2022/01/24 更新

写真a

マスダ ナオキ
増田 直紀
所属
理工学術院 創造理工学部
職名
教授(任期付)

兼担

  • 理工学術院   大学院創造理工学研究科

学内研究所等

  • 2020年
    -
    2022年

    理工学術院総合研究所   兼任研究員

学歴

  •  
    -
    2002年

    東京大学   大学院 工学系研究科   計数工学専攻  

  •  
    -
    2002年

    東京大学  

  •  
    -
    1998年

    東京大学   工学部   計数工学  

  •  
    -
    1998年

    東京大学  

学位

  • 東京大学   工学博士

経歴

  • 2008年
    -
    2009年

    東京大学 情報理工学系研究科   講師

 

研究分野

  • 制御、システム工学

  • 制御、システム工学

研究キーワード

  • 包括脳ネットワーク

  • 統合脳・統合脳

論文

  • 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

  • Controlling nosocomial infection based on structure of hospital social networks

    Taro Ueno, Naoki Masuda

    JOURNAL OF THEORETICAL BIOLOGY   254 ( 3 ) 655 - 666  2008年10月  [査読有り]

     概要を見る

    Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies. (c) 2008 Elsevier Ltd. All rights reserved.

    DOI PubMed

  • On global and local critical points of extended contact process on homogeneous trees

    Nobuaki Sugimine, Naoki Masuda, Norio Konno, Kazuyuki Aihara

    MATHEMATICAL BIOSCIENCES   213 ( 1 ) 13 - 17  2008年05月  [査読有り]

     概要を見る

    We study spatial stochastic epidemic models called households models. The households models have more than two states at each vertex of a graph in contrast to the contact process, We show that, in the households models on trees, two thresholds of infection rates characterize epidemics. The global critical infection rate is defined by epidemic occurrence. However, some households may be eventually disease-free even for infection rates above the global critical infection rate, in as far as they are smaller than the local critical point. Whether the global one is smaller than the local one depends on the graph and the model. We show that, in the households models, the global one is smaller than the local one on homogeneous trees. (C) 2008 Elsevier Inc. All rights reserved.

    DOI PubMed

  • A computational study of synaptic mechanisms of partial memory transfer in cerebellar vestibulo-ocular-reflex learning

    Naoki Masuda, Shun-ichi Amari

    JOURNAL OF COMPUTATIONAL NEUROSCIENCE   24 ( 2 ) 137 - 156  2008年04月  [査読有り]

     概要を見る

    There is a debate regarding whether motor memory is stored in the cerebellar cortex, or the cerebellar nuclei, or both. Memory may be acquired in the cortex and then be transferred to the cerebellar nuclei. Based on a dynamical system modeling with a minimal set of variables, we theoretically investigated possible mechanisms of memory transfer and consolidation in the context of vestibulo-ocular reflex learning. We tested different plasticity rules for synapses in the cerebellar nuclei and took robustness of behavior against parameter variation as the criterion of plausibility of a model variant. In the most plausible scenarios, mossy-fiber nucleus-neuron synapses or Purkinje-cell nucleus-neuron synapses are plastic on a slow time scale and store permanent memory, whose content is passed from the cerebellar cortex storing transient memory. In these scenarios, synaptic strengths are potentiated when the mossy-fiber afferents to the nuclei are active during a pause in Purkinje-cell activities. Furthermore, assuming that mossy fibers create a limited variety of signals compared to parallel fibers, our model shows partial memory transfer from the cortex to the nuclei.

    DOI PubMed

  • Oscillatory dynamics in evolutionary games are suppressed by heterogeneous adaptation rates of players

    Naoki Masuda

    JOURNAL OF THEORETICAL BIOLOGY   251 ( 1 ) 181 - 189  2008年03月  [査読有り]

     概要を見る

    Game dynamics in which three or more strategies are cyclically competitive, as represented by the rock-scissors-paper game, have attracted practical and theoretical interests. In evolutionary dynamics, cyclic competition results in oscillatory dynamics of densities of individual strategists. In finite-size populations, it is known that oscillations blow up until all but one strategies are eradicated if without mutation. In the present paper, we formalize replicator dynamics with players who have different adaptation rates. We show analytically and numerically that the heterogeneous adaptation rate suppresses the oscillation amplitude. In social dilemma games with cyclically competing strategies and homogeneous adaptation rates, altruistic strategies are often relatively weak and cannot survive in finite-size populations. In such situations, heterogeneous adaptation rates save coexistence of different strategies and hence promote altruism. When one strategy dominates the others without cyclic competition, fast adaptors earn more than slow adaptors. When not, mixture of fast and slow adaptors stabilizes population dynamics, and slow adaptation does not imply inefficiency for a player. (c) 2007 Elsevier Ltd. All rights reserved.

    DOI PubMed

  • Gamma oscillations of spiking neural populations enhance signal discrimination

    Naoki Masuda, Brent Doiron

    PLOS COMPUTATIONAL BIOLOGY   3 ( 11 ) 2348 - 2355  2007年11月  [査読有り]

     概要を見る

    Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive.

    DOI PubMed

  • Participation costs dismiss the advantage of heterogeneous networks in evolution of cooperation

    Naoki Masuda

    PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES   274 ( 1620 ) 1815 - 1821  2007年08月  [査読有り]

     概要を見る

    Real social interactions occur on networks in which each individual is connected to some, but not all, of others. In social dilemma games with a fixed population size, heterogeneity in the number of contacts per player is known to promote evolution of cooperation. Under a common assumption of positively biased pay-off structure, well-connected players earn much by playing frequently, and cooperation once adopted by well-connected players is unbeatable and spreads to others. However, maintaining a social contact can be costly, which would prevent local pay-offs from being positively biased. In replicator-type evolutionary dynamics, it is shown that even a relatively small participation cost extinguishes the merit of heterogeneous networks in terms of cooperation. In this situation, more connected players earn less so that they are no longer spreaders of cooperation. Instead, those with fewer contacts win and guide the evolution. The participation cost, or the baseline pay-off, is irrelevant in homogeneous populations, but is essential for evolutionary games on heterogeneous networks.

    DOI PubMed

  • Filtering of spatial bias and noise inputs by spatially structured neural networks

    Naoki Masuda, Masato Okada, Kazuyuki Aihara

    NEURAL COMPUTATION   19 ( 7 ) 1854 - 1870  2007年07月  [査読有り]

     概要を見る

    With spatially organized neural networks, we examined how bias and noise inputs with spatial structure result in different network states such as bumps, localized oscillations, global oscillations, and localized synchronous firing that may be relevant to, for example, orientation selectivity. To this end, we used networks of McCulloch-Pitts neurons, which allow theoretical predictions, and verified the obtained results with numerical simulations. Spatial inputs, no matter whether they are bias inputs or shared noise inputs, affect only firing activities with resonant spatial frequency. The component of noise that is independent for different neurons increases the linearity of the neural system and gives rise to less spatial mode mixing and less bistability of population activities.

    DOI PubMed

  • Dual coding hypotheses for neural information representation

    Naoki Masuda, Kazuyuki Aihara

    Mathematical Biosciences   207 ( 2 ) 312 - 321  2007年06月  [査読有り]

     概要を見る

    Information is represented and processed in neural systems in various ways. The rate coding, population coding, and temporal coding are typical examples of representation. It is a hot issue in neuroscience what kinds of coding is used in real neural systems. Different regions of the brain may resort to different coding strategies. Moreover, recent studies suggest the possibility of dual or multiple codes, in which different modes of information are embedded in one neural system. The present paper reviews various possibilities of neural codes focusing on dual codes. © 2006 Elsevier Inc. All rights reserved.

    DOI PubMed

  • Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity

    Naoki Masuda, Hiroshi Kori

    JOURNAL OF COMPUTATIONAL NEUROSCIENCE   22 ( 3 ) 327 - 345  2007年06月  [査読有り]

     概要を見る

    Spike-timing-dependent plasticity (STDP) with asymmetric learning windows is commonly found in the brain and useful for a variety of spike-based computations such as input filtering and associative memory. A natural consequence of STDP is establishment of causality in the sense that a neuron learns to fire with a lag after specific presynaptic neurons have fired. The effect of STDP on synchrony is elusive because spike synchrony implies unitary spike events of different neurons rather than a causal delayed relationship between neurons. We explore how synchrony can be facilitated by STDP in oscillator networks with a pacemaker. We show that STDP with asymmetric learning windows leads to self-organization of feedforward networks starting from the pacemaker. As a result, STDP drastically facilitates frequency synchrony. Even though differences in spike times are lessened as a result of synaptic plasticity, the finite time lag remains so that perfect spike synchrony is not realized. In contrast to traditional mechanisms of large-scale synchrony based on mutual interaction of coupled neurons, the route to synchrony discovered here is enslavement of downstream neurons by upstream ones. Facilitation of such feedforward synchrony does not occur for STDP with symmetric learning windows.

    DOI PubMed CiNii

  • Tag-based indirect reciprocity by incomplete social information

    Naoki Masuda, Hisashi Ohtsuki

    PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES   274 ( 1610 ) 689 - 695  2007年03月  [査読有り]

     概要を見る

    Evolution of altruistic behaviour in interacting individuals is accounted for by, for example, kin selection, direct reciprocity, spatially limited interaction and indirect reciprocity. Real social agents, particularly humans, often take actions based on similarity between themselves and others. Although tag-based indirect reciprocity in which altruism occurs exclusively among similar flocks is a natural expectation, its mechanism has not really been established. We propose a model of tag-based indirect reciprocity by assuming that each player may note strategies of others. We show that tag-based altruism can evolve to eradicate other strategies, including unconditional defectors for various initial strategy configurations and parameter sets. A prerequisite for altruism is that the strategy is sometimes, but not always, visible to others. Without visibility of strategies, policing does not take place and defection is optimal. With perfect visibility, what a player does is always witnessed by others and cooperation is optimal. In the intermediate regime, discriminators based on tag proximity, rather than mixture of generous players and defectors, are most likely to evolve. In this situation, altruism is realized based on homophily in which players are exclusively good to similar others.

    DOI PubMed

  • Dynamic switching of neural codes in networks with gap junctions

    Yuichi Katori, Naoki Masuda, Kazuyuki Aihara

    Neural Networks   19 ( 10 ) 1463 - 1466  2006年12月  [査読有り]

     概要を見る

    Population rate coding and temporal coding are common neural codes. Recent studies suggest that these two codes may be alternatively used in one neural system. Based on the fact that there are massive gap junctions in the brain, we explore how this switching behavior may be related to neural codes in networks of neurons connected by gap junctions. First, we show that under time-varying inputs, such neural networks show switching between synchronous and asynchronous states. Then, we quantify network dynamics by three mutual information measures to show that population rate coding carries more information in asynchronous states and temporal coding does so in synchronous states. © 2006 Elsevier Ltd. All rights reserved.

    DOI PubMed CiNii

  • Self-organizing dual coding based on spike-time-dependent plasticity

    N Masuda, K Aihara

    NEURAL COMPUTATION   16 ( 3 ) 627 - 663  2004年03月  [査読有り]

     概要を見る

    It has been a matter of debate how firing rates or spatiotemporal spike patterns carry information in the brain. Recent experimental and theoretical work in part showed that these codes, especially a population rate code and a synchronous code, can be dually used in a single architecture. However, we are not yet able to relate the role of firing rates and synchrony to the spatiotemporal structure of inputs and the architecture of neural networks. In this article, we examine how feedforward neural networks encode multiple input sources in the firing patterns. We apply spike-time-dependent plasticity as a fundamental mechanism to yield synaptic competition and the associated input filtering. We use the Fokker-Planck formalism to analyze the mechanism for synaptic competition in the case of multiple inputs, which underlies the formation of functional clusters in downstream layers in a self-organizing manner. Depending on the types of feedback coupling and shared connectivity, clusters are independently engaged in population rate coding or synchronous coding, or they interact to serve as input filters. Classes of dual codings and functional roles of spike-time-dependent plasticity are also discussed.

    DOI PubMed CiNii

  • Ergodicity of spike trains: When does trial averaging make sense?

    N Masuda, K Aihara

    NEURAL COMPUTATION   15 ( 6 ) 1341 - 1372  2003年06月  [査読有り]

     概要を見る

    Neuronal information processing is often studied on the basis of spiking patterns. The relevant statistics such as firing rates calculated with the peri-stimulus time histogram are obtained by averaging spiking patterns over many experimental runs. However, animals should respond to one experimental stimulation in real situations, and what is available to the brain is not the trial statistics but the population statistics. Consequently, physiological ergodicity, namely, the consistency between trial averaging and population averaging, is implicitly assumed in the data analyses, although it does not trivially hold true. In this letter, we investigate how characteristics of noisy neural network models, such as single neuron properties, external stimuli, and synaptic inputs, affect the statistics of firing patterns. In particular, we show that how high membrane potential sensitivity to input fluctuations, inability of neurons to remember past inputs, external stimuli with large variability and temporally separated peaks, and relatively few contributions of synaptic inputs result in spike trains that are reproducible over many trials. The reproducibility of spike trains and synchronous firing are contrasted and related to the ergodicity issue. Several numerical calculations with neural network examples are carried out to support the theoretical results.

    DOI PubMed CiNii

  • Duality of rate coding and temporal coding in multilayered feedforward networks

    Naoki Masuda, Kazuyuki Aihara

    Neural Computation   15 ( 1 ) 103 - 125  2003年01月  [査読有り]

     概要を見る

    A functional role for precise spike timing has been proposed as an alternative hypothesis to rate coding. We show in this article that both the synchronous firing code and the population rate code can be used dually in a common framework of a single neural network model. Furthermore, these two coding mechanisms are bridged continuously by several modulatable model parameters, including shared connectivity, feedback strength, membrane leak rate, and neuron heterogeneity. The rates of change of these parameters are closely related to the response time and the timescale of learning.

    DOI PubMed CiNii

  • Spatiotemporal spike encoding of a continuous external signal

    N Masuda, K Aihara

    NEURAL COMPUTATION   14 ( 7 ) 1599 - 1628  2002年07月  [査読有り]

     概要を見る

    Interspike intervals of spikes emitted from an integrator neuron model of sensory neurons can encode input information represented as a continuous signal from a deterministic system. If a real brain uses spike timing as a means of information processing, other neurons receiving spatiotemporal spikes from such sensory neurons must also be capable of treating information included in deterministic interspike intervals. In this article, we examine functions of neurons modeling cortical neurons receiving spatiotemporal spikes from many sensory neurons. We show that such neuron models can encode stimulus information passed from the sensory model neurons in the form of interspike intervals. Each sensory neuron connected to the cortical neuron contributes equally to the information collection by the cortical neuron. Although the incident spike train to the cortical neuron is a superimposition of spike trains from many sensory neurons, it need not be decomposed into spike trains according to the input neurons. These results are also preserved for generalizations of sensory neurons such as a small amount of leak, noise, inhomogeneity in firing rates, or biases introduced in the phase distributions.

    DOI PubMed CiNii

  • Bridging rate coding and temporal spike coding by effect of noise.

    Masuda N, Aihara K

    Physical review letters   88   248101  2002年06月  [査読有り]

    PubMed

▼全件表示

Misc

  • 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

  • ネットワーク上の3すくみダイナミクスと振動現象(非線形振動子系の物理学 : 現代的問題とその解析,基礎物理学研究所研究会YITP-W07-02)

    増田直紀

    物性研究   89 ( 5 ) 666 - 667  2008年02月

    CiNii

  • 結合振動子における集団引き込みと複雑ネットワーク

    郡宏, 増田直紀

    日本ロボット学会誌 = Journal of Robotics Society of Japan   26 ( 1 ) 6 - 9  2007年12月

    DOI CiNii

  • 複雑ネットワーク : 導入およびシナプス可塑性との関係

    増田直紀, 郡宏

    日本神経回路学会誌 = The Brain & neural networks   14 ( 3 ) 173 - 185  2007年09月

     概要を見る

    In this paper, we first explain basic concepts of complex networks, which have attracted broad interests in the last decade. Then, we introduce a recent study on the relation between spike-timing-dependent plasticity and the emergent structure of neural networks. Synaptic plasticity facilitates formation of feedforward structure in neural networks with pacemakers, and it lessens the threshold for frequency synchrony in comparison to the case of networks with quenched synapses.

    DOI CiNii

  • 複雑ネットワーク概説 : 生態学への応用を見据えて

    増田直紀, 中丸麻由子

    日本生態学会誌   56 ( 3 ) 219 - 229  2006年12月

     概要を見る

    複雑ネットワークは、要素と要素のつながり方の構造と機能に焦点をあてた新しい研究分野である。生態学の多くの対象においても、地理的空間、あるいは抽象的空間で個体や個体群同士がどのようなつながり方にのっとって相互作用するかは、全体や個々のふるまいに大きく影響しうる。本稿では、複雑ネットワークについて概説し、次に食物綱や伝播過程の例を紹介しながら、生態学へのネットワークの応用可能性を議論する。

    DOI CiNii

  • 構造と機能から見た複雑ネットワーク

    増田直紀, 巳波弘佳, 今野紀雄

    応用数理   16 ( 1 ) 2 - 16  2006年03月

     概要を見る

    Recently, complex networks have drawn increasing interests. It is often convenient to regard this research area to be composed of studies of network structure and network functions. Studies of network structure are concerned about topological characteristics of complex networks such as the small-world and scale-free properties. Studies of network functions deal with processes and phenomena on complex networks such as virus propagation. This article is a minireview of complex networks from these dual viewpoints.

    CiNii

  • 共同研究 25 熱帯病の数学モデルの構築と予防制圧への応用

    嶋田雅暁, 西浦博, 稲葉寿, 竹内昌平, 大日康史, 中澤港, 増田直紀, 加茂将史

    長崎大学熱帯医学研究所共同研究報告集   16   73 - 77  2004年

     概要を見る

    熱帯感染症の効果的な抑制政策には数理疫学(感染症数理モデル)に基づく研究手法による理論的理解が欠かせない。流行に関わる諸要因の影響探索や抑止対策の評価,サーベイランス等のフィールド疫学で用いられる手法の諸評価,そして将来予測に至るまで,数理生態学や数理統計学を中心とした数理的諸研究の貢献度は非常に高い。本共同研究は昨年度の共同研究(15-A-25)を継続して実施され,2004年2月の研究集会「熱帯疫学における観察データと複数数理モデルの対峙(15-B-4:研究代表:門司和彦)」を発展して研究集会が開催された。共同研究集会は科学的分野を区別しない学際的研究に関して,国際的レベルの先端的研究を牽引する研究者による基礎的理解の浸透と実際の社会貢献度の高い研究内容に関する活発な議論を目的として行われた。ロンドン大学インペリアルカレッジ感染症疫学の西浦博氏(現チュービンゲン大学医学部研究員・熱研非常勤講師)および中澤港氏(群馬大学大学院生態情報学助教授・熱研非常勤講師)らの尽力により,多くの感染症数理モデル研究者が研究内容を発表・議論し,共同研究を実施することができた。

    CiNii

  • カオス入力で駆動されるニューラルネットワークに現れる発火率コードと同期コードの二重性

    増田直紀, 合原一幸

    電子情報通信学会技術研究報告. NC, ニューロコンピューティング   102 ( 508 ) 59 - 64  2002年12月

     概要を見る

    脳がテンポラルコーディングと発火率コーディングのどちらを主に用いているかについて長年の論争がある。本報告では、チェンのカオス入力を受け取る2層の確率的ニューラルネットワークを解析する。ノイズの小さいときはニューロンは同期発火し、同期発火間隔が頑健に信号をコーディングする。ノイズが中程度のときは、ニューロンは非同期発火し、時間解像度の観点からは精度の高いコーディングが行われる。このノイズの役割は確率共振、coherence resonance,カオスのそれとは異なる。コーディングの二重性は、他のパラメータを変化させたときにも現れる。動物は、実際には状況に応じて適切な方を選択的に用いていると考えられる。

    CiNii

  • ラボラトリーズ 海外 University of California, San Diego

    増田直紀

    応用数理   12 ( 1 ) 78 - 80  2002年03月

    CiNii

  • Cryptosysfems with discretized chaotic maps

    IEEE Transactions on Circuits and Systems Part I   49(1), 28-40  2002年

    DOI

  • Cryptosysfems with discretized chaotic maps

    IEEE Transactions on Circuits and Systems Part I   49(1), 28-40  2002年

    DOI

  • 脳内情報表現の数理

    数理科学   12月号 43-48  2002年

  • Dynamical Characteristics of discretized chaotic permufations

    Infernational Journal of Bifurcation and chaos   12(10), 2087-2103  2002年

     概要を見る

    2002

    DOI

  • Dynamical Characteristics of discretized chaotic permufations

    Infernational Journal of Bifurcation and chaos   12(10), 2087-2103  2002年

     概要を見る

    2002

    DOI

  • Small-worldパルス結合ニューラルネットワークにおける同期現象

    増田直紀, 合原一幸

    電子情報通信学会技術研究報告. NC, ニューロコンピューティング   101 ( 365 ) 19 - 24  2001年10月

     概要を見る

    ニューロンの同期は生物の情報処理において重要な役割を果たす。そこで、様々な神経回路網モデルにおいて同期条件が理論的・数値的に研究されてきた。ところで、ほとんどの解析では、全結合か局所的結合といった単純なトポロジーが仮定されてきたが、実際の神経回路網ではsmall-worldネットワークなどの高次構造の存在も示されている。本研究ではパルスで結合されたleaky integrate-and-fireニューロンの同期現象を様々なトポロジーのもとで考察し、small-worldネットワークがランダムネットワークやローカルネットワークに比べて同期を導きやすいことを示す。

    CiNii

  • Time Series Analysis with Wavelet Coefficients

    Japan Journal of Industrial and Applied Mathematics   18   129 - 158  2001年

  • Cryptosystems based on space-discretization of chaotic maps

    Naoki Masuda, Kazuyuki Aihara

    ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings   3   321 - 324  2001年

     概要を見る

    Many kinds of chaotic cryptosystems have been proposed so far. However, most of them do not have enough security. In the present paper, a new kind of chaotic cryptosystem is proposed. The cryptosystem is based on a discretization of the skew tent map. The security is also investigated based on dynamical characteristics. Dynamical system theory is helpful for designing chaotic cryptosystems. © 2001 IEEE.

    DOI

  • 状態離散化カオス写像のエルゴード性、カオス性、及びフラクタル構造

    増田直紀, 合原幸一

    電子情報通信学会技術研究報告. CAS, 回路とシステム   100 ( 202 ) 39 - 46  2000年07月

     概要を見る

    カオス力系の応用や丸め誤差を伴う計算機実験の解釈のために、状態離散化力学系の理解が重要である。本報告では、状態離散化写像の不変測度の漸近的振る舞いを考察する。離散化写像の不変測度は自明には収束しないが、実用的な観測精度に落として測度を解釈すれば連続写像のそれに収束することが示される。その結果、離散化写像は元の写像のエルゴード性やカオス性を反映する長周期軌道を典型的に持つことが示される。また、離散化写像の不変測度が持つフラクタル構造について考察する。

    CiNii

  • 状態離散化カオス写像のエルゴード性、カオス性、及びフラクタル構造

    増田直紀, 合原一幸

    電子情報通信学会技術研究報告. NLP, 非線形問題   100 ( 204 ) 39 - 46  2000年07月

     概要を見る

    カオス力学系の応用や丸め誤差を伴う計算機実験の解釈のために、状態離散化力学系の理解が重要である。本報告では、状態離散化写像の不変測度の漸近的振る舞いを考察する。離散化写像の不変測度は自明には収束しないが、実用的な観測精度に落として測度を解釈すれば連続写像のそれに収束することが示される。その結果、離散化写像は元の写像のエルゴード性やカオス性を反映する長周期軌道を典型的に持つことが示される。また、離散化写像の不変測度が持つフラクタル構造について考察する。

    CiNii

  • 状態離散化カオス写像の力学系特性

    増田直紀, 合原一幸

    電子情報通信学会技術研究報告. NLP, 非線形問題   100 ( 33 ) 27 - 34  2000年05月

     概要を見る

    計算機によって、カオス写像の様々な力学的特性を明らかになった。しかし、丸め誤差の影響はあまり考慮されてこなかった。また、状態離散化カオス写像から作られるカオス暗号系では、連続近似を用いて安全性を解析するので、離散化の影響を評価しなければならない。そこで、本報告では、サイクルの統計量やBowenの理論などを用いて状態離散化カオス写像の力学的特性を評価する。その結果、離散化写像は元の写像のカオス性を反映するような長周期軌道を典型的に持つことが示される。

    CiNii

  • Cryptological systems using discretization of chaotic maps

    Computer Today     14 - 20  2000年

  • 離散化カオス写像を用いた暗号システム

    サイエンス社     14 - 20  2000年

  • 状態離散化カオス写像を用いた暗号システム

    臨時別冊・数理科学『現代暗号とマジックプロトコル』サイエンス社     65 - 75  2000年

  • ウェーブレット係数列を用いたカオス時系列の予測

    増田直紀, 合原一幸

    電子情報通信学会論文誌. A, 基礎・境界   82 ( 11 ) 1710 - 1718  1999年11月

     概要を見る

    時系列をウェーブレット展開すると,時系列は時間域で局在した周波数成分の和の形に表される.本論文では,ウェーブレット展開で得られた各周波数成分はもとの力学系の位相構造を保存することを示し,各周波数成分の時系列を個別に予測し,ウェーブレット逆変換によってもとの時系列の予測値を得る方法を提案する.提案される予測手法は,高周波の決定論的ノイズや確率的ホワイトノイズが観測的ノイズとして加法的に乗った決定論的な低周波カオス時系列信号の長期予測に有効であることが示される.

    CiNii

  • 有限状態パイコネ変換を用いたカオス暗号

    増田直紀, 合原一幸

    電子情報通信学会論文誌. A, 基礎・境界   82 ( 7 ) 1038 - 1046  1999年07月

     概要を見る

    カオスの初期値鋭敏依存性を用いた暗号方式は既に提案されている. しかし, 平文を直接力オス写像で変換したカオス暗号は区分線形性をもち, 暗号化に縮小的な関数を用いるので容易に解読される. 本論文では, まず, 上の型の既存のカオス暗号の仕組みを述べる. 更に, その暗号の解読方式の構成を通じて区分線形性をもつカオス暗号の本質的な弱さに言及するとともに, それを克服する新しいカオス暗号方式を提案する.

    CiNii

  • 疎な結合行列を持つ連想記憶のダイナミクスの解析

    増田直紀, 合原一幸

    電子情報通信学会技術研究報告. NLP, 非線形問題   99 ( 204 ) 77 - 84  1999年07月

     概要を見る

    連想記憶は, 理論的解析, モデルの拡張, 結合が疎な場合の解析, パターン認識などへの応用など広く研究されている。疎な結合行列をもつ連想記憶は全結合の連想記憶よりも生物学的に妥当であり, 実装コストの削減にもつながる。本報告では, 疎な結合行列をもつ連想記憶のダイナミクスを理論的に解析する。幾何学的解析, 統計学的解析によって, 結合が疎になるほど記憶ベクトルが不安定になることと, 記憶ベクトルの引き込み領域が小さくなることが示される。

    CiNii

  • 疎な結合行列を持つ連想記憶のダイナミクスの解析

    増田直紀, 合原一幸

    電子情報通信学会技術研究報告. CST, コンカレント工学   99 ( 206 ) 77 - 84  1999年07月

     概要を見る

    連想記憶は, 理論的解析, モデルの拡張, 結合が疎な場合の解析, パターン認識などへの応用など広く研究されている。疎な結合行列をもつ連想記憶は全結合の連想記憶よりも生物学的に妥当であり, 実装コストの削減にもつながる。本報告では, 疎な結合行列をもつ連想記憶のダイナミクスを理論的に解析する。幾何学的解析, 統計学的解析によって, 結合が疎になるほど記憶ベクトルが不安定になることと, 記憶ベクトルの引き込み領域が小さくなることが示される。

    CiNii

  • A Chaotic Cryptosystem based on a Finite-state Baker's map and its Security Analysis

    Proceedings of NOLTA99     613 - 616  1999年

  • Chaotic Cipher by Finite-state Baker's Map

    IEICE Transactions   J82-A ( 7 ) 1038 - 1046  1999年

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共同研究・競争的資金等の研究課題

  • 移動運動と学習記憶の確率モデルによる数理解析

    文部科学省  科学研究費補助金(新学術領域研究(研究領域提案型))

    研究期間:

    2008年
    -
    2009年
     

  • 社会ネットワークを考慮した、ゲームの数理モデリングと協力行動の解析

    文部科学省  科学研究費補助金(若手研究(B))

    研究期間:

    2008年
    -
    2009年
     

  • 神経回路構造に基づく協力行動の数理モデリング

    文部科学省  科学研究費補助金(特定領域研究)

    研究期間:

    2008年
     
     
     

  • Spatial Prisoner's Dilemma

    研究期間:

    2002年
    -
     
     

  • 空間囚人のジレンマ

    研究期間:

    2002年
    -
     
     

  • スパイクにより連絡するニューロン群の同期現象

    研究期間:

    2000年
    -
     
     

  • スパイクを受け取るニューロン群の情報処理

    研究期間:

    2000年
    -
     
     

  • カオス力学系を用いた秘密鍵暗号系

    研究期間:

    1998年
    -
     
     

  • ニューロンの同期現象の生物学的意味について

  • mathematical study of collective behavior resulted from social interactions of humans

  • synchronization of neurons interacting by feedback spikes

  • information processing of neural populations receiving spike inputs

  • 人間の社会的相互作用がもたらす集団的ふるまいの数理的研究

  • Application of chaotic cryptosystems

  • mathematical study of optimal designs of social organizations and networks

  • On biological functions of Synchronous behavior of neurons

  • カオス暗号の社会応用

  • private-key cryptosystems using chaotic dynamical systems

  • 社会的組織の最適設計の数理的研究

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現在担当している科目

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