
        Shimazaki H; Shinomoto S
        Advances in Neural Information Processing Systems, 2007, Peer-reviewed
      • Correlated Multiplicative Modulation in Coupled Oscillator Systems : A Model of Selective Attention(Oscillation, Chaos and Network Dynamics in Nonlinear Science) :
        SHIMAZAKI Hideaki; NIEBUR Ernst
        Progress of theoretical physics. Supplement, 2006
      • Phase transitions in multiplicative competitive processes
        Hideaki Shimazaki; Ernst Niebur
        Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Jul. 2005, Peer-reviewed
      • Spatial analysis of spike-timing-dependent LTP and LTD in the CAI area of hippocampal slices using optical imaging
        Minoru Tsukada; Takeshi Aihara; Yuki Kobayashi; Hideaki Shimazaki
        HIPPOCAMPUS, 2005, Peer-reviewed, Last author
      • Spatial Distributions of Hippocampal LTP/LTD Induced Electrically from Schaffer Collaterals and Stratum Oriens with Relative Timing
        KABAYASHI Yuki; SHIMAZAKI Hide-aki; AIHARA Takeshi; TSUKADA Minoru
        The Brain & Neural Networks, 05 Jun. 2001

      Misc.

      • Locally Adaptive Kernel Density Estimation on Quasi-Elastic Neutron Scattering Energy Profiles
        K. Tatsumi; M. Matsuura; H. Shimazaki; Y. Inamura
        MLF Annual Report 2020, 2021
      • The principles of adaptation in organisms and machines II: Thermodynamics of the Bayesian brain
        Hideaki Shimazaki
        arXiv, 23 Jun. 2020, Lead author
      • Structured Mean-field Variational Inference and Learning in Winner-take-all Spiking Neural Networks
        Shashwat Shukla; Hideaki Shimazaki; Udayan Ganguly
        14 Nov. 2019
      • 2019 年度時限研究会 システム神経科学スプリングスクール 2019 (SNSS2019) 実施報告書
        中江健; 浦久保秀俊; 東広志; 田中康裕; 島崎秀昭; 尾藤晴彦; 石井信
        日本神経回路学会誌, Sep. 2019
      • 知覚の時間構造: 認知心理学・神経生理学・計算論の視点から
        島崎秀昭; 小川正; 熊田孝恒
        日本神経回路学会誌, Sep. 2019
      • The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamics
        Hideaki Shimazaki
        arXiv, 28 Feb. 2019
      • Uncovering network architecture using an exact statistical input-output relation of a neuron model
        Safura Rashid Shomali; Majid Nili Ahmadabadi; Seyyed Nader Rasuli; Hideaki Shimazaki
        bioRxiv, Nov. 2018
      • 特集「自由エネルギー原理入門」
        島崎 秀昭; 吉田 正俊; 田口 茂; 磯村 拓哉; 田中 琢真; 大羽 成征; 乾 敏郎
        日本神経回路学会誌, Sep. 2018
      • 2017 年度時限研究会 「脳の理論から身体・世界へ:行動と認識への再挑戦」実施報告
        島崎 秀昭; 大羽 成征; 吉田 正俊
        日本神経回路学会誌, Dec. 2017, Invited
      • Learning Complex Representations from Spatial Phase Statistics of Natural Scene
        MaBouDi H; Shimazaki H; Soltanian-Zadeh H; Amari S
        bioRxiv, Mar. 2017
      • Simultaneous silence organizes structured higher-order interactions in neural populations (vol 5, 9821, 2015)
        Hideaki Shimazaki; Kolia Sadeghi; Tomoe Ishikawa; Yuji Ikegaya; Taro Toyoizumi
        SCIENTIFIC REPORTS, Oct. 2015
      • 『留学』という選択
        島崎 秀昭
        脳科学若手の会, 25 Jan. 2014, Invited
      • F1000Prime Recommendation
        Fukai T; Shimazaki
        Optogenetic activation of an inhibitory network enhances feedforward functional connectivity in auditory cortex, Jan. 2014, Invited
      • Analysis of Neural Activities using Statistical Models
        SHIMAZAKI Hideaki
        Seibutsu Butsuri, 2013, Peer-reviewed, Invited
      • Analysis of Multiple Neural Spike Train Data using the Log-linear Model : From Stationary to Time-Varying Spike Correlation
        Shimazaki H
        The Brain & neural networks, Dec. 2011, Peer-reviewed, Invited
      • Characterizing neuronal firing with the rate and the irregularity
        Shigeru Shinomoto; Hideaki Shimazaki; Takeaki Shimokawa
        NEUROSCIENCE RESEARCH, 2010
      • Estimating time-dependent higher-order interactions in parallel spike trains
        Hideaki Shimazaki; Sonja Gruen
        NEUROSCIENCE RESEARCH, 2008
      • 離散力学系の競争モデルに見られる相転移 : 統計物理学の視点から(経済物理学II-社会・経済への物理学的アプローチ-,京都大学基礎物理学研究所2005年度後期研究会)
        島崎秀昭
        物性研究, Jul. 2006
      • 脳と心のメカニズム第六回冬のワークショップ参加報告
        島崎秀昭
        日本神経回路学会誌 = The Brain & neural networks, Jun. 2006
      • 離散力学系の競争モデルに見られる相転移 : 統計物理学の視点から(経済物理学II-社会・経済への物理学的アプローチ-,京都大学基礎物理学研究所2005年度後期研究会)
        島崎秀昭
        素粒子論研究, 20 May 2006
      • 25pYF-4 Phase transitions observed in competition modeled by a discrete dynamical system and its approach to the transition point by natural selection
        Shimazaki Hideaki
        Meeting abstracts of the Physical Society of Japan, 04 Mar. 2005
      • The spatial distribution of LTP and LTD induced by input-output coincidence in hippocampal CA1 area
        KOBAYASHI Yuki; SHIMAZAKI Hide-aki; OGIKUBO Yoshinobu; MIZOGUCHI Kenji; AIHARA Takeshi; TSUKADA Minoru
        IEICE technical report. Neurocomputing, 15 Mar. 2000
      • Identification of LTP/LTD Characteristic Curve by Spike Timing : Approach with Optical Recording Method
        SHIMAZAKI Hide-aki; KOBAYASHI Yuki; OSAWA Sayaka; MORITA Minoru; MIZOGUCHI Kenji; AIHARA Takeshi; TSUKADA Minoru
        IEICE technical report. Neurocomputing, 15 Mar. 2000

      Presentations

      • Emergence of sparse coding via dendritic computation in a population of canonical visual binary neurons
        Ulises Rodrıguez-Domınguez; Hideaki Shimazaki
        NeuroVisión 2023: Joint Meeting on Neuroimage Processing and Computational Vision, Oct. 2023, Mathematics Research Center (CIMAT) and the Institute of Neurobiology of the UNAM
      • Application of Variable Kernel Density Estimation to Analyses of Quasi Elastic Neutron Scattering
        K. Tatsumi; M. Matsuura; T. Yamada; Y. Kawakita; H. Shimazaki
        日本中性子科学会第23回年会(JSNS2023), Sep. 2023, 日本中性子科学会
      • 非定常・非対称な機能的結合の推定に基づく神経スパイク活動の不可逆性の検証
        石原憲; 島崎秀昭
        日本神経回路学会, 05 Sep. 2023, 日本神経回路学会
      • Analysis of nonequilibrium neural spiking activity using a state-space kinetic Ising model
        Ken Ishihara; Hideaki Shimazaki
        ニューロコンピューティング研究会(NC), 01 Jul. 2023, ニューロコンピューティング研究会(NC)
      • 神経符号化研究の歴史と最前線
        神経回路学会2023 サテライト, Sep. 2023
      • Deciphering hidden circuits from higher-order statistics of neural activity
        Hideaki Shimazaki
        CSN Virtual Seminars, 05 Jul. 2023, Computational and Systems Neuroscience (INM-6) & Theoretical Neuroscience (IAS-6), Forschungszentrum Jülich, Invited
      • Introduction to computational theories of the brain: from the efficient coding hypothesis to the Bayesian brain and free energy principle
        Hideaki Shimazaki
        日本神経科学会, 04 Aug. 2023, Invited
      • 大脳皮質局所回路の結合推定と符号化方式
        島崎秀昭
        第37回 全脳アーキテクチャ勉強会, 17 Feb. 2023, WBA勉強会実行委員会, Invited
      • 脳の認識のダイナミクスと時間遅れ
        島崎秀昭
        2022年度 RIMS 共同研究(公開型)「時間遅れ系と数理科学:理論と応用の新たな展開に向けて」, 17 Nov. 2022, Invited
      • 神経活動の高次統計量から回路構造を読み解く
        島崎秀昭
        日本神経回路学会 オータムスクールASCONE2022, 14 Nov. 2022, 日本神経回路学会, Invited
      • 神経科学研究の理論的アプローチ
        島崎秀昭
        京都大学情報学研究科システム科学専攻 集中講義, 12 Sep. 2022, Invited
      • 脳の自由エネルギー原理:背景と応用
        島崎秀昭
        応用脳科学コンソーシアム アドバンスコース「脳に学ぶAI」, 09 Sep. 2022, Invited
      • 神経細胞集団活動の数理とデータ解析
        島崎秀昭
        日本応用数理学会 2022年度年会, 08 Sep. 2022
      • Consciousness and the thermodynamics of the Bayesian brain
        Hideaki Shimazaki
        International Symposium on Artificial Intelligence and Brain Science 2022, 05 Jul. 2022, Invited
      • The state-space kinetic Ising model for nonequilibrium neuronal dynamics
        Ken Ishihara; Hideaki Shimazaki
        NEURO2022, 02 Jul. 2022
      • State-space analysis for neural population dynamics
        Hideaki Shimazaki; Ken Ishihara; Ulises Rodriguez Dominguez; Sai Sumedh Hindupur; Miguel Aguilera; S. Amin Moosavi; Magalie Tatischeff; Jimmy Gaudreault; Christian Donner
        Neuro2022, 30 Jun. 2022, Invited
      • Stochastic thermodynamics of a non-equilibrium Sherrington-Kirkpatrick model
        Miguel Aguilera; Masanao Igarashi; Hideaki Shimazaki
        The Workshop on Stochastic Thermodynamics III, 26 May 2022
      • Application of adaptive kernel density estimation to quasi-elastic neutron scattering energy profiles
        巽一厳; 松浦真人; 島崎秀昭; 稲村泰弘
        2021年度量子ビームサイエンスフェスタ
      • 標準リカレントネットワークモデルでつなぐ皮質回路の構造・機能・作動原理
        島崎秀昭
        生理学研究所研究会「大脳皮質を中心とした神経回路:構造と機能、その作動原理」, Dec. 2021, 生理学研究所, Invited
      • Bayesian Computation of Generic Neural Binary Code by Local Competition
        Ulises Rodriguez Dominguez; Hideaki Shimazaki
        The 44th Annual Meeting of the Japan Neuroscience Society (Neuro 2021), 31 Jul. 2021
      • An information geometry approach for unifying mean field theories of asymmetric kinetic Ising systems
        Miguel Aguilera; S. Amin Moosavi; Hideaki Shimazaki
        Entropy 2020: The Scientific Tool of the 21st Century, 07 May 2021
      • 非定常・非平衡イジングモデルによる神経細胞集団活動の解明
        島崎秀昭
        データ駆動生物学ワークショップ, 23 Mar. 2021, 本田直樹, Invited
      • Revealing hidden microcircuits using higher-order interactions of neuronal activity
        Safura Rashid Shomali; S. Nader Rasuli; Hideaki Shimazaki
        The 3rd Sharif Neuroscience Symposium, 04 Mar. 2021
      • 脳への計算論的アプローチ概説:視覚野の理論を中心に
        島崎秀昭
        日本視覚学会2021年冬季大会, 21 Jan. 2021, 日本視覚学会, Invited
      • 神経活動の数理モデリングで回路・情報,そして意識へ迫る
        島崎秀昭
        CHAIN Webiner, 03 Aug. 2020, 人間知・脳・AI研究教育センター
      • Higher-order interactions induced by strong shared inputs
        Safura Rashid Shomali, Seyyed; Nader Rasuli; Hideaki Shimazaki
        Organization for Computational Neurosciences 2020 (CNS*2020), 18 Jul. 2020
      • Effects of structured neural correlations in population coding: beneficial or detrimental?
        Seyedamin Moosavi; Magalie Tatischeff; Bingyue Zhu; Hideaki Shimazaki
        Computational and Systems Neuroscience (Cosyne) 2020, 01 Mar. 2020
      • Inferring network motifs from neural activity using analytic input-output relation of LIF neurons
        Safura Rashid Shomali; Majid Nili Ahmadabadi; Seyyed Nader Rasuli; Hideaki Shimazaki
        Computational and Systems Neuroscience (Cosyne) 2020, 28 Feb. 2020
      • Thermodynamics of the Bayesian brain: A new paradigm for quantifying perceptual capacity of neural dynamics
        Hideaki Shimazaki
        Computational Principles in Active Perception and Reinforcement Learning in the Brain, 14 Feb. 2020, MACS International Symposium, Invited
      • The brain as an information-theoretic engine: A new paradigm for quantifying perceptual capacity of neural dynamics
        Hideaki Shimazaki
        Combining Information theoretic Perspectives on Agency, 28 Jan. 2020, Invited
      • Past and Future of Theoretical Neuroscience: From Bayesian Brain Hypothesis to Neural Engine
        島崎 秀昭
        Singularity Salon, 07 Dec. 2019, Singularity Salon, Invited
      • Past and Future of Theoretical Neuroscience: From Bayesian Brain Hypothesis to Neural Engine
        島崎 秀昭
        Singularity Salon, 16 Nov. 2019, Singularity Salon, Invited
      • Dynamic neural interactions revealed by the state-space Ising model
        Hideaki Shimazaki
        The 7th International Congress on Cognitive Neurodynamics, 29 Sep. 2019
      • Judging between Excitation and Inhibition: Identifying Local Network Architecture by an Analytic Pre-Post Relation
        Safura Rashid Shomali; Majid Nili Ahmadabadi; Seyyed Nader Rasuli; Hideaki Shimazaki
        Bernstein Conference 2019, 18 Sep. 2019
      • Unifying framework for mean field theories of asymmetric kinetic Ising systems
        Miguel Aguilera; Amin Seyed Moosavi; Hideaki Shimazaki
        15th Granada Seminar: Stochastic and Collective Effects in Neural Systems, 17 Sep. 2019
      • 学習と認識の熱力学:ニューラルエンジンとはなにか?
        島崎 秀昭
        生理研研究会2019 認知神経科学の先端 「脳の理論から身体・世界へ」, 02 Sep. 2019, 生理学研究所
      • Visualizing dynamics of cooperative activities of neurons for neural coding studies
        Hideaki Shimazaki
        Data Science, Statistics, & Visualisation (DSSV2019), 13 Aug. 2019, International Association for Statistical Computing, Invited
      • Online Estimation of Multiple Dynamic Graphs in Pattern Sequences
        Jimmy Gaudreault; Arunabh Saxena; Hideaki Shimazaki
        The 2019 International Joint Conference on Neural Networks (IJCNN), 14 Jul. 2019, INNS, IEEE CIS
      • 神経細胞集団活動の統計解析:脳の熱力学に向けて
        島崎 秀昭
        サロン・ド・脳, 07 Jun. 2019, サロン・ド・脳運営委員会
      • Network architecture underlying sparse neural activity characterized by structured higher-order interactions
        Hideaki Shimazaki
        26 Mar. 2019, Kenji Doya
      • Thermodynamic analysis of neural populations by the state-space Ising model
        Magalie Tatischeff; Jimmy Gaudreault; Christian Donner; Hideaki Shimazaki
        Consciousness Research Network (CoRN 2019), 23 Feb. 2019
      • Role of gain-control and neural correlations in efficient stimulus coding
        S. Amin Moosavi; Hideaki Shimazaki
        Consciousness Research Network (CoRN 2019), 23 Feb. 2019
      • 社会神経科学的アプローチによる精神疾患の社会性障害の理解
        島崎秀昭
        平成30年度生理研研究会 第8回社会神経科学研究会, 29 Nov. 2018, 高橋宗良(玉川大学 特任准教授)・定藤規弘(生理研 教授), Invited
      • Thermodynamic analyses of neural populations
        Hideaki Shimazaki; Magalie Tatischeff; Jimmy Gaudreault; Christian Donner
        Analysis and Synthesis for Human/Artificial Cognition and Behaviour, 22 Oct. 2018
      • State-space analysis of an Ising model reveals contributions of pairwise interactions to sparseness, fluctuation, and stimulus coding of monkey V1 neurons
        Jimmy Gaudreault; Hideaki Shimazaki
        The 27th International Conference on Artificial Neural Networks (ICANN2018), 05 Oct. 2018, European Neural Network Society
      • The active inference in decision making by adult zebrafish revealed by in-vivo imaging of the telencephalic neural activities in the closed-loop virtual reality environment
        Makio Torigoe; Islam Tanvir; Hisaya Kakinuma; Fung Chi Chung Alan; Takuya Isomura; Hideaki Shimazaki; Tazu Aoki; Taro Toyoizumi; Tomoki Fukai; Hitoshi Okamoto
        The 41st Annual Meeting of the Japan Neuroscience Society, 27 Jul. 2018
      • スパースな集団活動を生み出す神経ネットワーク構造
        島崎 秀昭
        第6回 数理モデリング研究会, 06 Jul. 2018
      • State-space analysis of an Ising model reveals contributions of pairwise interactions to sparseness, fluctuation, and stimulus coding of monkey V1 neurons
        Jimmy Gaudreault; Arunabh Saxena; Hideaki Shimazaki
        Mechanisms of Brain and Mind The 18th winter workshop, 09 Jan. 2018
      • Network architectures underlying variable, sparse population activity of neurons
        HIDEAKI SHIMAZAKI
        Fluctuations of event occurrences in a variety of networks, 15 Nov. 2017, Shigeru Shinomoto (Kyoto University), Takaaki Aoki (Kagawa University) Ryota Kobayashi (NII), Taro Takaguchi (NICT), Hideaki Shimazaki (Kyoto University, HRI)
      • 神経細胞集団活動の統計数理
        島崎 秀昭
        玉川大学 脳科学ワークショップ, 27 Sep. 2017, 玉川大学, Invited
      • In-vivo imaging of telencephalic neural activities in adult zebrafish performing decision making task in the closed-loop virtual reality environment
        Makio Torigoe; Tanvir Islam; Hisaya Kakinuma; Hideaki Shimazaki; Chi Chung Alan Fung; Tazu Aoki; Tomoki Fukai; Hitoshi Okamoto
        Neuroscience2017, 23 Jul. 2017, Japan Neuroscience Society
      • 神経活動データの時系列モデリング入門
        島崎 秀昭
        第8回脳科学若手の会合宿, 04 Mar. 2017, 脳科学若手の会, Invited
      • Exact analysis of spike­timing and higher­order interactions of neurons at the threshold regime suggests network architecture underlying sparse population activity
        S. R. SHOMALI; M. NILI AHMADABADI; S. RASULI; H. SHIMAZAKI
        Society for Neuroscience 2016, 12 Nov. 2016
      • Estimating dynamic functional networks of larger neural populations
        C. DONNER; H. SHIMAZAKI
        Society for Neuroscience 2016, 12 Nov. 2016
      • Large-scale inference of time-varying neural interactions
        Christian Donner; Hideaki Shimazaki
        ICONIP2016, 16 Oct. 2016
      • Modelling elemental learning of honeybees by spiking neural networks
        HaDi MaBouDi; Hideaki Shimazaki; Lars Chittka
        EURBEE 2016, 07 Sep. 2016
      • Analytical study of correlation and Fisher information caused by common inputs
        Safura Rashid Shomali; Majid Nili Ahmadabadi; Hideaki Shimazaki; S Nader Rasuli
        the 39th Annual Meeting of the Japan Neuroscience Society, 22 Jul. 2016
      • Exact spike-timing distribution and its usage in neural structure identification
        S. Rashid Shomali; M. Nili Ahmadabadi; H. Shimazaki; S.N. Rasuli
        Statistical physics methods in biology and computer science (Satellite meeting of StatPhys 2016, 13 Jul. 2016
      • Toward thermodynamic principles of consciousness
        HIDEAKI SHIMAZAKI
        Seminar, 07 Jul. 2016, Christopher L Buckley
      • Higher-order interactions of neural populations
        HIDEAKI SHIMAZAKI
        Seminar at TNJC, 05 Jul. 2016, Mehdi Keramati
      • Population coding of neurons: Dynamics, higher-order interactions, and mechanisms
        HIDEAKI SHIMAZAKI
        Seminar, 04 Jul. 2016, Lars Chittka
      • Exact spike-timing distribution reveals higher-order interactions
        Shomali SR; Ahmadabad MN; Shimazaki H; Rasuli SN
        CNS*2016, 02 Jul. 2016
      • Simultaneous silence explains structured higher-order interactions of neural population
        Hideaki Shimazaki
        MONA2 - Modelling Neural Activity, 22 Jun. 2016
      • Toward thermodynamic principles of consciousness
        Hideaki Shimazaki
        Consciousness club, 16 Jun. 2016, Ryota Kanai
      • 相関を伴う神経回路網の活動と情報コーディング
        島崎 秀昭
        ホンダ・リサーチ・インスティチュート, 23 Mar. 2016
      • 神経ネットワークの情報コーディング:ダイナミクス・高次相関・メカニズム
        島崎 秀昭
        第4回東工大若手物性セミナー, 18 Feb. 2016, Invited
      • Analysis of network activity of neurons by the dynamic Ising model
        Shimazaki H
        International Christian University NS Forum, 02 Feb. 2016, Invited
      • Approximation methods for inferring time-varying interactions of a large neural population
        Christian Donner; Hideaki Shimazaki
        NIPS 2015 Workshop on `Statistical Methods for Understanding Neural Systems', 11 Dec. 2015
      • 神経回路網の熱力学的考察
        島崎 秀昭
        28 Nov. 2015, 数理モデリング研究会
      • Simultaneous silence explains structured higher-order interactions of neural populations
        Shimazaki H
        Juelich Research Center, 04 May 2015, Invited
      • Simultaneous silence explains structured higher-order interactions of neural populations
        Shimazaki H
        BCCN Berlin, 28 Apr. 2015, Invited
      • Simultaneous silence explains structured higher-order interactions of neural populations
        HIDEAKI SHIMAZAKI
        第16回ノンパラメトリック統計解析とベイズ統計, 25 Mar. 2015
      • 神経細胞の集団活動の高次統計とメカニズム
        島崎 秀昭
        第3回ヘテロ・ニューロ・アナリシス研究会, 18 Mar. 2015
      • State-space analysis of behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement
        Thomas Sharp; Hideaki Shimazaki; Yoshikazu Isomura; Tomoki Fukai
        Society for Neuroscience 2014, 16 Nov. 2014
      • Theoretical study on spike-timing probability in a pair of pre-post synaptic neurons
        Safura Rashid Shomali; Majid Nili Ahmadabadi; Hideaki Shimazaki; S Nader Rasuli
        Neuro2014, 11 Sep. 2014
      • Behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement
        Thomas Sharp; Hideaki Shimazaki; Yoshikazu Isomura; Tomoki Fukai
        Neuro2014, 11 Sep. 2014
      • Behaviour- and layer-dependent synchrony in motor cortex during volitional arm movement
        Sharp T; Shimazaki H; Isomura Y; Fukai T
        Workshop on data mining in neuroscience, 28 May 2014
      • Bimodal distributions of local phase variables in natural images
        HaDi MaBouDi; Hideaki Shimazaki; Hamid Soltanian-Zadeh; Shun-ichi Amari
        The 2014 VSS Annual Meeting, 18 May 2014
      • State-space analysis of higher-order interactions in parallel event sequences
        Shimazaki H; Amari S; Brown EN; Grün S
        第15回ノンパラメトリック統計解析とベイズ統計, 20 Mar. 2014
      • 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
        島崎 秀昭
        神経科学と脳科学の対話4, 17 Mar. 2014, 統計数理研究所
      • Statistical inference for directed phase coupling in neural oscillators
        HaDi MaBouDi; Hideaki Shimazaki; Mehdi Abouzari; Shun-ichi Amari; Hamid Soltanian-Zadeh
        Computational and Systems Neuroscience (Cosyne) 2014, 27 Feb. 2014
      • Statistical inference for directed phase coupling in neural oscillators. Computational and Systems Neuroscience
        HaDi MaBouDi; Hideaki Shimazaki; Mehdi Abouzari; Shun-ichi Amari; Hamid Soltanian-Zadeh
        Cosyne 2014, Salt Lake City, USA., Feb. 2014
      • Structured higher-order interactions explain the simultaneous silence of neural populations
        Shimazaki H; Sadeghi K; Ikegaya Y; Toyoizumi T
        脳と心のメカニズム 第14回 冬のワークショップ, 08 Jan. 2014
      • The simultaneous silence of neurons explains structured higher-order interactions in ensemble spiking activity
        Shimazaki H; Sadeghi K; Ikegaya Y; Toyoizumi T
        Society for Neuroscience (SfN) 2013, 09 Nov. 2013
      • State-space analysis of time-varying higher-order interactions: its applications to neuroscience
        Shimazaki H
        ELC International Meeting on ''Inference, Computation, and Spin Glasses'' (ICSG2013), 28 Jul. 2013, Invited
      • Higher-order interactions in population activity of hippocampal CA3 neurons
        Shimazaki H
        Workshop on statistical analysis of neurophysiological and clinical data, 08 Jul. 2013, Kyoto University, Invited
      • Estimating time-varying higher-order neuronal interactions in awake behaving animals
        Shimazaki H; Amari S; Brown EN; Grün S
        Modeling Neural Activity: Statistics, Dynamical Systems, and Networks, 26 Jun. 2013
      • The simultaneous silence of neurons explains higher-order interactions in ensemble spiking activity
        Shimazaki H; Sadeghi K; Ikegaya Y; Toyoizumi T
        Neuro2013, 20 Jun. 2013
      • The simultaneous silence of neurons explains higher-order interactions in ensemble spiking activity
        Shimazaki H
        The 3rd Mathematical Neuroscience Workshop in School of Mathematics, 14 Mar. 2013, Institute for Research in Fundamental Sciences (IPM), Invited
      • Estimating dynamic neural interactions in awake behaving animals
        Shimazaki H
        The 3rd Mathematical Neuroscience Workshop in School of Mathematics, 13 Mar. 2013, Institute for Research in Fundamental Sciences (IPM), Invited
      • 高次相関を伴う神経回路網の活動と情報コーディング
        島崎 秀昭
        玉川大学脳科学若手の会 第88回談話会, 22 Feb. 2013, 玉川大学脳科学若手の会, Invited
      • The simultaneous silence of neurons explains structured higher-order interactions in spontaneous spiking activity
        Shimazaki H; Sadeghi K; Ikegaya Y; Toyoizumi T
        神経科学と統計科学の対話3, 18 Feb. 2013, 統計数理研究所
      • Joint inactivation statistics of population spiking activities
        HIDEAKI SHIMAZAKI
        Workshop on statistical aspects of neural coding, 01 Nov. 2012, Kyoto University & Ritsumeikan University, Invited
      • Tracking dynamic neural interactions in awake behaving animals
        Shimazaki H
        Workshop on neural information flow, 20 Jun. 2012, Kyoto University
      • 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
        島崎 秀昭; 篠本 滋
        第13回ノンパラメトリック統計解析とベイズ統計, 29 Mar. 2012
      • The simultaneous silence of neurons explains higher-order interactions in ensemble spiking activity
        Shimazaki H; Sadeghi K; Ikegaya Y; Toyoizumi T
        Computational and Systems Neuroscience (Cosyne) 2012, 23 Feb. 2012
      • 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
        島崎 秀昭
        京都大学理学部物理学第一教室 非線形セミナー, 02 Feb. 2012, 京都大学
      • 神経スパイク解析における状態空間モデル,GLMの応用
        島崎 秀昭; 小山 慎介
        統計科学と神経科学の対話2, 26 Dec. 2011, 統計数理研究所
      • 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
        島崎 秀昭
        統計神経科学ミニワークショップ, 08 Sep. 2011, 統計数理研究所
      • Constructing a joint time-series model of continuous and Bernoulli/Poisson processes using a copula
        Shimazaki H; Brown EN
        Computational and Systems Neuroscience (Cosyne) 2011, 24 Feb. 2011
      • Analysis of dynamic neural spike data: from firing rate to spike correlation
        Shimazaki H
        Neurostatistics Working Group Seminar, 01 Dec. 2010, Dept. of Biostatistics, Harvard University, Invited
      • Detection of dynamic cell assemblies by the Bayes factor
        Shimazaki H
        Workshop on spatio-temporal neuronal computation, 06 Sep. 2010, Kyoto University
      • Characterizing neuronal firing with the rate and the irregularity
        Shinomoto S; Shimazaki H; Shimokawa T
        Neuro 2010, 02 Sep. 2010
      • Analysis of subsets of higher-order correlated neurons based on marginal correlation coordinates
        Shimazaki H; Amari S; Brown EN; Grün S
        Computational and Systems Neuroscience (Cosyne) 2010, 25 Feb. 2010
      • 動的スパイク相関の状態空間モデル
        島崎秀昭; 甘利俊一; Emery Brown; Sonja Gruen
        日本神経回路学会 第19回全国大会, 24 Sep. 2009, 日本神経回路学会
      • Histogram binwidth and kernel bandwidth selection for the Spike-rate estimation
        Shimazaki H; Shinomoto S
        CNS2009, 18 Jul. 2009
      • Bayes factor analysis for detection of time-dependent higher-order spike correlations
        Shimazaki H; Amari S; Brown EN; Grün S
        CNS2009, 18 Jul. 2009
      • State-space model of dynamic correlations in parallel spike sequences
        島崎 秀昭
        京都大学理学研究科物理学第一教室 非線形動力学セミナー, 01 Jun. 2009, Invited
      • Estimating time-varying spike correlations from parallel spike sequences
        Shimazaki H; Amari S; Brown EN; Grün S
        German-Japanese Workshop "Computational and Systems Neuroscience", 25 May 2009
      • State-space Analysis on Time-varying Correlations in Parallel Spike Sequences
        Shimazaki H; Amari S; Brown EN; Grün S
        ICASSP2009 Special Session on `Signal Processing for Neural Spike Trains', 24 Apr. 2009, IEEE, Invited
      • Detection of non-stationary higher-order spike correlation
        Shimazaki H; Amari S; Brown EN; Grün S
        Computational and Systems Neuroscience (Cosyne) 2009, 26 Feb. 2009
      • State-space analysis on time-varying higher-order spike correlations
        Shimazaki H; Amari S; Brown EN; Grün S
        NIPS2008 Workshop on `Statistical Analysis and Modeling of Response Dependencies in Neural Populations', 13 Dec. 2008
      • 多細胞同時記録スパイク時系列データの状態空間モデル
        島崎 秀昭; ソーニャ グリューエン
        第11回情報論的学習理論ワークショップ, 29 Oct. 2008
      • 局所適応カーネル法によるスパイクレート推定
        島崎 秀昭; 篠本 滋
        日本神経回路学会 第18回全国大会, 24 Sep. 2008, 日本神経回路学会
      • Estimating time-dependent higher-order interactions in parallel spike trains
        Shimazaki H; Gruen S
        Neuro2008, 09 Jul. 2008
      • State-space Analysis on time-dependent correlation in parallel spike trains
        Shimazaki H; Amari S; Brown EN; Grün S
        Statistical Analysis of Neuronal Data (SAND4), 29 May 2008
      • Kernel width optimization in the spike-rate estimation
        Shimazaki H; Shinomoto S
        Neural Coding 2007, 07 Nov. 2007
      • Optimization of a histogram of spike data
        Shimazaki H; Shinomoto S
        Neuro2007, 11 Sep. 2007
      • ヒストグラムのビン幅の選択方法 -最適なPSTHの作り方
        島崎 秀昭
        マルチニューロン研究会, 30 Jun. 2007, Invited
      • A recipe for optimizing a time histogram of spike data
        Shimazaki H
        RIKEN BSI Forums, 17 Apr. 2007, RIKEN Brain Science Institute
      • A recipe for constructing a peri-stimulus time histogram
        Shimazaki H
        The Boadian Seminar at Mind/Brain Institute, 01 Mar. 2007, Johns Hopkins University
      • A recipe for optimizing a time-histogram with variable bin sizes
        Shimazaki H; Shinomoto S
        Computational and Systems Neuroscience (Cosyne) 2007, 22 Feb. 2007
      • A recipe for optimizing a time-histogram
        Shimazaki H; Shinomoto S
        Neural Information Processing Systems (NIPS) 2006, 04 Dec. 2006
      • スパイク時系列の潜時を補正して時間ヒストグラムを最適化する方法
        島崎 秀昭
        日本神経回路学会第16回全国大会, 21 Sep. 2006
      • Self-organized criticality by natural selection
        Shimazaki H
        Frontiers in Dynamics: Physical and Biological Systems., 22 May 2006
      • Recipes for constructing an optimal time histogram
        Shimazaki H
        Statistical Analysis of Neuronal Data (SAND3), 12 May 2006
      • スパイク時系列ヒストグラムのビン幅の選択方法 -最適なPSTHの作り方
        島崎 秀昭
        脳と心のメカニズム 第6回冬のワークショップ, Jan. 2006
      • 乗法的競争モデルに見られる相転移
        島崎 秀昭
        経済物理学 II -社会・経済への物理学的アプローチ-, 01 Dec. 2005
      • スパイク時系列のヒストグラム作成における最適区間幅決定のレシピ
        島崎秀昭; 篠本滋
        日本神経回路学会第15回全国大会, Sep. 2005
      • 離散力学系の競争モデルに見られる相転移と自然選択による転移点への接近
        島崎 秀昭
        日本物理学会第60回年次大会, Mar. 2005
      • Bose-einstein condensation in competitive processes
        Shimazaki H
        日本物理学会第59回年次大会, Mar. 2004
      • イベント時系列解析入門
        小山, 慎介; 島崎, 秀昭, Joint work
        近代科学社, May 2023
      • Active Inference Third International Workshop, IWAI 2022, Grenoble, France, September 19, 2022, Revised Selected Papers
        Christopher L. Buckley; Daniela Cialfi; Pablo Lanillos; Maxwell Ramstea; Noor Saji; Hideaki Shimazaki; Tim Verbelen, Editor
        Springer, 2023
      • Neural coding
        Hideaki Shimazaki, Contributor
        脳科学辞典編集委員会, 24 Aug. 2021, Refereed
      • Dynamic neuroscience : statistics, modeling, and control
        Chen, Zhe; Sarma Sridevi V.
        Springer, 2018
      • Principles of Neural Science, Fifth Edition
        金澤一郎; 宮下保司; Eric R. Kandel; James H. Schwartz; Steven A. Siegelbaum; Thomas M.Jessell; A. J. Hudspeth, Single translation, Appendix F, Theoretical Approaches to Neuroscience: Examples from SingleNeurons to Networks, Eric R. Kandel; James H. Schwartz; Steven A. Siegelbaum; Thomas M.Jessell; A. J. Hudspeth
        MEDICAL SCIENCES INTERNATIONAL, LTD, Apr. 2014, Not refereed

      Industrial Property Rights

      • 特許第7325755号, 特開2021-112503, 特願2020-007811, 情報処理装置、情報処理方法およびプログラム
        島崎 秀昭; 下西 慶; 仁科 繁明; ジュ ビンユエ

      Awards

      • 20 Oct. 2016
        Excellent paper award(Asia Pacific Neural Network Society,Japanese Neural Net)
      • 15 Nov. 2009
        大会研究賞(日本神経回路学会)
      • 26 Sep. 2007
        奨励賞(日本神経回路学会)

      External funds: Kakenhi

      • Theoretical approaches to adaptive neuronal circuits identified by the cell type census
        Grant-in-Aid for Transformative Research Areas (A)
        Transformative Research Areas, Section (III)
        Kyoto University;Hokkaido University
        島崎 秀昭
        From 10 Sep. 2021, To 31 Mar. 2026, Granted
        適応原理;状態空間モデル;神経活動ダイナミクス;学習則;理論モデル;神経スパイクデータ解析;回路推定;高次相関;ベイズ脳仮説;自由エネルギー原理
      • Cell type census of adaptive neuronal circuits: biological mechanisms of structural and functional organization
        Grant-in-Aid for Transformative Research Areas (A)
        Transformative Research Areas, Section (III)
        Tokyo Medical and Dental University
        礒村 宜和
        From 10 Sep. 2021, To 31 Mar. 2026, Granted
        神経回路;トランスクリプトーム;行動適応;オミックス;理論モデル
      • Development of statistical analysis methods for visualizing nonlinear activity of large-scale neural populations
        Grant-in-Aid for Scientific Research (C)
        Basic Section 60030:Statistical science-related
        Kyoto University;Hokkaido University
        島崎 秀昭
        From 01 Apr. 2020, To 31 Mar. 2024, Granted
        状態空間モデル;イジングモデル;神経スパイクデータ;キネティック・イジングモデル;非平衡系;情報幾何;平均場近似;神経符号化;非線形ダイナミクス
      list
        Last Updated :2024/02/21

        Education

        Teaching subject(s)

        • From 01 Apr. 2023, To 31 Mar. 2024
          Electrical and Electronic Engineering in Biomedical Applications
          6200, Spring, Faculty of Engineering, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Integrated Systems Biology
          3511, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Systems Science, Advanced I
          3542, Spring, Graduate School of Informatics, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Systems Science, Advanced II
          3512, Fall, Graduate School of Informatics, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Practice of Basic Informatics (Faculty of Engineering)
          T006, Fall, Institute for Liberal Arts and Sciences, 2
        • From 01 Apr. 2023, To 31 Mar. 2024
          Computational neuroscience
          3544, Year-long, Graduate School of Informatics, 1
        list
          Last Updated :2024/02/21

          Administration

          Faculty management (title, position)

          • From 01 Apr. 2023, To 31 Mar. 2024
            人を対象とする研究倫理小委員会委員
          list
            Last Updated :2024/02/21

            Academic, Social Contribution

            Committee Memberships

            • From Jan. 2023, To Present
              脳と心のメカニズム 第40回計画委員, 脳と心のメカニズム
            • From Sep. 2023, To Sep. 2024
              プログラム委員長, 日本神経回路学会第34回全国大会
            • From Jul. 2022, To Jan. 2023
              脳と心のメカニズム 第39回計画委員, 脳と心のメカニズム
            • From Oct. 2021, To Mar. 2024
              領域アドバイザー, 学術変革研究領域(B)「あいまい環境に対峙する脳・生命体の情報獲得戦略の解明」
            • From Jan. 2020, To Present
              Action Editor, Neural Networks
            • From Jul. 2022, To Aug. 2023
              コアプログラム委員, 日本神経科学会 第46回日本神経科学大会
            • From Jan. 2021, To Jul. 2022
              第45回日本神経科学大会プログラム委員, 日本神経科学会
            • From Apr. 2018, To Mar. 2020
              Board member, Japanese Neural Network Society
            • From Feb. 2014, To Mar. 2016
              専門調査員, 文部科学省科学技術政策研究所科学技術動向研究センター

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