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Laboratory for Neural Coding and Brain Computing

神経情報・脳計算研究チームへようこそ

 深井は2019年4月1日より沖縄科学技術大学院大学 OISTが本務となりました

ラボの目標

 認知、学習と記憶、意思決定などの高次脳機能は、脳の神経回路の働きによって実現されます。当研究室では脳の計算原理と、それを実現している神経回路メカニズムを明らかにするために、実験と理論の両面から研究を行なっています。

  回路メカニズムに拘るのは、計算原理を実装しているメカニスティックな仕組みに、脳の情報処理の優位性の秘密があると感じているためです。とくに脳の神経回路は、ノイズを積極的に利用して本質的に確率的なこの世界を“モデル化”し、その知識を利用して計算することで、知覚認知や意思決定などを効率的かつ柔軟に行なっていると考えられます。また計算に要する消費エネルギーが少ないという脳の情報処理の特徴も(たかだか数十ワット程度と言われています)、脳がコンピュータのように、信号とノイズが明確に分離された方法で計算を実行していない可能性を示唆します。

  そのような脳の計算の“確率過程”を解明し、脳型情報処理機械の創造を可能にするための理論的基盤を築くことが、当研究室の究極の目標です。

主な研究テーマ

  • 脳の確率的計算原理と回路メカニズム
  • 神経ダイナミクスと情報表現
  • 大脳皮質局所回路の機能に関する理論と実験(ラット)
  • 神経集団活動データからの情報抽出(機械学習等)

業績抜粋

  • Fung C C A and Fukai T (2019) Discrete-attractor-like tracking in continuous attractor neural networks. Phys Rev Lett, 122,018102
  • Kurikawa T, Haga T, Handa T, Harukuni R and Fukai T(2018) Neuronal stability in medial frontal cortex sets individual variability in decision-making. Nat Neurosci, 21:1764-1773, Published online 12 November
  • Hiratani N and Fukai T (2018) Redundancy in synaptic connections enables neurons to learn optimally. PNAS, 115(29): E6871-E6879
  • Haga T and Fukai T (2018) Recurrent network model for learning goal-directed sequences through reverse replay. Elife, 7:e34171
  • Hiratani N and Fukai T (2017) Detailed dendritic excitatory/inhibitory balance through heterosynaptic spike-timing-dependent plasticity. J Neurosci, 37 (50): 12106-12122
  • Omura Y, Carvalho M M, Inokuchi K and Fukai T (2015) A lognormal recurrent network model for burst generation during hippocampal sharp waves. J Neurosci, 35(43):14585-14601
  • Igarashi J, Isomura Y, Arai K, Harukuni R and Fukai T (2013) A θ-γ oscillation code for neuronal coordination during motor behavior. J Neurosci, 33(47):18515-18530
  • Teramae J, Tsubo Y, Fukai T (2012) Optimal spike-based communication in excitable networks with strong-sparse and weak-dense links, Scientific Reports 2, 485
  • Gilson M, Fukai T (2011) Stability versus Neuronal Specialization for STDP: Long-Tail Weight Distributions Solve the Dilemma, PLoS ONE 6(10), e25339.
  • Okamoto H, Fukai T. (2009) Recurrent network models for perfect temporal integration of fluctuating correlated inputs, PLoS Comput. Biol. 5(6) e1000404.
  • Sakai Y, Fukai T (2008) When does reward maximization lead to matching law? PLoS ONE 3(11), e3795.
  • Fukai T, Tanaka S (1997) A simple neural network exhibiting selective activation of neuronal ensembles: From winner-take-all to winners-share-all, Neural Computation 9, 77-97.
  • Shiino M, Fukai T (1993) Self-consistent signal-to-noise analysis of the statistical behavior of analog neural networks & enhancement of the storage capacity, Physical Review E48, 867-897.

関連記事

eLIFE_cover

News & Topics

2018/12/10 Publications
Chi Chung Alan Fung and Tomoki Fukai. Discrete-attractor-like tracking in continuous attractor neural networks. Phys Rev Lett

Anthony Joseph Decostanzo, Chi Chung Alan Fung and Tomoki Fukai. Hippocampal neurogenesis reduces the dimensionality of sparsely coded representations to enhance memory encoding. Front Comput Neurosci


2018/11/13 Publications
Tomoki Kurikawa, Tatsuya Haga, Takashi Handa, Rie Harukuni and Tomoki Fukai.Neuronal stability in medial frontal cortex sets individual variability in decision-making. Nat Neurosci
[News & Views] [報道発表資料]


2018/10/03 Publications
Toshitake Asabuki, Naoki Hiratani and Tomoki Fukai. Interactive reservoir computing for chunking information streams. PLoS Comput Biol

Tatsuya Haga T and Tomoki Fukai. Dendritic processing of spontaneous neuronal sequences for single-trial learning. Scientific Reports


2018/07/10 Publications
Tatsuya Haga and Tomoki Fukai. Recurrent network model for learning goal-directed sequences through reverse replay. eLIFE

Gonzalo Martín-Vázquez, Toshitake Asabuki, Yoshikazu Isomura and Tomoki Fukai. Learning Task-Related Activities From Independent Local-Field-Potential Components Across Motor Cortex Layers. Front. Neurosci

Chi Chung Alan Fung and Tomoki Fukai.Transient and Persistent UP States during Slow-wave Oscillation and their Implications for Cell-Assembly Dynamics.Sci Rep

Naoki Hiratani and Tomoki Fukai. Redundancy in synaptic connections enables neurons to learn optimally. PNAS


2017/10/17 Publications
Naoki Hiratani and Tomoki Fukai. Detailed dendritic excitatory/inhibitory balance through heterosynaptic spike-timing-dependent plasticity. The Journal of Neuroscience


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Lab. for Neural Coding and Brain Computing, RIKEN CBS
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