増田 直紀 (マスダ ナオキ)

写真a

所属

理工学術院 創造理工学部

職名

教授(任期付)

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  • 理工学術院   大学院創造理工学研究科

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  • 2020年
    -
    2022年

    理工学術院総合研究所   兼任研究員

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  •  
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    2002年

    東京大学   大学院 工学系研究科   計数工学専攻  

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    2002年

    東京大学  

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    1998年

    東京大学   工学部   計数工学  

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    1998年

    東京大学  

学位 【 表示 / 非表示

  • 東京大学   工学博士

経歴 【 表示 / 非表示

  • 2008年
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    2009年

    東京大学 情報理工学系研究科   講師

 

研究分野 【 表示 / 非表示

  • 制御、システム工学

  • 制御、システム工学

研究キーワード 【 表示 / 非表示

  • 包括脳ネットワーク

  • 統合脳・統合脳

論文 【 表示 / 非表示

  • Selective Population Rate Coding: A Possible Computational Role of Gamma Oscillations in Selective Attention

    Naoki Masuda

    NEURAL COMPUTATION   21 ( 12 ) 3335 - 3362  2009年12月  [査読有り]

     概要を見る

    Selective attention is often accompanied by gamma oscillations in local field potentials and spike field coherence in brain areas related to visual, motor, and cognitive information processing. Gamma oscillations are implicated to play an important role in, for example, visual tasks including object search, shape perception, and speed detection. However, the mechanism by which gamma oscillations enhance cognitive and behavioral performance of attentive subjects is still elusive. Using feedforward fan-in networks composed of spiking neurons, we examine a possible role for gamma oscillations in selective attention and population rate coding of external stimuli. We implement the concept proposed by Fries (2005) that under dynamic stimuli, neural populations effectively communicate with each other only when there is a good phase relationship among associated gamma oscillations. We show that the downstream neural population selects a specific dynamic stimulus received by an upstream population and represents it by population rate coding. The encoded stimulus is the one for which gamma rhythm in the corresponding upstream population is resonant with the downstream gamma rhythm. The proposed role for gamma oscillations in stimulus selection is to enable top-down control, a neural version of time division multiple access used in communication engineering.

    DOI PubMed

  • A Theoretical Analysis of Temporal Difference Learning in the Iterated Prisoner's Dilemma Game

    Naoki Masuda, Hisashi Ohtsuki

    BULLETIN OF MATHEMATICAL BIOLOGY   71 ( 8 ) 1818 - 1850  2009年11月  [査読有り]

     概要を見る

    Direct reciprocity is a chief mechanism of mutual cooperation in social dilemma. Agents cooperate if future interactions with the same opponents are highly likely. Direct reciprocity has been explored mostly by evolutionary game theory based on natural selection. Our daily experience tells, however, that real social agents including humans learn to cooperate based on experience. In this paper, we analyze a reinforcement learning model called temporal difference learning and study its performance in the iterated Prisoner's Dilemma game. Temporal difference learning is unique among a variety of learning models in that it inherently aims at increasing future payoffs, not immediate ones. It also has a neural basis. We analytically and numerically show that learners with only two internal states properly learn to cooperate with retaliatory players and to defect against unconditional cooperators and defectors. Four-state learners are more capable of achieving a high payoff against various opponents. Moreover, we numerically show that four-state learners can learn to establish mutual cooperation for sufficiently small learning rates.

    DOI PubMed

  • Analysis of relative influence of nodes in directed networks

    Naoki Masuda, Yoji Kawamura, Hiroshi Kori

    Physical Review E - Statistical, Nonlinear, and Soft Matter Physics   80 ( 4 ) 046114  2009年10月  [査読有り]

     概要を見る

    Many complex networks are described by directed links
    in such networks, a link represents, for example, the control of one node over the other node or unidirectional information flows. Some centrality measures are used to determine the relative importance of nodes specifically in directed networks. We analyze such a centrality measure called the influence. The influence represents the importance of nodes in various dynamics such as synchronization, evolutionary dynamics, random walk, and social dynamics. We analytically calculate the influence in various networks, including directed multipartite networks and a directed version of the Watts-Strogatz small-world network. The global properties of networks such as hierarchy and position of shortcuts rather than local properties of the nodes, such as the degree, are shown to be the chief determinants of the influence of nodes in many cases. The developed method is also applicable to the calculation of the PAGERANK. We also numerically show that in a coupled oscillator system, the threshold for entrainment by a pacemaker is low when the pacemaker is placed on influential nodes. For a type of random network, the analytically derived threshold is approximately equal to the inverse of the influence. We numerically show that this relationship also holds true in a random scale-free network and a neural network. © 2009 The American Physical Society.

    DOI

  • Directionality of contact networks suppresses selection pressure in evolutionary dynamics

    Naoki Masuda

    JOURNAL OF THEORETICAL BIOLOGY   258 ( 2 ) 323 - 334  2009年05月  [査読有り]

     概要を見る

    Individuals of different types, may it be genetic, Cultural, or else, with different levels of fitness often compete for reproduction and Survival. A fitter type generally has higher chances of disseminating their copies to other individuals. The fixation Probability of a single mutant type introduced in a population of wild-type individuals quantifies how likely the Mutant type spreads. How much the excess fitness of the mutant type increases its fixation probability, namely, the selection pressure, is important in assessing the impact of the introduced mutant. Previous studies mostly based Oil undirected and unweighted contact networks of individuals showed that the selection pressure depends on the Structure of networks and the rule Of reproduction. Real networks underlying ecological and social interactions are usually directed or weighted. Here we examine how the selection pressure is modulated by directionality of interactions Under several update rules. Our conclusions are twofold. First, directionality, discounts the selection pressure for different networks and update rules. Second, given a network, the update rules in which death events precede reproduction events significantly decrease the selection pressure than the other rules. (C) 2008 Elsevier Ltd. All rights reserved.

    DOI PubMed

  • Self-organization of feed-forward structure and entrainment in excitatory neural networks with spike-timing-dependent plasticity

    Yuko K. Takahashi, Hiroshi Kori, Naoki Masuda

    PHYSICAL REVIEW E   79 ( 5 ) 051904  2009年05月  [査読有り]

     概要を見る

    Spike-timing dependent plasticity (STDP) is an organizing principle of biological neural networks. While synchronous firing of neurons is considered to be an important functional block in the brain, how STDP shapes neural networks possibly toward synchrony is not entirely clear. We examine relations between STDP and synchronous firing in spontaneously firing neural populations. Using coupled heterogeneous phase oscillators placed on initial networks, we show numerically that STDP prunes some synapses and promotes formation of a feedforward network. Eventually a pacemaker, which is the neuron with the fastest inherent frequency in our numerical simulations, emerges at the root of the feedforward network. In each oscillatory cycle, a packet of neural activity is propagated from the pacemaker to downstream neurons along layers of the feedforward network. This event occurs above a clear-cut threshold value of the initial synaptic weight. Below the threshold, neurons are self-organized into separate clusters each of which is a feedforward network.

    DOI CiNii

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  • 複雑ネットワークの階層構造がウェブページのページランクに与える影響(無線分散ネットワーク,一般)

    増田直紀, 河村洋史, 郡宏

    電子情報通信学会技術研究報告. SR, ソフトウェア無線   109 ( 246 ) 103 - 104  2009年10月

     概要を見る

    世の中の複雑ネットワークの多くは、枝に方向をもつ有向グラフである。有向グラフに特化した中心性指標の代表例は、グーグルの検索エンジンの基幹をなすページランクというアルゴリズムである。本発表では、ネットワークが巨大であるなどの理由で各頂点のページランクが正確には求められないという状況のもとで、ページランクを近似する手法を紹介する。近似手法を開発するために、線形代数の行列=木定理を用いる。結果の実データへの応用例についても講演で触れる。

    CiNii

  • 複雑ネットワークの階層構造がウェブページのページランクに与える影響(無線分散ネットワーク,一般)

    増田直紀, 河村洋史, 郡宏

    電子情報通信学会技術研究報告. USN, ユビキタス・センサネットワーク   109 ( 248 ) 77 - 78  2009年10月

     概要を見る

    世の中の複雑ネットワークの多くは、枝に方向をもつ有向グラフである。有向グラフに特化した中心性指標の代表例は、グーグルの検索エンジンの基幹をなすページランクというアルゴリズムである。本発表では、ネットワークが巨大であるなどの理由で各頂点のページランクが正確には求められないという状況のもとで、ページランクを近似する手法を紹介する。近似手法を開発するために、線形代数の行列=木定理を用いる。結果の実データへの応用例についても講演で触れる。

    CiNii

  • 複雑ネットワークで社会を変える(III 研究者に聞く(2),<特集>非線形・複雑系の科学とこれからの建築・都市)

    増田直紀, 倉方俊輔

    建築雑誌   124 ( 1590 ) 12 - 13  2009年05月

    CiNii

  • 複雑ネットワークの研究動向について(<特集>複雑ネットワークの世界-ネットワーク研究の新展開-)

    増田直紀

    オペレーションズ・リサーチ : 経営の科学   53 ( 9 ) 511 - 516  2008年09月

     概要を見る

    現実世界に見られるグラフは複雑である.複雑でありながらも,スモールワールド,スケールフリーなどといった特徴が同定されている.そのような複雑ネットワークの研究は1998年ごろから始まった.10年が経過した現在,多くの研究者の参画によって,様々な方向へ研究が発展している.本稿では,複雑ネットワークの代表的なモデルを概観した後に,ネットワーク上の現象論やその応用可能性を述べる.

    CiNii

  • ネットワーク上の進化ゲーム(<特集>繋がりの科学)

    増田直紀

    人工知能学会誌   23 ( 5 ) 652 - 658  2008年09月

    CiNii

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