Kazuyuki Aihara 研究室

主宰者：Kazuyuki Aihara

東京大学

AI 要約（直近 5 年の研究成果）

本研究室は、複雑な動的システムの解析と制御、および疾病予測などの応用を中心に、数学的モデリング・機械学習・神経ネットワーク理論を融合させた研究に取り組んでいます。特に、ランダムに初期化されたニューラルネットワークを時系列データの処理に活用する「リザーバーコンピューティング」という手法が一つの大きなテーマになっており、この方法により複雑な時間パターンを効率的に学習・予測することを実現しています。さらに研究室では、この基礎理論を医療・感染症対策といった実際の課題へ応用する研究も活発に行っています。例えば、新型コロナウイルス感染症やサル痘の患者データを数学モデルで分析し、個人ごとの感染ダイナミクスを定量化して患者を分類することで、より効果的な診断法の選択や患者層の把握に貢献しています。また、遺伝子制御ネットワークの動態変化を監視することで、疾病が発症する直前の状態を検出し、早期干預を可能にする手法も開発しています。このように、動的システム理論と機械学習を基礎に、神経科学から感染症、遺伝子ネットワークまで幅広い生命現象・医療現象を分析・予測する研究が進められています。理論と応用の両面で視点を養い、複雑な現象の本質を数学と計算で読み解く力を磨くことのできる環境です。

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

外部リンク

研究成果（158 件）

[2026] バランスの取れた大脳皮質E-Iネットワークにおける力学習
Force Learning in Balanced Cortical E-I Networks
DOI: https://doi.org/10.1162/neco.a.1503
[2026] スクリーニング及び隔離終了判定に最適な迅速抗原検査の特定：モデリング研究
Identifying the optimal rapid antigen test for screening and determining the end of isolation: A modeling study
DOI: https://doi.org/10.1371/journal.pcbi.1013102
[2026] 高速イジングマシンに基づく最適化の無線リソース割当問題への応用
Application of High-Speed Ising Machine based Optimization to Wireless Resource Allocation Problems
DOI: https://doi.org/10.1109/ccnc65079.2026.11366461
[2026] COVID-19患者の唾液におけるウイルス脱落パターンの階層化
Stratification of viral shedding patterns in saliva of COVID-19 patients
DOI: https://doi.org/10.7554/elife.96032.3
[2025] COVID-19患者の唾液におけるウイルス脱落パターンの階層化
Stratification of viral shedding patterns in saliva of COVID-19 patients
DOI: https://doi.org/10.7554/elife.96032.2
[2025] エコー状態ネットワークにおける疑似ローレンツアトラクタ
Pseudo-Lorenz attractors in echo state networks
DOI: https://doi.org/10.1007/s13160-025-00740-3
[2025] ガウス貯水池状態解析（GRSA）による多変量時系列データのオンライン分類
Online classification of multivariate time series data through Gaussian Reservoir State Analysis (GRSA)
DOI: https://doi.org/10.1109/ijcnn64981.2025.11227942
[2025] コンゴ民主共和国のクレード I mpox患者の臨床特性化のための病変遷移動態モデリング
Modeling lesion transition dynamics to clinically characterize patients with clade I mpox in the Democratic Republic of the Congo
DOI: https://doi.org/10.1126/scitranslmed.ads4773
[2025] 大規模言語モデルと失語症の比較
Comparison of Large Language Model with Aphasia
DOI: https://doi.org/10.1002/advs.202414016
[2025] 複雑ネットワークダイナミクスへの空間的早期警報シグナルの適用可能性
Applicability of spatial early warning signals to complex network dynamics
DOI: https://doi.org/10.1098/rsif.2024.0696

続きを表示（残り 148 件）

[2025] 貯水池コンピューティングにおける危機誘発間欠性
Crisis-induced intermittency in reservoir computing
DOI: https://doi.org/10.1103/vqvp-mbxx
[2025] mRNA-タンパク質遺伝子制御ネットワークの小サンプルサイズデータ駆動型早期疾患検出と再安定化
Small-Sample-Size Data-Driven Early Disease-Detection and Re-stabilization for mRNA-Protein Gene Regulatory Networks
DOI: https://doi.org/10.23919/acc63710.2025.11107418
[2025] Detection of atrial fibrillation from pulse waves using convolution neural networks and recurrence-based plots
DOI: https://doi.org/10.1063/5.0212068
[2025] 興奮性および自己発振型Izhikevichニューロンの混合集団における強健な振動動態：2次線形および非線形相互作用の影響
Robust oscillatory dynamics in a mixed population of excitable and self-oscillatory Izhikevich neurons: Influence of second-order linear and nonlinear interactions
DOI: https://doi.org/10.1063/5.0274541
[2025] カオスベース強化学習とTD3
Chaos-based reinforcement learning with TD3
DOI: https://doi.org/10.1016/j.neunet.2025.108202
[2025] 貯水池コンピューティングを用いた動的システムの適応制御
Adaptive control of dynamical systems using reservoir computing
DOI: https://doi.org/10.1063/5.0291585
[2025] アトピー性皮膚炎様症状を示すNC/Ngaマウスの疾患前期状態の同定：動的ネットワークバイオマーカーの利用
Identification of Pre-Disease State in NC/Nga Mice with Atopic Dermatitis-Like Symptoms Using Dynamical Network Biomarkers
DOI: https://doi.org/10.1016/j.jid.2025.09.009
[2025] 粒子群最適化を用いた複数の単純サイクル貯水池の構造化
Structuring Multiple Simple Cycle Reservoirs with Particle Swarm Optimization
DOI: https://doi.org/10.1109/ijcnn64981.2025.11228517
[2025] 複雑系予測における特徴不足の克服：代替遅延埋め込み法
Overcoming feature scarcity in complex system prediction: An alternative delay embedding
DOI: https://doi.org/10.1063/5.0279303
[2025] 生体肝移植における移植片喪失の早期術後期における予測
Prediction of graft loss in living donor liver transplantation during the early postoperative period
DOI: https://doi.org/10.1371/journal.pcbi.1013734
[2025] アナログメモリ内蔵コンピューティング回路における非理想性の活用：ニューロモルフィックシステムのための物理モデリングアプローチ
Harnessing Nonidealities in Analog In‐Memory Computing Circuits: A Physical Modeling Approach for Neuromorphic Systems
DOI: https://doi.org/10.1002/aisy.202500351
[2025] 実ニューロンにおけるカオス
Chaos in Real Neurons
DOI: https://doi.org/10.1142/s0218127425400073
[2025] Tu1803: 数学モデルを用いた炎症性腸疾患の病態解明への新規アプローチ
Tu1803: A NOVEL APPROACH TO ELUCIDATING THE PATHOGENESIS OF INFLAMMATORY BOWEL DISEASE USING MATHEMATICAL MODELS
DOI: https://doi.org/10.1016/s0016-5085(25)04332-x
[2025] Brain dynamics simulation of schizophrenia with chaotic neural networks
DOI: https://doi.org/10.1016/j.neucom.2025.129585
[2025] A modeling study to define guidelines for antigen screening in schools and workplaces to mitigate COVID-19 outbreaks
DOI: https://doi.org/10.1038/s43856-024-00716-3
[2025] 相関異常と前兆タンパク質シグナルを用いた単一細胞PLOM-CONアプローチによる細胞周期依存的な薬剤効果の層別化と解明
Unveiling and stratifying cell cycle-dependent drug efficacy using a single-cell PLOM-CON approach with correlation anomaly and presage protein signals
DOI: https://doi.org/10.1038/s42003-025-08916-w
[2025] Ultralow‐Dimensionality Reduction for Identifying Critical Transitions by Spatial‐Temporal PCA
DOI: https://doi.org/10.1002/advs.202408173
[2025] Information processing with large-scale network of optical oscillators
DOI: https://doi.org/10.1117/12.3040430
[2025] Integration of Dynamical Network Biomarkers, Control Theory and Drosophila Model Identifies Vasa/DDX4 as the Potential Therapeutic Targets for Metabolic Syndrome
DOI: https://doi.org/10.3390/cells14060415
[2025] Designing chaotic attractors: A semisupervised approach
DOI: https://doi.org/10.1103/physreve.111.034207
[2025] Detection of atrial fibrillation from pulse waves using convolution neural networks and recurrence-based plots
DOI: https://doi.org/10.1063/5.0212068
[2025] Information processing with large-scale network of optical oscillators
DOI: https://doi.org/10.1117/12.3040430
[2025] Designing chaotic attractors: A semisupervised approach
DOI: https://doi.org/10.1103/physreve.111.034207
[2025] Brain dynamics simulation of schizophrenia with chaotic neural networks
DOI: https://doi.org/10.1016/j.neucom.2025.129585
[2025] Neural activity responsiveness by maturation of inhibition underlying critical period plasticity
DOI: https://doi.org/10.3389/fncir.2024.1519704
[2025] High-Speed Resource Allocation for Multi-User NOMA Systems Using a Coherent Ising Machine
DOI: https://doi.org/10.1109/icoin63865.2025.10992949
[2025] Prediction of cccDNA dynamics in hepatitis B patients by a combination of serum surrogate markers
DOI: https://doi.org/10.1371/journal.pcbi.1012615
[2025] Neural activity responsiveness by maturation of inhibition underlying critical period plasticity
DOI: https://doi.org/10.3389/fncir.2024.1519704
[2025] High-Speed Resource Allocation for Multi-User NOMA Systems Using a Coherent Ising Machine
DOI: https://doi.org/10.1109/icoin63865.2025.10992949
[2025] Prediction of cccDNA dynamics in hepatitis B patients by a combination of serum surrogate markers
DOI: https://doi.org/10.1371/journal.pcbi.1012615
[2025] A modeling study to define guidelines for antigen screening in schools and workplaces to mitigate COVID-19 outbreaks
DOI: https://doi.org/10.1038/s43856-024-00716-3
[2025] Aging in a weighted ensemble of excitable and self-oscillatory neurons: The role of pairwise and higher-order interactions
DOI: https://doi.org/10.1063/5.0247769
[2025] COVID-19 mRNAワクチン接種後の追従抗体価測定による後続感染リスク患者の特定
Longitudinal antibody titers measured after COVID-19 mRNA vaccination can identify individuals at risk for subsequent infection
DOI: https://doi.org/10.1126/scitranslmed.adv4214
[2025] 結合光パラメトリック発振器に基づくフォトニックスパイキングニューラルネットワーク
Photonic Spiking Neural Network Based on Coupled Optical Parametric Oscillators
DOI: https://doi.org/10.23919/oecc/psc62146.2025.11109680
[2024] Learning reservoir dynamics with temporal self-modulation
DOI: https://doi.org/10.1038/s42005-023-01500-w
[2024] Modelling the effectiveness of an isolation strategy for managing mpox outbreaks with variable infectiousness profiles
DOI: https://doi.org/10.1038/s41467-024-51143-w
[2024] Impact of time-history terms on reservoir dynamics and prediction accuracy in echo state networks
DOI: https://doi.org/10.1038/s41598-024-59143-y
[2024] Anticipating regime shifts by mixing early warning signals from different nodes
DOI: https://doi.org/10.1038/s41467-024-45476-9
[2024] Re-Stabilizing Large-Scale Network Systems Using High-Dimension Low-Sample-Size Data Analysis
DOI: https://doi.org/10.1109/tetci.2024.3442824
[2024] Can Timing-Based Backpropagation Overcome Single-Spike Restrictions in Spiking Neural Networks?
DOI: https://doi.org/10.1109/ijcnn60899.2024.10651135
[2024] Modeling and predicting individual variation in COVID-19 vaccine-elicited antibody response in the general population
DOI: https://doi.org/10.1371/journal.pdig.0000497
[2024] Exogenous and endogenous factors affecting stock market transactions: A Hawkes process analysis of the Tokyo Stock Exchange during the COVID-19 pandemic
DOI: https://doi.org/10.1371/journal.pone.0301462
[2024] Impact of time-history terms on reservoir dynamics and prediction accuracy in echo state networks
DOI: https://doi.org/10.1038/s41598-024-59143-y
[2024] Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers
DOI: https://doi.org/10.1371/journal.pcbi.1011238
[2024] Nonlinear Dynamics of the Brain and its Mathematical Structure
DOI: https://doi.org/10.2142/biophys.64.272
[2024] Applying Coherent Ising Machines for Enhancing Communication Efficiency in Large-Scale UAV-Aided Networks
DOI: https://doi.org/10.1109/access.2024.3450539
[2024] Nonlinear Dynamics of the Brain and its Mathematical Structure
DOI: https://doi.org/10.2142/biophys.64.272
[2024] Applying Coherent Ising Machines for Enhancing Communication Efficiency in Large-Scale UAV-Aided Networks
DOI: https://doi.org/10.1109/access.2024.3450539
[2024] Anticipating regime shifts by mixing early warning signals from different nodes
DOI: https://doi.org/10.1038/s41467-024-45476-9
[2024] Traffic Signal Optimization in Large-Scale Urban Road Networks: An Adaptive-Predictive Controller Using Ising Models
DOI: https://doi.org/10.1109/access.2024.3514162
[2024] Traffic Signal Optimization in Large-Scale Urban Road Networks: An Adaptive-Predictive Controller Using Ising Models
DOI: https://doi.org/10.1109/access.2024.3514162
[2024] Learning reservoir dynamics with temporal self-modulation
DOI: https://doi.org/10.1038/s42005-023-01500-w
[2024] Exogenous and endogenous factors affecting stock market transactions: A Hawkes process analysis of the Tokyo Stock Exchange during the COVID-19 pandemic
DOI: https://doi.org/10.1371/journal.pone.0301462
[2024] Dynamic tuning of neural stability for cognitive control
DOI: https://doi.org/10.1073/pnas.2409487121
[2024] Dynamic tuning of neural stability for cognitive control
DOI: https://doi.org/10.1073/pnas.2409487121
[2024] MCGAE: unraveling tumor invasion through integrated multimodal spatial transcriptomics
DOI: https://doi.org/10.1093/bib/bbae608
[2024] Modelling the effectiveness of an isolation strategy for managing mpox outbreaks with variable infectiousness profiles
DOI: https://doi.org/10.1038/s41467-024-51143-w
[2024] Can Timing-Based Backpropagation Overcome Single-Spike Restrictions in Spiking Neural Networks?
DOI: https://doi.org/10.1109/ijcnn60899.2024.10651135
[2024] Modeling and predicting individual variation in COVID-19 vaccine-elicited antibody response in the general population
DOI: https://doi.org/10.1371/journal.pdig.0000497
[2024] MCGAE: unraveling tumor invasion through integrated multimodal spatial transcriptomics
DOI: https://doi.org/10.1093/bib/bbae608
[2023] Experimental observation of chimera states in spiking neural networks based on degenerate optical parametric oscillators
DOI: https://doi.org/10.1038/s42005-023-01240-x
[2023] Data-Driven Re-stabilization of Gene Regulatory Network Towards Early Medical Treatment
DOI: https://doi.org/10.1016/j.ifacol.2023.10.738
[2023] Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks
DOI: https://doi.org/10.1162/neco_a_01596
[2023] Infectious virus shedding duration reflects secretory IgA antibody response latency after SARS-CoV-2 infection
DOI: https://doi.org/10.1073/pnas.2314808120
[2023] Sparse-firing regularization methods for spiking neural networks with time-to-first-spike coding
DOI: https://doi.org/10.1038/s41598-023-50201-5
[2023] Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution
DOI: https://doi.org/10.1038/s41467-023-43043-2
[2023] Sparse-firing regularization methods for spiking neural networks with time-to-first-spike coding
DOI: https://doi.org/10.1038/s41598-023-50201-5
[2023] Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution
DOI: https://doi.org/10.1038/s41467-023-43043-2
[2023] STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning
DOI: https://doi.org/10.1093/nar/gkad801
[2023] High-Speed Resource Allocation Algorithm Using a Coherent Ising Machine for NOMA Systems
DOI: https://doi.org/10.1109/tvt.2023.3300920
[2023] STAMarker: determining spatial domain-specific variable genes with saliency maps in deep learning
DOI: https://doi.org/10.1093/nar/gkad801
[2023] Earthquake alerting based on spatial geodetic data by spatiotemporal information transformation learning
DOI: https://doi.org/10.1073/pnas.2302275120
[2023] High-Speed Resource Allocation Algorithm Using a Coherent Ising Machine for NOMA Systems
DOI: https://doi.org/10.1109/tvt.2023.3300920
[2023] Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks
DOI: https://doi.org/10.1162/neco_a_01596
[2023] Contrastively generative self-expression model for single-cell and spatial multimodal data
DOI: https://doi.org/10.1093/bib/bbad265
[2023] Contrastively generative self-expression model for single-cell and spatial multimodal data
DOI: https://doi.org/10.1093/bib/bbad265
[2023] Optimal Excitatory and Inhibitory Balance for High Learning Performance in Spiking Neural Networks with Long-Tailed Synaptic Weight Distributions
DOI: https://doi.org/10.1109/ijcnn54540.2023.10191709
[2023] Optimal Excitatory and Inhibitory Balance for High Learning Performance in Spiking Neural Networks with Long-Tailed Synaptic Weight Distributions
DOI: https://doi.org/10.1109/ijcnn54540.2023.10191709
[2023] Experimental observation of chimera states in spiking neural networks based on degenerate optical parametric oscillators
DOI: https://doi.org/10.1038/s42005-023-01240-x
[2023] Design of input assignment and feedback gain for re‐stabilizing undirected networks with High‐Dimension Low‐Sample‐Size data
DOI: https://doi.org/10.1002/rnc.6720
[2023] Entropic herding
DOI: https://doi.org/10.1007/s11222-022-10199-8
[2023] Model-Free Dominant Pole Placement for Restabilizing High-Dimensional Network Systems via Small-Sample-Size Data
DOI: https://doi.org/10.1109/access.2023.3274530
[2023] Pre-disease Detection Using Dynamical Network Biomarkers in Gene Regulatory Networks with Cell-to-cell Interaction
DOI: https://doi.org/10.1016/j.ifacol.2023.10.859
[2022] A Spiking Neural Network with Resistively Coupled Synapses Using Time-to-First-Spike Coding Towards Efficient Charge-Domain Computing
DOI: https://doi.org/10.1109/iscas48785.2022.9937662
[2022] Embedding entropy: a nonlinear measure of dynamical causality
DOI: https://doi.org/10.1098/rsif.2021.0766
[2022] Criticality in the Healthy Brain
DOI: https://doi.org/10.3389/fnetp.2021.755685
[2022] A 18.7 TOPS/W Mixed-Signal Spiking Neural Network Processor With 8-bit Synaptic Weight On-Chip Learning That Operates in the Continuous-Time Domain
DOI: https://doi.org/10.1109/access.2022.3170579
[2022] Low-Sample-Size Data-Driven Re-stabilization of Gene Network Systems
DOI: https://doi.org/10.1016/j.ifacol.2022.09.353
[2022] Low-Sample-Size Data-Driven Re-stabilization of Gene Network Systems
DOI: https://doi.org/10.1016/j.ifacol.2022.09.353
[2022] A 18.7 TOPS/W Mixed-Signal Spiking Neural Network Processor With 8-bit Synaptic Weight On-Chip Learning That Operates in the Continuous-Time Domain
DOI: https://doi.org/10.1109/access.2022.3170579
[2022] Estimation of timing of infection from longitudinal SARS-CoV-2 viral load data: mathematical modelling study
DOI: https://doi.org/10.1186/s12879-022-07646-2
[2022] Monkey Prefrontal Single-Unit Activity Reflecting Category-Based Logical Thinking Process and Its Neural Network Model
DOI: https://doi.org/10.1523/jneurosci.2286-21.2022
[2022] Energy landscape decomposition for cell differentiation with proliferation effect
DOI: https://doi.org/10.1093/nsr/nwac116
[2022] Criticality in the Healthy Brain
DOI: https://doi.org/10.3389/fnetp.2021.755685
[2022] Reservoir computing with diverse timescales for prediction of multiscale dynamics
DOI: https://doi.org/10.1103/physrevresearch.4.l032014
[2022] Early dynamics of chronic myeloid leukemia on nilotinib predicts deep molecular response
DOI: https://doi.org/10.1038/s41540-022-00248-3
[2022] A Trainable Synapse Circuit Using a Time-Domain Digital-to-Analog Converter
DOI: https://doi.org/10.1007/s00034-022-02168-3
[2022] Designing isolation guidelines for COVID-19 patients with rapid antigen tests
DOI: https://doi.org/10.1038/s41467-022-32663-9
[2022] Reservoir computing with diverse timescales for prediction of multiscale dynamics
DOI: https://doi.org/10.1103/physrevresearch.4.l032014
[2022] Estimation of timing of infection from longitudinal SARS-CoV-2 viral load data: mathematical modelling study
DOI: https://doi.org/10.1186/s12879-022-07646-2
[2022] Monkey Prefrontal Single-Unit Activity Reflecting Category-Based Logical Thinking Process and Its Neural Network Model
DOI: https://doi.org/10.1523/jneurosci.2286-21.2022
[2022] Energy landscape decomposition for cell differentiation with proliferation effect
DOI: https://doi.org/10.1093/nsr/nwac116
[2022] Mean-field analysis of Stuart–Landau oscillator networks with symmetric coupling and dynamical noise
DOI: https://doi.org/10.1063/5.0081295
[2022] A Spiking Neural Network with Resistively Coupled Synapses Using Time-to-First-Spike Coding Towards Efficient Charge-Domain Computing
DOI: https://doi.org/10.1109/iscas48785.2022.9937662
[2022] Embedding entropy: a nonlinear measure of dynamical causality
DOI: https://doi.org/10.1098/rsif.2021.0766
[2022] Mean-field analysis of Stuart–Landau oscillator networks with symmetric coupling and dynamical noise
DOI: https://doi.org/10.1063/5.0081295
[2021] A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2
DOI: https://doi.org/10.1371/journal.pbio.3001128
[2021] Estimation of the incubation period of COVID-19 using viral load data
DOI: https://doi.org/10.1016/j.epidem.2021.100454
[2021] A High-Speed Channel Assignment Algorithm for Dense IEEE 802.11 Systems via Coherent Ising Machine
DOI: https://doi.org/10.1109/lwc.2021.3077311
[2021] A High-Speed Channel Assignment Algorithm for Dense IEEE 802.11 Systems via Coherent Ising Machine
DOI: https://doi.org/10.1109/lwc.2021.3077311
[2021] Practical Data‐Driven Flood Forecasting Based on Dynamical Systems Theory
DOI: https://doi.org/10.1029/2020wr028427
[2021] Coherent Ising Machine Based Optimal Channel Allocation and User Pairing in NOMA Networks
DOI: https://doi.org/10.1109/icaiic51459.2021.9415221
[2021] Time variation in the probability of failing to detect a case of polymerase chain reaction testing for SARS-CoV-2 as estimated from a viral dynamics model
DOI: https://doi.org/10.1098/rsif.2020.0947
[2021] CMOS Mixed-Signal Spiking Neural Network Circuit Using a Time-Domain Digital-To-Analog Converter
DOI: https://doi.org/10.1109/iscas51556.2021.9401230
[2021] Potential anti-COVID-19 agents, cepharanthine and nelfinavir, and their usage for combination treatment
DOI: https://doi.org/10.1016/j.isci.2021.102367
[2021] Predicting local COVID-19 outbreaks and infectious disease epidemics based on landscape network entropy
DOI: https://doi.org/10.1016/j.scib.2021.03.022
[2021] A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2
DOI: https://doi.org/10.1371/journal.pbio.3001128
[2021] Estimation of the incubation period of COVID-19 using viral load data
DOI: https://doi.org/10.1016/j.epidem.2021.100454
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