{"id":78,"date":"2011-11-23T22:22:37","date_gmt":"2011-11-23T13:22:37","guid":{"rendered":"http:\/\/www.cns.atr.jp\/dbi\/"},"modified":"2026-02-09T12:43:52","modified_gmt":"2026-02-09T03:43:52","slug":"publications-ja","status":"publish","type":"page","link":"https:\/\/bicr.atr.jp\/dbi\/publications-ja\/","title":{"rendered":"\u7814\u7a76\u696d\u7e3e"},"content":{"rendered":"

<\/a><\/p>\n

2026\u5e74<\/h3>\n

\u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

    \n
  1. Tsutsumi M<\/u>, Kishi T<\/u>, Ogawa T<\/u>, Kuroda T<\/u>, Kobler R, Kawanabe M<\/u>.
    \n    An EEG dataset with carbon wire loops in cognitive tasks and resting state inside and outside MR scanners.<\/a>
    \nScientific Data<\/em>, 2026.<\/li>\n
  2. Podlesnik CA, Martinez-Perez CN, Montague KL, Ritchey CM, Lamperski MS, Kuroda T<\/u>.
    \n    Evaluating multiple-context training to mitigate renewal following differential reinforcement.<\/a>
    \nJ Exp Anal Behav<\/em>, 2026 (accepted).<\/li>\n<\/ol>\n

    \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

      \n
    1. Li S<\/u>, Chu S, Koc O, Ding Y, Zhao Q, Kawanabe M<\/u>, and Chen Z.
      \n      HEEGNet: Hyperbolic Embeddings for EEG.<\/a>
      \nICLR 2026<\/em>, accepted.<\/li>\n
    2. Y Tang, J Bang, S Li<\/u>, Y Li, C Liu, X Zhou, Y Ding, C Guan.
      \nEEG-D2: Dataset Distillation for Efficient Large EEG Model Training.
      \nAAAI Conference on Artificial Intelligence 2026<\/em>, accepted.<\/li>\n<\/ol>\n

      \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

        \n
      1. Ogawa T<\/u>, Kuroda T<\/u>, Tsutsumi M<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
        \nStatistical profiles of dynamic brain states associated with changes in confidence.
        \nTechnical Committee of CQ\/CBE<\/em>, Beppu, Japan, January, 2026.<\/li>\n<\/ol>\n

        <\/a><\/p>\n

        2025\u5e74<\/h3>\n

        \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

          \n
        1. Podlesnik CA, Martinez-Perez CN, Ritchey CM, Kuroda T<\/u>.
          \n          Cues paired with alternative reinforcement mitigate resurgence in humans.<\/a>
          \nLearning & Motivation<\/em>, 91<\/strong>: 102137, 2025.<\/li>\n
        2. Villalobos AM, \u00c1vila-Rozo DA, Ritchey CM, Martinez-Perez CN, Lamperski MS, Kuroda T<\/u>, Podlesnik CA.
          \n          Resurgence of target behavior after negative punishment of alternative behavior.<\/a>
          \nBehav Processes<\/em>, 105238, 2025.<\/li>\n
        3. Ritchey CM, Kuroda T<\/u>, Podlesnik CA.
          \n          Examining resurgence following alternating exposures to high- and low-magnitude alternative reinforcement.<\/a>
          \nLearning & Motivation<\/em>, 90<\/strong>: 102133, 2025.<\/li>\n
        4. Montague KL, Ritchey CM, Martinez-Perez CN, Kuroda T<\/u>, Podlesnik CA.
          \n          A quantitative analysis of the effects of target and alternative reinforcement rate on resurgence.<\/a>
          \nJ Exp Anal Beh<\/em>, 123<\/strong>: 455-470, 2025.<\/li>\n
        5. Ogawa T<\/u>, Aihara T, Yamashita O.
          \n          Neural Correlates and Dynamical Brain States of Creative Insight in a Spatial Problem Task.<\/a>
          \nScientific Reports<\/em>, 15<\/strong>:1, 1-13, 2025.<\/li>\n<\/ol>\n

          \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

            \n
          1. Li S<\/u>, Kawanabe M<\/u>, Kobler R<\/u>.
            \n            SPDIM: Source-free unsupervised conditional and label shift adaptation in EEG.<\/a>
            \nICLR2025<\/em>, Singapore, April, 2025.<\/li>\n<\/ol>\n

            \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

              \n
            1. Kuroda T<\/u>, Ogawa T<\/u>, Tsutsumi M<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
              \nConfidence about rules measured in a novel behavioral task and decoded from simultaneous EEG-fMRI.
              \nNeuroscience 2025<\/em>, San Diego, USA, November, 2025.<\/li>\n
            2. Tsutsumi M<\/u>, Kuroda T<\/u>, Ogawa T<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
              \nDeveloping and validating a task for capturing confidence fluctuations.
              \nThe 89th Annual Convention of Japanese Psychological Association<\/em>, Sendai, Japan, September, 2025.<\/li>\n
            3. Ogawa T<\/u>.
              \nAn analysis of statistical profile for dynamic brain state associated with verbal insight problem solving.
              \nCogNac x CBE workshop<\/em>, Sendai, Japan, September, 2025.<\/li>\n
            4. Kuroda T<\/u>, Ogawa T<\/u>, Kishi T<\/u>, Tsutsumi M<\/u>, Kawanabe M<\/u>.
              \nThe failure of differential reinforcement due to a mismatch between a response and its receiving end: An operant simulation of neurofeedback.
              \nThe 43th Annual Convention of Japanese Association for Behavioral Analysis<\/em>, Fukui, Japan, August, 2025.<\/li>\n
            5. Ogawa T<\/u>, Kuroda T<\/u>, Kishi T<\/u>, Tsutsumi M<\/u>, Kawanabe M<\/u>.
              \nConfidence as public and private events in a contingency and decoding from the brain activity.
              \nThe 43th Annual Convention of Japanese Association for Behavioral Analysis<\/em>, Fukui, Japan, August, 2025.<\/li>\n
            6. Hosoya H<\/u>.
              \nA computational model of structural analogy that reuses grid cells for learning abstract relational representations.
              \nThe 48th Annual Meeting of Japan Neuroscience Society<\/em>, Niigata, Japan, July, 2025.<\/li>\n
            7. Kuroda T<\/u>, Kawanabe M<\/u>.
              \nConditional discrimination of EEG.
              \nThe 48th Annual Meeting of Japan Neuroscience Society<\/em>, Niigata, Japan, July, 2025.<\/li>\n
            8. Kishi T<\/u>, Tsustumi M<\/u>, Ogawa T<\/u>, Kuroda T<\/u>, Kobler RJ<\/u>, Kawanabe M<\/u>.
              \nSimultaneous EEG-fMRI dataset recorded from multiple MRI scanners using a carbon-wire-loop.
              \nThe 48th Annual Meeting of Japan Neuroscience Society<\/em>, Niigata, Japan, July, 2025.<\/li>\n
            9. Ogawa T<\/u>, Aihara T, Yamashita O.
              \nImplications of strategy-dependent neural mechanisms and cognitive flexibility for spatial insight problem-solving.
              \nThe 48th Annual Meeting of Japan Neuroscience Society<\/em>, Niigata, Japan, July, 2025.<\/li>\n
            10. Noda S<\/u>, Kawashima T, Ogawa T<\/u>, Tamano R<\/u> et al.
              \nDevelopment of EEG neurofeedback training based on fMRI-biomarker for patients with schizophrenia.
              \nInternational Symposium on Decoded Neurofeedback<\/em>, Nara, Japan, July, 2025. (invited talk)<\/li>\n
            11. Li S<\/u>, Kawanabe M<\/u>, Kobler R<\/u>.
              \nSource-free unsupervised conditional and label shift adaptation in EEG.
              \nWinter Workshop on Mechanism of Brain and Mind 2025<\/em>, Hokkaido, Japan, March, 2025.<\/li>\n
            12. Yoshida T<\/u>, Kawanabe M<\/u>, Kuroda T<\/u>.
              \nFiner EEG-based Emotion Recognition with Semantic Space Theory.
              \nTechnical Committee of CQ\/CBE<\/em>, Fukuoka, Japan, January, 2025.<\/li>\n
            13. Ogawa T<\/u>.
              \nA perspective on environmental factors that promote spatial insight problem-solving.
              \nTechnical Committee of CQ\/CBE<\/em>, Fukuoka, Japan, January, 2025.<\/li>\n<\/ol>\n

              <\/a><\/p>\n

              2024\u5e74<\/h3>\n

              \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                \n
              1. Kuroda T<\/u>, Kobler RJ<\/u>, Ogawa T<\/u>, Tsutsumi M<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
                \n                Test-retest reliability of EEG microstate metrics for evaluating noise reductions in simultaneous EEG-fMRI.<\/a>
                \nImaging Neuroscience<\/em>, 2<\/strong>: 1\u201320, 2024.<\/li>\n
              2. Martinez-Perez CN, Ritchey CM, Gregory ME, Kuroda T<\/u>, Gage NA, Podlesnik CA.
                \n                A parametric manipulation and meta-analysis of target-response punishment on resurgence.<\/a>
                \nJ Exp Anal Behav<\/em>, 112<\/strong>: 139-157, 2024.<\/li>\n
              3. Ritchey CM, Martinez-Perez CN, Lamperski MS, Kuroda T<\/u>, Podlesnik CA.
                \n                Examining the effects of response-cost punishment and extinction in isolation and combination on resurgence.<\/a>
                \nLearning & Motivation<\/em>, 87<\/strong>: 102018, 2024.<\/li>\n<\/ol>\n

                \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                  \n
                1. Li S<\/u>, Kawanabe M<\/u>, Kobler R<\/u>.
                  \n                  Geometric deep learning to enhance imbalanced domain adaptation in EEG.<\/a>
                  \nESANN2024<\/em>, Bruges, Belgium, October, 2024.<\/li>\n
                2. Sakamoto K<\/u>, Azuma D, Miyanishi T<\/u>, Kurita S, Kawanabe M<\/u>.
                  \n                  Map-based Modular Approach for Zero-shot Embodied Question Answering.<\/a>
                  \nIROS 2024<\/em>, Abu Dhabi, UAE, October, 2024.<\/li>\n
                3. Azuma D, Miyanishi T<\/u>, Kurita S, Sakamoto K<\/u>, Kawanabe M<\/u>.
                  \n                  Answerability Fields: Answerable Location Estimation via Diffusion Models.<\/a>
                  \nIROS 2024<\/em>, Abu Dhabi, UAE, October, 2024.<\/li>\n
                4. Hosoya H<\/u>.
                  \n                  A Cognitive Model for Learning Abstract Structures from Memory-based Relational Decision-Making.<\/a>
                  \nICLR’24<\/em>, Vienna, Austria, May, 2024.<\/li>\n
                5. Ju C, Kobler R<\/u>, Tang L, Guan C, Kawanabe M<\/u>.
                  \n                  Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data.<\/a>
                  \nICLR’24<\/em>(accepted; spotlight), Vienna, Austria, May, 2024.<\/li>\n
                6. Miyanishi T<\/u>, Azuma D, Kurita S, Kawanabe M<\/u>.
                  \n                  Cross3DVG: Cross-Dataset 3D Visual Grounding on Different RGB-D Scans.<\/a>
                  \nProc. 3DV\u201924<\/em>, 2024.<\/li>\n<\/ol>\n

                  \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                    \n
                  1. Tsutsumi M<\/u>, Kuroda T<\/u>, Kobler RJ<\/u>, Ogawa T<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
                    \nEvaluation method for noise reduction in simultaneous EEG-fMRI measurement using Test-retest reliability of EEG microstate.
                    \nThe 88th Annual Convention of JPA<\/em>, Kumamoto, Japan, Sept, 2024.<\/li>\n
                  2. Kuroda T<\/u>.
                    \nConditional discrimination of EEG microstate.
                    \nThe 42nd Annual Convention of J-ABA<\/em>, Tokyo, Japan, July, 2024.<\/li>\n
                  3. Montague K, Martinez-Perez CN, Ritchey C, Seijo A, Kuroda T<\/u>, Podlesnik CA.
                    \nAn evaluation of the effects of multiple-context training on Applied Behavior Analysis (ABA) and ABC renewal.
                    \nThe 50th Annual Convention of ABAI<\/em>, Pennsylvania, USA, 2024.<\/li>\n
                  4. Martinez-Perez CN, Ritchey C, Kuroda T<\/u>, Montague K, Williams J, Zhen J, Podlesnik CA.
                    \nAn evaluation of the effects of multiple-context training on Applied Behavior Analysis (ABA) and ABC renewal.
                    \nThe 50th Annual Convention of ABAI<\/em>, Pennsylvania, USA, 2024.<\/li>\n
                  5. Kuroda T<\/u>, Kawanabe M<\/u>.
                    \nAn energy landscape analysis of EEG as an alternative to microstate.
                    \nJST Moonshot 9 Retreat<\/em>, Hyogo, Japan, April, 2024.<\/li>\n
                  6. Hosoya H<\/u>.
                    \nA learning model of abstract relational structure explains brain activities in the human hippocampal formation.
                    \nNeuro2024<\/em>, Fukuoka, Japan, July, 2024.<\/li>\n
                  7. Ogawa T<\/u>, Kuroda T<\/u>, Kobler RJ<\/u>, Tsutsumi M<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
                    \nA robust noise reduction filter consisting of the autoregressive model with exogenous input for EEG measured in MRI.
                    \nNeuro2024<\/em>, Fukuoka, Japan, July, 2024.<\/li>\n
                  8. Kishi T<\/u>, Kuroda T<\/u>, Kobler RJ<\/u>, Ogawa T<\/u>, Tsutsumi M<\/u>, Kawanabe M<\/u>.
                    \nTest-retest reliability of EEG microstate metrics to assess noise reduction in simultaneous EEG-fMRI
                    \nNeuro2024<\/em>, Fukuoka, Japan, July, 2024.<\/li>\n
                  9. Kobler RJ<\/u>, Kuroda T<\/u>, Ogawa T<\/u>, Kawanabe M<\/u>.
                    \nData-driven latent alignment in simultaneous EEG-fMRI to fuse and generalize brain states.
                    \nNeuro2024<\/em>, Fukuoka, Japan, July, 2024.<\/li>\n
                  10. Tamano R<\/u>, Ogawa T<\/u>, Katagiri A, Cai C, Asai T, Kawanabe M<\/u>.
                    \nCharacteristics of EEG microstate dynamics during working memory task.
                    \nThe 26th Annual Meeting of the Japanese Phamaco-EEG Society<\/em>, Kyoto, Japan, July 2024 (*invited talk).<\/li>\n
                  11. Kobler R<\/u>, Kuroda T<\/u>, Ogawa T<\/u>, Ju C, Kawanabe M<\/u>.
                    \nData-driven latent alignment in simultaneous EEG-fMRI to fuse and generalize brain states.
                    \nOHBM2024<\/em>, Seoul, Korea, June 2024.<\/li>\n
                  12. Kuroda T<\/u>, Ogawa T<\/u>, Reinmar K<\/u>, Tsutsumi M<\/u>, Kishi T<\/u>, Kawanabe M<\/u>.
                    \nMicrostate-metric test-retest reliability to assess simultaneous EEG-fMRI noise reduction methods.
                    \nOHBM2024<\/em>, Seoul, Korea, June 2024.<\/li>\n<\/ol>\n

                    <\/a><\/p>\n

                    2023\u5e74<\/h3>\n

                    \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                      \n
                    1. Kuroda T<\/u>, Ritchey CM, Podlesnik CA.
                      \n                      Selective effects of conspecific movement on social preference in zebrafish (Danio rerio) using real-time 3D tracking and 3D animation.<\/a>
                      \nScientific Reports<\/em>, 13<\/strong>, June 2023.<\/li>\n
                    2. Ritchey CM, Kuroda T<\/u>, Podlesnik CA.
                      \n                      A quantitative analysis of resurgence following downshifts in alternative-reinforcer magnitude.<\/a>
                      \nJournal of the Experimental Analysis of Behavior<\/em>, 119<\/strong>, March 2023.<\/li>\n<\/ol>\n

                      \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                        \n
                      1. \n
                          \n
                        1. Miyanishi T<\/u>, Kitamori F, Kurita S, Lee J, Kawanabe M<\/u>, Inoue N.
                          \n                          CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data.<\/a>
                          \nProc. NeurIPS<\/em>, 2023.<\/li>\n
                        2. Kobler R, Kawanabe M<\/u>.
                          \nTSMNet for BCI: online, unsupervised adaptation.
                          \nProc the 10th International BCI Meeting<\/em>, Brussels, Belgium, May 2023.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

                          Ju C, Kobler R<\/u>, Guan C.
                          \nScore-Based Data Generation for Spatial Covariance Matrices of Electroencephalography.
                          \nProc. the 45th EMBC<\/em>, Sydney, Australia, July 2023.<\/p>\n

                          \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                            \n
                          1. Kobler R<\/u>.
                            \nGeometric Deep Learning meets BCI.
                            \nCutting Gardens<\/em>, 2023 (invited talk).<\/li>\n
                          2. Kobler R<\/u>, Hirayama J, Zhao Q, Kawanabe M<\/u>.
                            \nTSMNet for BMI: inter-subject and session transfer and online, unsupervised adaptation.
                            \nThe 10th annual meeting of JBMI<\/em>, Kyoto, Japan, November 11, 2023.<\/li>\n
                          3. Hosoya H<\/u>. “Categorical Invariant Generative Model (CIGMO): Deep Generative Learning Inspired by Primate Higher Vision,” Neuroscience 2023<\/em>, Washington DC, USA, November, 2023.<\/li>\n
                          4. Ogawa T, Kuroda T, Kobler RJ, Tsutsumi M, Kishi T, Kawanabe M<\/u>. \u201cA denoising filter for the simultaneously recorded EEG-fMRI data by using an autoregressive model with exogenous input with carbon-wire loop signals.\u201d Neuroscience 2023<\/em>, Washington DC, USA, November, 2023.<\/li>\n
                          5. Kuroda T, Ogawa T, Kobler RJ, Tsutsumi M, Kishi T, Kawanabe M<\/u>. \u201cA proposal for denoising EEG recorded simultaneously with fMRI.\u201d The 10th annual meeting of JBMI<\/em>, Kyoto, Japan, November 11, 2023.<\/li>\n
                          6. Tsutsumi M, Kuroda T, Ogawa T, Kishi T, Kobler RJ, Kawanabe M<\/u>. \u201cComparison of fMRI data during tasks in different sequences.\u201d The 10th annual meeting of JBMI<\/em>, Kyoto, Japan, November 11, 2023.<\/li>\n
                          7. Tamano R, Ogawa T<\/u>, Katagiri A, Cai C, Kawanabe M<\/u>. “Estimation of the functional connectivity-based biomarkers for schizophrenia and depression using machine learning and simultaneous EEG-fMRI; towards to EEG-neurofeedback training,” Proc. 36th ECNP Congress 2023<\/em>, Oct7-10, 2023.<\/li>\n
                          8. Hasegawa F, Kuroda T<\/u>. \u201cThe preference for biological motion in children under simultaneous choice test.\u201d The 41st annual meeting of JABA<\/em>, Osaka, Japan, September 15, 2023.<\/li>\n
                          9. Kuroda T<\/u>. \u201cSuccessive reinforcement of approximations to the target EEG-microstate.\u201d The 41st annual meeting of JABA<\/em>, Osaka, Japan, September 14, 2023.<\/li>\n
                          10. Ogawa T<\/u>. \u201cA neuroscientific\/psychological approach associated with problem-solving.” The 24th Technical Committee of CBE<\/em>, Sendai & online, Aug 25, 2023.<\/li>\n
                          11. Tamano R, Ogawa T<\/u>, Katagiri A, Cai C, Asai T, Kawanabe M<\/u>. “Dynamic properties of EEG microstate associated with working memory.” JPEG 2023<\/em>, Osaka, Japan, Aug 4-5, 2023 (Invited talk)<\/li>\n
                          12. Hosoya H<\/u>. “A computational model that learns to represent abstract relational structure from memory-based decision making,” The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          13. Kuroda T, Ogawa T, Kobler R, Tsutsumi M, Kishi T, Kawanabe M<\/u>. “Comparisons of event-related potentials in visual oddball and N-back tasks conducted inside and outside MRI following noise reductions,” The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          14. Kobler R, Kuroda T, Ogawa T, Kawanabe M<\/u>. “Towards decoding fMRI-derived large-scale brain dynamics at rest from EEG: a simultaneous EEG-fMRI study,” The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          15. Tsutsumi M, Kuroda T, Ogawa T, Kishi T, Kobler RJ, Kawanabe M<\/u>. \u201cEvaluating reproducibility of functional MRI across scanners: the impact of scanning sequences on statistical outcome measures during oddball and n-back tasks.\u201d The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          16. Kishi T, Kuroda T, Ogawa T, Tsutsumi M, Kobler RJ, Kawanabe M<\/u>. \u201cEvaluating the effectiveness of carbon-wire loop artifact removal in EEG-fMRI simultaneous measurements across different scanners.\u201d The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          17. Ogawa T, Kuroda T, Kobler R, Tsutsumi M, Kishi T, Kawanabe M<\/u>. \u201cImproving EEG signal quality in the concurrent measurement of EEG-fMRI using signals of carbon-wire loops and nonlinear filter consisting of autoregressive with exogenous input.” The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          18. Tamano R, Ogawa T<\/u>, Katagiri A, Cai C, Kawanabe M<\/u>. “Estimation of the functional connectivity-based biomarkers for schizophrenia and depression using machine learning and simultaneous EEG-fMRI data from healthy subjects; towards to EEG-neurofeedback training,” The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          19. Noda S, Tamano R, Ogawa T, Kawanabe M<\/u>. “Improving EEG-fMRI analysis: a preliminary assessment of the IC-U-Net for artifact removal,” The 46th Annual Meeting of JNSS<\/em>, Sendai, Japan, August 1, 2023.<\/li>\n
                          20. Montague K, Ritchey C, Martinez-Perez CN, Murphy S, Kuroda T<\/u>, Podlesnik CA. \u201cA quantitative analysis of the effects of target and alternative reinforcement rate on resurgence.\u201d The 49th annual convention of ABAI<\/em>, Denver, CO, May, 2023.<\/li>\n
                          21. Martinez-Perez CN, Ritchey C, Kuroda T<\/u>, Montague K, Podlesnik CA. \u201cExamining punishment of target behavior on resurgence: A parametric study of response cost and meta-analysis.\u201d The 49th annual convention of ABAI<\/em>, Denver, CO, May, 2023.<\/li>\n
                          22. Kuroda T<\/u>, Ogawa T<\/u>, Kobler R<\/u>, Tsutsumi M<\/u>, Kishi T<\/u>, Kawanabe M<\/u>. “A new type of neurofeedback based on EEG-fMRI simultaneous recording.” The 26th annual meeting of the Society for the Analysis of Human Behavior<\/em>, Kyoto, Japan, March 18, 2023 (invited talk).<\/li>\n
                          23. Kishi T, Ogawa T, Kobler RJ, Kuroda T, Tsutsumi M, Kawanabe M<\/u>. \u201cEvaluation of artifact removal for EEG-fMRI simultaneous measurements using a carbon-wire loop.\u201d Winter Workshop on Mechanism of Brain and Mind 2023<\/em>, Hokkaido, Japan, January 6, 2023.<\/li>\n<\/ol>\n

                            <\/a><\/p>\n

                            2022\u5e74<\/h3>\n

                            \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                              \n
                            1. Tamano R<\/u>, Ogawa T<\/u>, Katagiri A<\/u>, Cai C, Asai T, Kawanabe M<\/u>.
                              \n                              Event-related microstate dynamics represents working memory performance<\/a>
                              \nNeuroImage<\/em>, 263<\/strong>, November, 2022.<\/li>\n
                            2. Ogawa T<\/u>, Shimobayashi H<\/u>, Hirayama J-I<\/u>, Kawanabe M<\/u>.
                              \n                              Asymmetric directed functional connectivity within the frontoparietal motor network during motor imagery and execution<\/a>
                              \nNeuroImage<\/em>, 247<\/strong>, February 15, 2022.<\/li>\n<\/ol>\n

                              \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                \n
                              1. Kobler RJ<\/u>, Hirayama J-I<\/u>, Kawanabe M<\/u>
                                \n                                Controlling The Fr\u00e9chet Variance Improves Batch Normalization on the Symmetric Positive Definite Manifold.<\/a>
                                \nProc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, pp. 3863-3867, Singapore, 2022.<\/li>\n
                              2. Kobler RJ<\/u>, Hirayama J-I<\/u>, Zhao Q, Kawanabe M<\/u>
                                \n                                SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG .<\/a>
                                \nProc. Advances in Neural Information Processing Systems 35 (NeurIPS)<\/em>, New Orleans, 2022.<\/li>\n
                              3. Azuma D<\/u>, Miyanishi T<\/u>, Kurita S, Kawanabe M<\/u>
                                \n                                ScanQA: 3D Question Answering for Spatial Scene Understanding.<\/a>
                                \nProc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)<\/em>, pp.19129-19139, 2022.<\/li>\n
                              4. Hosoya H<\/u>. “CIGMO: Categorical invariant representations in a deep generative framework,” UAI, in Uncertainty in Artificial Intelligence (UAI), August, 2022.<\/li>\n<\/ol>\n

                                \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                  \n
                                1. Tamano R<\/u>, Ogawa T<\/u>, Katagiri A<\/u>, Cai C, Kawanabe M<\/u>. “Event-related dynamics of EEG microstate characterizes working memory function.”, NEURO2022<\/em>, Ginowan, Japan, June 30- July 3, 2022.<\/li>\n
                                2. *Ogawa T<\/u>. “Identification of brain regions associated with spatial insight problem solving.”, Technical Committee of CQ<\/em>, Kanazawa & online, Japan, Jan 27-28, 2022.<\/li>\n
                                3. Hosoya H<\/u>, Chen M, Freiwald W. “Multiplicative computation in face-selective neurons”, NEURO2022<\/em>, June 30-July 3, 2022.<\/li>\n<\/ol>\n

                                  <\/a><\/p>\n

                                  2021\u5e74<\/h3>\n

                                  \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                    \n
                                  1. Freiwald WA, Hosoya H<\/u>
                                    \n                                    Neuroscience: A Face’s Journey through Space and Time.<\/a>
                                    \nCurrent Biology<\/em>, Dispatch, 31<\/strong>(1), PR13-R15, 2021.<\/li>\n
                                  2. Miyanishi T<\/u>, Maekawa T<\/u>, Kawanabe M<\/u>
                                    \n                                    Sim2RealQA: Using Life Simulation to Solve Question Answering Real-World Events.<\/a>
                                    \nIEEE Access<\/em>, 9<\/strong>(1), pp.75003-75020, 14 May 2021.<\/li>\n
                                  3. Dissanayake T, Maekawa T<\/u>, Hara T, Miyanishi T<\/u>, Kawanabe M<\/u>
                                    \n                                    IndoLabel: predicting indoor location class by discovering location-specific sensor data motifs.<\/a>
                                    \nIEEE Sensors Journal<\/em>, 1<\/strong>(1), 06 August 2021.<\/li>\n<\/ol>\n

                                    \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                      \n
                                    1. Miyanishi T<\/u>, Kawanabe M<\/u>. “Watch, Listen, and Answer: Open-ended VideoQA with Modulated Multi-stream 3D ConvNets.”<\/a>, Proc. 29th European Signal Processing Conference 2021 (EUSIPCO 2021)<\/em>, 2021.<\/li>\n
                                    2. Hosoya H<\/u>. “CIGMO: Learning categorical invariant deep generative models from grouped data.”<\/a>, ICLR Workshop on Weakly Supervised Learning<\/em>, 2021.<\/li>\n<\/ol>\n

                                      \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                        \n
                                      1. Ogawa T<\/u>, Tamano R<\/u>, Cai C, Katagiri A<\/u>, Kawanabe M<\/u>. “Improvement of depressive symptoms conducting EEG-based neurofeedback with fMRI biomarker.”, The 44th Annual Meeting of JNSS<\/em>, Kobe, Japan, July 28-31, 2021.<\/li>\n
                                      2. Tamano R<\/u>, Ogawa T<\/u>, Cai C, Katagiri A<\/u>, Kawanabe M<\/u>. “EEG-based neurofeedback training informed by fMRI biomarker improves schizophrenia symptoms.”, The 44th Annual Meeting of JNS<\/em>, Kobe, Japan, July 28-31, 2021.<\/li>\n
                                      3. Ogawa T<\/u>, Takeuchi H, Ikeda S et al. “Connectome Prediction Model for representation of individual cognitive function.”, IEICE General Conference 2021<\/em>, Online, Japan, Mar 9-12, 2021.<\/li>\n
                                      4. *Ogawa T<\/u>. “Individual representation of creativity using large-scale brain dataset.”, Technical Committee of CQ<\/em>, Niigata & online, Japan, Jan 20-22, 2021 (*invited talk).<\/li>\n<\/ol>\n

                                        <\/a><\/p>\n

                                        2020\u5e74<\/h3>\n

                                        \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                          \n
                                        1. Aihara T, Shimokawa T, Ogawa T<\/u>, Okada Y, Ishikawa A, Inoue Y, Yamashita O
                                          \n                                          Resting-state functional connectivity estimated with hierarchical Bayesian diffuse optical tomography<\/a>
                                          \nFront Neurosci<\/em>, 31<\/strong>, 31 January 2020.<\/li>\n
                                        2. Monti R, Gibberd A, Roy S, Nunes M, Lorenz R, Leech R, Ogawa T<\/u>, Kawanabe M<\/u>, Hyvarinen A.
                                          \n                                          Interpretable brain age prediction using linear latent variable models of functional connectivity<\/a>
                                          \nPLOS ONE<\/em>, 15<\/strong>, (6):e0232296, Jun 10, 2020.<\/li>\n
                                        3. Raman R<\/u>, Hosoya H<\/u>.
                                          \n                                          Convolutional neural networks explain tuning properties of anterior, but not middle, face-processing areas in macaque inferotemporal cortex.<\/a>
                                          \nCommunications Biology<\/em>, 3<\/strong>, 221, 2020.<\/li>\n
                                        4. Li Y, Kanemura A<\/u>, Asoh H, Miyanishi T<\/u>, Kawanabe M<\/u>.
                                          \n                                          Multi-sensor integration for key-frame extraction from first-person videos.<\/a>
                                          \nIEEE Access<\/em>, 8<\/strong>, pp.122281\u2013122291, July 9, 2020.<\/li>\n<\/ol>\n

                                          \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                            \n
                                          1. Miyanishi T<\/u>, MaekawaT<\/u>, Kawanabe M<\/u>. “Two-Stream Spatiotemporal Compositional Attention Network for VideoQA.”<\/a>, Proc. 31st British Machine Vision Conference 2020 (BMVC 2020)<\/em>, September 2020.<\/li>\n<\/ol>\n

                                            \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                              \n
                                            1. Ogawa T<\/u>, Aihara T, Yamamshita O. “Identification of brain regions underlying spatial insight problem solving.”, SfNC2020<\/em>, Online, USA, Oct 22-23, 2020.<\/li>\n
                                            2. Ogawa T<\/u>, Tamano R<\/u>, Cai C, Katagiri A<\/u>, Kawanabe M<\/u>. “Estimation of brain biomarker states using EEG-fMRI simultaneous recordings and its application to EEG neurofeedback.”, 7th Japan Brain Machine Interface Symposium<\/em>, Online, Oct 3, 2020.<\/li>\n
                                            3. Tamano R<\/u>, Ogawa T<\/u>, Cai C, Kawanabe M<\/u>. “Towards using EEG-Neurofeedback for the treatment of psychotic symptoms and working memory in Schizophrenia: A feasibility study in healthy subjects.”, ECNP2020 <\/em>, Vienna (online), Austria, Sept 12-15, 2020.<\/li>\n
                                            4. Tamano R<\/u>, Ogawa T<\/u>, Cai C, Kawanabe M<\/u>. “Predicting of the schizophrenia classifier in EEG signals using dynamic functional connectivity: a simultaneous EEG-fMRI study in subclinical subjects.”, NPBPPP2020<\/em>, Sendai(online), Austria, Aug 21-23, 2020.<\/li>\n
                                            5. Tamano R<\/u>, Ogawa T<\/u>, Cai C, Kawanabe M<\/u>. “Predicting of the schizophrenia classifier in EEG signals using dynamic functional connectivity: a simultaneous EEG-fMRI study in subclinical subjects.”, The 43rd Annual Meeting of JNSS<\/em>, Kobe (online), Japan, Aug 21-23, 2020.<\/li>\n
                                            6. Ogawa T<\/u>. “Neuroscience of creativity: individual difference and brain dynamics.”, KANKO Online Exhibition 2021<\/em>, online, Japan, Nov 17th, 2020 (invited).<\/li>\n
                                            7. Ogawa T<\/u>. “Brain technology.”, NTT docomo 5G evolution & 6G Summit<\/em>, online, Japan, July 30th, 2020 (invited).<\/li>\n
                                            8. Ogawa T<\/u>. “Individual trait and brain dynamics associated with creative insight.”, The 43rd Annual Meeting of JNSS<\/em>, Kobe (online), Japan, July 29th – Aug 1st, 2020 (oral presentation, symposium organizer).<\/li>\n
                                            9. Ogawa T<\/u>. “Non-invasive Functional Brain Imaging and Its Application.”, Technical Committee on CQ (CQ)<\/em>, Tokyo, Japan, Jan 16th, 2020 (invited).<\/li>\n<\/ol>\n

                                              <\/a><\/p>\n

                                              2019\u5e74<\/h3>\n

                                              \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                              \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                \n
                                              1. Hosoya H<\/u>. “A deep generative model explaining tuning properties of monkey face processing patches.”, Computational Cognitive Neuroscience<\/em>, Sep, 2019.<\/li>\n
                                              2. Raman R<\/u>, Hosoya H<\/u>. “Does CNN Explain Tuning Properties of Face-Selective Neurons in Macaque IT?”, Computational Cognitive Neuroscience<\/em>, Sep, 2019.<\/li>\n
                                              3. Hosoya H<\/u>. “Group-based learning of disentangled representations with generalizability for novel contents.”, The International Joint Conference on Artificial Intelligence (IJCAI)<\/em>, Aug, 2019.<\/li>\n
                                              4. Tamano R<\/u>, Ogawa T<\/u>, Hirayama J<\/u>, Kawanabe M<\/u>. “Predicting schizophrenia-related functional connectivity from EEG using SPLICE filter: a statistical analysis with resting-state EEG-fMRI data.”, Real-time functional imaging and neurofeedback conference 2019 (rtfin2019)<\/em>, Maastricht, the Netherlands, and Aachen, Germany, Dec 7-11, 2019.<\/li>\n
                                              5. Ogawa T<\/u>, Moriya H, Hiroe N, Yamada T, Kawanabe M<\/u>, Hirayama J<\/u>. “Large-scale network estimation using SPLICE filter: an EEG-fMRI study.”, OHBM 2019<\/em>, Rome, Italy, June 9-13.<\/li>\n
                                              6. Zapf MP<\/u>, Kawanabe M<\/u>, Saiki LYM. “Pedestrian Density Prediction for Efficient Mobile Robot Exploration.”, 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)<\/em>, pp. 4615-4622, doi: 10.1109\/IROS40897.2019.8967763, 2019.<\/li>\n<\/ol>\n

                                                \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                  \n
                                                1. Ogawa T<\/u>, Moriya H, Hiroe N, Yamada T, Kawanabe M<\/u>, Hirayama J<\/u>. “Large-scale network estimation using SPLICE filter: an EEG-fMRI study.”, The 42nd Annual Meeting of JNSS<\/em>, Niigata, Japan, July 24-28.<\/li>\n
                                                2. Ogawa T<\/u>. “Large-scale Brain Network Associated with Motor-imagery\/execution: Using Neural Decoding and Causality Analysis.”, IEICE 15th Communication Behavior Engineering Seminar<\/em>, Tokyo, Japan, Jan 17th.<\/li>\n
                                                3. Ogawa T<\/u>. “Brain dynamics associated with creative insight.” 16th Communication Behavior Engineering Seminar<\/em>, Kobe, Japan, Sept 21st, 2019.<\/li>\n
                                                4. Ogawa T<\/u>. “What’s happened in our brain when we have Aha! experience?” JOEM Workshop’19<\/em>, Kizugawa, Japan, July 4th, 2019(invited).<\/li>\n<\/ol>\n

                                                  <\/a><\/p>\n

                                                  2018\u5e74<\/h3>\n

                                                  \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                    \n
                                                  1. Fuchigami T, Shikauchi Y, Nakae K, Shikauchi M, Ogawa T<\/u>, Ishii S
                                                    \n                                                    Zero-shot fMRI decoding with three-dimensional registration based on diffusion tensor imaging<\/a>
                                                    \nSci Rep.<\/em>, 8<\/strong>, 12342.<\/li>\n
                                                  2. Ogawa T<\/u>., Aihara T, Shimokawa T, Yamashita O
                                                    \n                                                    Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses<\/a>
                                                    \nSci Rep.<\/em>, 8<\/strong>, 6477.<\/li>\n<\/ol>\n

                                                    \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                      \n
                                                    1. Hoshino T, Kanoga S, Kanemura A<\/u>, Ogawa T<\/u>. “A No-Reference Metric of Cerebral Blood Flow Extraction for fNIRS Data.”, IEEE-SMC’18<\/em>, Miyazaki, Japan, Oct 7-10.<\/li>\n
                                                    2. Li Y, Kanemura A<\/u>, Asoh H, Miyanishi T<\/u>, Kawanabe M<\/u>. “Supervised saliency maps for first-person videos based on sparse coding.”, Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)<\/em>, Honolulu, Hawaii, USA, 2018.<\/li>\n
                                                    3. Miyanishi T<\/u>, Hirayama J<\/u>, Kanemura A<\/u>, Kawanabe M<\/u>. ” Answering Mixed Type Questions about Daily Living Episodes.”, The 27th International Joint Conference on Artificial Intelligence (IJCAI-18)<\/em>, Stockholm, Sweden, 2018.<\/li>\n
                                                    4. Zapf MP<\/u>, Gupta A<\/u>, Morales LM, Kawanabe M<\/u>. “Data-driven 3-D classification of person object relationships and semantic context clustering for robotics and AI applications”, Proc. 27th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)<\/em>, 2018.<\/li>\n
                                                    5. Li Y, Kanemura A<\/u>, Asoh H, Miyanishi T<\/u>, Kawanabe M<\/u>. “A sparse coding framework for gaze prediction in egocentric video.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)<\/em>, Calgary, Canada, 2018.<\/li>\n
                                                    6. Miyanishi T<\/u>, Hirayama J<\/u>, Maekawa T<\/u>, Kawanabe M<\/u>. “Generating an Event Timeline about Daily Activities from a Semantic Concept Stream.” Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)<\/em>, New Orleans, USA, 2018.<\/li>\n<\/ol>\n

                                                      \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                        \n
                                                      1. Ogawa T<\/u>. “Brain structure difference associated with internet addiction.”, \u7b2c14\u56de\u901a\u4fe1\u884c\u52d5\u5de5\u5b66\u7814\u7a76\u4f1a<\/em>, Nov 10th, 2018.<\/li>\n
                                                      2. Ogawa T<\/u>, Moriya H<\/u>, Yamada T, Kawanabe M<\/u>, Hirayama J<\/u>. “Extraction of EEG network components by using stacked pooling and linear components estimation.”, BIOMAG 2018<\/em>, Philadelphia, USA, Aug 26-30, 2018.<\/li>\n
                                                      3. Ogawa T<\/u>, Moriya H<\/u>, Yamada T, Kawanabe M<\/u>, Hirayama J<\/u>. “Extraction of network components from EEG signal: data-driven approach by using stacked pooling and linear components estimation.”, Neuroscience 2018<\/em>, Kobe, Japan, July 26-30, 2018.<\/li>\n
                                                      4. Hoshino T, Kanoga S, Kanemura A<\/u>, Ogawa T<\/u>. “Selecting artifactual independent Components from fNIRS Based on Decoding Analysis.”, IEEE EMBC’18<\/em>, Honolulu, USA, July 17-21, 2018.<\/li>\n
                                                      5. Hoshino T, Kanoga S, Kanemura A<\/u>, Ogawa T<\/u>. “Dictionary learning of fNIRS signals to examine scalp blood flow.”, OHBM2018<\/em>, Singapore, June 17-21, 2018.<\/li>\n
                                                      6. \u5ddd\u934b \u4e00\u6643<\/u>, \u5c71\u4e0b \u5b99\u4eba, \u68ee\u672c \u6df3. “\u4eba\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306eBMI\u6280\u8853”, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8a8c 2018\u5e741\u6708\u53f7 \u7279\u96c6\u300c\u8133\u60c5\u5831\u79d1\u5b66\u304c\u62d3\u304fAI\u3068ICT\u300d<\/em>, 59(1)<\/strong> 54-59, 2018.<\/li>\n
                                                      7. \u5c0f\u5ddd \u525b\u53f2<\/u>, \u76f8\u539f \u5b5d\u6b21, \u4e0b\u5ddd \u4e08\u660e, \u5c71\u4e0b \u5b99\u4eba. “\u3072\u3089\u3081\u304d\u306b\u95a2\u3059\u308b\u8133\u5185\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u500b\u4eba\u5dee”, \u7b2c13\u56de\u901a\u4fe1\u884c\u52d5\u5de5\u5b66\u7814\u7a76\u4f1a<\/em>, 2018.<\/li>\n<\/ol>\n

                                                        <\/a><\/p>\n

                                                        2017\u5e74<\/h3>\n

                                                        \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                          \n
                                                        1. Hosoya H<\/u>, Hyvarinen A<\/u>
                                                          \n                                                          A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing<\/a>
                                                          \nPLoS Comput Biol.<\/em>, 13(7)<\/strong>, e1005667, 2017.<\/li>\n
                                                        2. Samek W, Nakajima S, Kawanabe M<\/u>, Mueller KR
                                                          \n                                                          On robust parameter estimation in brain-computer interfacing<\/a>
                                                          \nJ Neural Eng.<\/em>, 14(6)<\/strong>, 061001. doi: 10.1088\/1741-2552\/aa8232.14, 2017.<\/li>\n
                                                        3. Aihara T, Ogawa T<\/u>, Shimokawa T, Yamashita O
                                                          \n                                                          Anodal transcranial direct current stimulation of the right anterior temporal lobe did not significantly affect verbal insight<\/a>
                                                          \nPLoS ONE<\/em> 12(9)<\/strong>, e0184749, 2017.<\/li>\n<\/ol>\n

                                                          \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                            \n
                                                          1. Li Y, Kanemura A<\/u>, Asoh H, Miyanishi T<\/u>, Kawanabe M<\/u>
                                                            \n                                                            Key frame extraction from first-person video with multi-sensor integration<\/a>
                                                            \nIEEE-ICME2017<\/em>, Hong Kong, China, 2017.<\/li>\n
                                                          2. Li Y, Kanemura A<\/u>, Asoh H, Miyanishi T<\/u>, Kawanabe M<\/u>
                                                            \n                                                            Extracting key frames from first-person videos in the common space of multiple sensors<\/a>
                                                            \nIEEE-ICIP2017<\/em>, pp.3993-3997, Beijing, China, 2017.<\/li>\n
                                                          3. Celikkanat H, Moriya H<\/u>, Ogawa T<\/u>, Kauppi JP, Kawanabe M<\/u>, Hyv\u00e4rinen A
                                                            \n                                                            Decoding emotional valence from electroencephalographic rhythmic activity<\/a>
                                                            \nIEEE-EMBC’17<\/em>, Jeju, Korea, July 11-15, 2017.<\/li>\n
                                                          4. Hirayama J<\/u>, Hyv\u00e4rinen A, Kawanabe M<\/u>. “SPLICE: Fully tractable hierarchical extension of ICA with pooling.” International Conference on Machine Learning (ICML2017)<\/em>, Sydney, Australia, 2017.<\/li>\n<\/ol>\n

                                                            \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                              \n
                                                            1. Hirayama J<\/u>, Hyvarinen A, Kiviniemi V, Kawanabe M<\/u>, Yamashita O, “Characterizing variability of brain connectivity with constrained principal component analysis,” Yamada Symposium 2017 on “Neuroimaging of Natural Behaviors”, Tokyo Tech., Tokyo, 2017 (invited).<\/li>\n
                                                            2. \u5ddd\u934b \u4e00\u6643<\/u>, \u5e73\u5c71 \u6df3\u4e00\u90ce<\/u>, Hyvaerinen A, Kiviniemi V, \u5c71\u4e0b \u5b99\u4eba, “\u5236\u7d04\u4ed8\u304d\u4e3b\u6210\u5206\u5206\u6790\u3092\u7528\u3044\u305f\u8133\u5185\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u7d50\u5408\u306e\u500b\u4eba\u5dee\u306e\u7279\u5fb4\u4ed8\u3051”, 2017\u5e74\u5ea6\u751f\u547d\u79d1\u5b66\u7cfb\u5b66\u4f1a\u5408\u540c\u5e74\u6b21\u5927\u4f1a (ConBio2017), \u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\uff1a\u300c\u500b\u6027\u300d\u5275\u767a\u795e\u7d4c\u57fa\u76e4\u306e\u7d71\u5408\u7684\u7406\u89e3\u306b\u5411\u3051\u305f\u968e\u5c64\u6a2a\u65ad\u7684\u89e3\u6790, \u795e\u6238\u30dd\u30fc\u30c8\u30a2\u30a4\u30e9\u30f3\u30c9\uff08\u5175\u5eab\u770c\uff09, 2017\uff08\u62db\u5f85\uff09.<\/li>\n
                                                            3. Ogawa T<\/u>, Moriya H<\/u>, Yamada T, Kawanabe M<\/u>, Hirayama J<\/u>. “Prediction of resting state fMRI signatures from EEG signal: a study of EEG-fMRI simultaneous recording.” rtfin2017, Nara, Japan, Nov 29, 2017.<\/li>\n
                                                            4. Hirayama J<\/u>, Ogawa T<\/u>, Moriya H<\/u>, Hyvarinen A, Kawanabe M<\/u>. “Exploring EEG source resting-state networks by SPLICE: A simultaneous fMRI study.” rtfin2017, Nara, Japan, Nov 29, 2017.<\/li>\n
                                                            5. Moriya H<\/u>, Ogawa T<\/u>, Kawanabe M<\/u>, Hirayama J<\/u>. “Predictability of amygdala BOLD signal from multiple-electrode EEGs.” rtfin2017, Nara, Japan, Nov 29, 2017.<\/li>\n
                                                            6. Ogawa T<\/u>, Aihara T, Shimokawa T, and Yamashita O. “Large-scale network associated with creative insight: Data-driven approach by using VBM-constrained resting-state functional connectivity analysis.” SfN 2017, Washington DC, USA, Nov 11-15, 2017.<\/li>\n
                                                            7. Ogawa T<\/u>, Aihara T, Shimokawa T, and Yamashita O. “Robust large-scale network associated to individual creative insight: VBM-constrained resting-state functional connectivity analysis.”, Neuroscience 2017, Chiba, Japan, July 20-23, 2017 .<\/li>\n<\/ol>\n

                                                              <\/a><\/p>\n

                                                              2016\u5e74<\/h3>\n

                                                              \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                                \n
                                                              1. Hosoya H<\/u>, Hyvarinen A
                                                                \n                                                                Learning visual spatial pooling by strong PCA dimension reduction<\/a>
                                                                \nNeural Comput.<\/em>,28(7)<\/strong>, 1249-64, 2016.<\/li>\n
                                                              2. Hirayama J<\/u>, Hyv\u00e4rinen A, Kiviniemi V, Kawanabe M<\/u>, Yamashita O.
                                                                \n                                                                Characterizing variability of modular brain connectivity with constrained principal component analysis<\/a>
                                                                \nPLOS ONE<\/em>, 11<\/strong>, e0168180, 2016.<\/li>\n
                                                              3. Hyv\u00e4rinen A, Hirayama J<\/u>, Kiviniemi V, Kawanabe M<\/u>.
                                                                \n                                                                Orthogonal connectivity factorization: Interpretable decomposition of variability in correlation matrices<\/a>
                                                                \nNeural Computation<\/em>, 28<\/strong>, pp.445-484, 2016.<\/li>\n<\/ol>\n

                                                                \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                                  \n
                                                                1. Miyanishi T<\/u>, Hirayama J<\/u>, Kong Q, Maekawa T<\/u>, Moriya H<\/u>, Suyama T<\/u>
                                                                  \nEgocentric video search via physical interactions
                                                                  \n30th AAAI Conference on Artificial Intelligence(AAAI2016)<\/em>, Phoenix, USA, 2016.2.12-2.17.<\/li>\n<\/ol>\n

                                                                  \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                                    \n
                                                                  1. \u5bae\u897f \u5927\u6a39<\/u>,\u5e73\u5c71 \u6df3\u4e00\u90ce<\/u>,\u524d\u5ddd \u5353\u4e5f<\/u>,\u5b54 \u5168,\u5b88\u8c37 \u5927\u6a39<\/u>,\u9808\u5c71 \u656c\u4e4b<\/u>,\u201c\u74b0\u5883\u3068\u306e\u76f8\u4e92\u4f5c\u7528\u3092\u7528\u3044\u305f\u4e00\u4eba\u79f0\u8996\u70b9\u6620\u50cf\u306e\u691c\u7d22\u201d,\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c78\u56de\u5168\u56fd\u5927\u4f1a, \u795e\u5948\u5ddd\u770c, 2016.<\/li>\n
                                                                  2. \u5b88\u8c37 \u5927\u6a39<\/u>, \u201c\u6a5f\u68b0\u5b66\u7fd2\u3092\u5229\u7528\u3057\u305f\u60c5\u52d5\u306e\u5fc3\u7406\u751f\u7406\u5b66\u7814\u7a76\u201d, \u7b2c34\u56de\u65e5\u672c\u751f\u7406\u5fc3\u7406\u5b66\u4f1a\u5927\u4f1a, \u611b\u77e5\u770c, 2016.<\/li>\n
                                                                  3. Hyvarinen A, Hirayama J<\/u>, Kiviniemi V, Kawanabe M<\/u>, “Analysing non-stationarity by a new matrix decomposition method,” OHBM2016, Geneva, Switzerland, 2016.<\/li>\n<\/ol>\n

                                                                    <\/a><\/p>\n

                                                                    2015\u5e74<\/h3>\n

                                                                    \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                                      \n
                                                                    1. Morioka H<\/u>, Kanemura A<\/u>, Hirayama J<\/u>, Shikauchi M<\/u>, Ogawa T<\/u>, Ikeda S<\/u>, Kawanabe M<\/u>, Ishii S<\/u>
                                                                      \n                                                                      Learning a common dictionary for subject-transfer decoding with resting calibration<\/a>
                                                                      \nNeuroImage<\/em>, 111<\/strong>, 167-178, 2015.<\/li>\n
                                                                    2. Singh AK<\/u>, Asoh H, Takeda Y, Phillips S
                                                                      \n                                                                      Statistical detection of EEG synchrony using empirical bayesian inference<\/a>
                                                                      \nPLoS ONE<\/em>, 10(3)<\/strong>, e0121795, 2015<\/li>\n
                                                                    3. Hirayam J<\/u>, Ogawa T<\/u>, Hyvarinen A
                                                                      \n                                                                      Unifying Blind Separation and Clustering for Resting-State EEG\/MEG Functional Connectivity Analysis<\/a>
                                                                      \nNeural Comput<\/em>, 27(7)<\/strong>, 1373-404, 2015.<\/li>\n
                                                                    4. Ugur E, Nagai Y, Sahin E, Oztop E<\/u>
                                                                      \n                                                                      Staged development of robot skills: Behavior formation, affordance learning and imitation with motionese<\/a>
                                                                      \nTransactions on Autonomous Mental Development<\/em>, 2015.<\/li>\n
                                                                    5. Hosoya H<\/u>, Hyvarinen A
                                                                      \n                                                                      A hierarchical statistical model of natural images explains tuning properties in V2<\/a>
                                                                      \nJ Neurosci<\/em>, 35(29)<\/strong>, 10412-10428, 2015<\/li>\n<\/ol>\n

                                                                      \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                                        \n
                                                                      1. Ogawa T<\/u>, Hirayama J<\/u>, Gupta P<\/u>, Moriya H<\/u>, Yamaguchi S, Ishikawa A, Inoue Y, Kawanabe M<\/u>, Ishii S<\/u>
                                                                        \n                                                                        “Brain-machine interfaces for assistive smart homes: a feasibility study with wearable near-infrared spectroscopy”<\/a>
                                                                        \nIEEE-EMBC’15<\/em>, Milan, Italy, 2015.<\/li>\n<\/ol>\n

                                                                        \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                                          \n
                                                                        1. Ishii S<\/u>. \u201cData-driven brain computer interface in real environments\u201d, 3rd International Winter Conference on Brain-Computer Interface 2015, invited (High1 Resort, Korea), 2015.<\/li>\n
                                                                        2. Ishii S<\/u>. \u201cData-driven brain decoding techniques\u201d, 10th AEARU Workshop on Computer Science and Web Technology 2015, Tsukuba University, invited (\u7b51\u6ce2\u5e02\u3001\u8328\u57ce\u770c), 2015.<\/li>\n
                                                                        3. \u5b88\u8c37 \u5927\u6a39<\/u>, \u9e7f\u5185 \u5b66<\/u>, \u5e73\u5c71 \u6df3\u4e00\u90ce<\/u>, \u5c0f\u5ddd \u525b\u53f2<\/u>, \u77f3\u4e95 \u4fe1<\/u>. \u201c\u96fb\u6c17\u751f\u7406\u5b66\u7684\u6307\u6a19\u3092\u7528\u3044\u305f\u60c5\u52d5\u8b58\u5225\u306e\u6bd4\u8f03\u201d, \u7b2c33\u56de \u65e5\u672c\u751f\u7406\u5fc3\u7406\u5b66\u4f1a\u5927\u4f1a, \u5927\u962a\u5e9c, 2015.<\/li>\n
                                                                        4. \u5c0f\u5ddd \u525b\u53f2<\/u>. \u201c\u5b9f\u751f\u6d3b\u7a7a\u9593\u306b\u5e83\u304c\u308bBMI\u6280\u8853\u3068\u305d\u306e\u5fdc\u7528\u201d, \u65e5\u672c\u8a8d\u77e5\u5fc3\u7406\u5b66\u4f1a\u7b2c13\u56de\u5927\u4f1a, \u6771\u4eac\u90fd, 2015 (invited).<\/li>\n
                                                                        5. Kanemura A<\/u>. \u201cMeasuring unconstrained human activities in daily life\u201d, \u7b2c6\u56de\u65b0\u6f5f\u5927\u5b66\u8133\u7814\u7a76\u6240\u5171\u540c\u7814\u7a76\u62e0\u70b9\u56fd\u969b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u65b0\u6f5f\u770c, 2015.<\/li>\n
                                                                        6. Hosoya H<\/u>. \u201cUnderstanding representations in visual cortex with hierarchical statistical models of natural images\u201d, \u7b2c6\u56de\u65b0\u6f5f\u5927\u5b66\u8133\u7814\u7a76\u6240\u5171\u540c\u7814\u7a76\u62e0\u70b9\u56fd\u969b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u65b0\u6f5f\u770c, 2015.<\/li>\n
                                                                        7. Kong Q<\/u>, Maekawa T<\/u>, Miyanishi T<\/u>, Suyama T<\/u>. \u201cSelection method for Electric appliances based on the context using GoogleGlass\u201d, \u7b2c47\u56de\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u30e6\u30d3\u30ad\u30bf\u30b9\u30b3\u30f3\u30d4\u30e5\u30fc\u30b7\u30f3\u30b0\u30b7\u30b9\u30c6\u30e0\u7814\u7a76\u4f1a, 2015-UBI-47(21)<\/strong>, 1-8, \u5927\u962a\u5e9c, 2015.<\/li>\n
                                                                        8. Yano K<\/u>. \u201cBuilding dense 3D maps of indoor environments from kinect RGB-D images\u201d, \u7b2c18\u56de\u753b\u50cf\u306e\u8a8d\u8b58\u30fb\u7406\u89e3\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u5927\u962a\u5e9c, 2015.<\/li>\n
                                                                        9. Ogawa T<\/u>, Hirayama J<\/u>, Gupta P<\/u>, Abdur-Rahim J<\/u>, Moriya H<\/u>, Yano K<\/u>, Kawanabe M<\/u>, Ishii S<\/u>., \u201cAn application of NIRS-based brain machine interface in the realistic environment: supporting appliance control with online single-trial decoding\u201d, Neurosience2015, Kobe, 2015.<\/li>\n
                                                                        10. Pehlivan AB, Oztop E<\/u>. “A comparison of dynamic movement primitives with hidden markov models in human motion recognition,” 17th International Conference on Advanced Robotics (ICAR2015), Istanbul, Turkey, 2015.<\/li>\n
                                                                        11. Panknin D, von Buenau P, Kawanabe M<\/u>, Meinecke F, Mueller KR. “Higher order stationary subspace analysis,” Journal of Physics: Conference Series,International Meeting on High-Dimensional Data-Driven Science (HD3-2015), 699(012021)<\/strong>, 2015.<\/li>\n
                                                                        12. Kawanabe M<\/u>. \u201cOn possibilities and difficulties in adaptive brain-computer interface in real environments\u201d,Germany-Japan Adaptive BCI Workshop, \u4eac\u90fd\u5927\u5b66 (2015.10.28-10.29)<\/li>\n
                                                                        13. Hosoya H<\/u>, Hyvarinen A. \u201cHierarchical sparse coding model and shape representation in V4\u201d, SfN 2015, Chicago, USA, 2015.<\/li>\n<\/ol>\n

                                                                          <\/a><\/p>\n

                                                                          2014\u5e74<\/h3>\n

                                                                          \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                                            \n
                                                                          1. Kawanabe M<\/u>, Samek W, Mueller KR, Vidaure C.
                                                                            \n                                                                            Robust common spatial filters with a maxmin approach<\/a>
                                                                            \nNeural Comput.<\/em>, 26(2)<\/strong>, 349-76, 2014.<\/li>\n
                                                                          2. \u7af9\u5185 \u4ea8\u3001\u5742\u91ce \u907c\u5e73\u3001\u99ac\u8d8a \u5065\u6cbb\u3001\u517c\u6751 \u539a\u7bc4<\/u>\u3001\u5ddd\u934b \u4e00\u6643<\/u>\u3001\u5ddd\u91ce \u54f2\u751f\u3001\u795e\u6797 \u9686\u3001\u6b66\u672c \u5145\u6cbb\u3001\u677e\u5c3e \u771f\u4eba\u3001\u67ff\u6cbc \u9686\u99ac
                                                                            \n\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u30d9\u30fc\u30b9\u5206\u6563\u51e6\u7406\u57fa\u76e4\u306e\u63d0\u6848\u3068BMI\u5fdc\u7528\u30b5\u30fc\u30d3\u30b9\u3078\u306e\u9069\u7528\u306b\u3088\u308b\u8a55\u4fa1
                                                                            \n\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c<\/em>, 55(2)<\/strong>, 681-694, 2014.<\/li>\n
                                                                          3. Morioka H<\/u>, Kanemura A<\/u>, Morimoto S<\/u>, Yoshioka T, Oba S, Kawanabe M<\/u>, Ishii S<\/u>
                                                                            \n                                                                            Decoding spatial attention by using cortical currents estimated from electroencephalography with near-infrared spectroscopy prior information<\/a>
                                                                            \nNeuroImage<\/em>, 90<\/strong>, 128-139, 2014.<\/li>\n
                                                                          4. \u5e73\u5c71 \u6df3\u4e00\u90ce\u3001\u77f3\u4e95\u4fe1\u3001\u201c\u6f5c\u5728\u7a7a\u9593\u30e2\u30c7\u30ea\u30f3\u30b0\u306b\u3088\u308b\u6642\u7cfb\u5217\u304b\u3089\u306e\u518d\u69cb\u6210\u201d, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8a8c Vol.97, No.5, pp.399-404 (2014.5.1)<\/li>\n
                                                                          5. Ugur, E., Nagai, Y., Celikkant, H., Oztop, E., \u201cParental scaffolding as a bootstrapping mechanism for learning grasp affordances and imitation skills\u201d, Robotica DOI:10.1017\/S0263574714002148 (2014.8.19)<\/li>\n
                                                                          6. Ahamed T<\/u>, Kawanabe M<\/u>, Ishii S<\/u>, Callan D.
                                                                            \n                                                                            Structural differences in gray matter between glider pilots and non-pilots. A voxel based morphometry study<\/a>
                                                                            \nFrontiers in Neurology<\/em>, 35<\/strong>(29), fneur.2014.00248, 2014.<\/li>\n<\/ol>\n

                                                                            \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                                              \n
                                                                            1. Hosoya H<\/u>, Hyvarinen A
                                                                              \nFour-layer sparse coding model of natural images that reproduces tuning properties in V1, V2 and V4
                                                                              \nComputational and Systems Neuroscience<\/em>, 145, II-77, Salt Lake City, USA, Feb 27-Mar 2, 2014.<\/li>\n
                                                                            2. Samek W, Mueller,KR, Kawanabe M<\/u>
                                                                              \nRobust common spatial patterns by minimum divergence covariance estimator
                                                                              \nICASSP2014<\/em>, 2059-2062, Florence, Italy, May 4-9, 2014.<\/li>\n
                                                                            3. Hirayama J<\/u>, Ogawa T<\/u>, Hyvarinen A
                                                                              \nSimultaneous blind separation and clustering of coactivated EEG\/MEG sources for analyzing spontaneous
                                                                              \nIEEE-EMBC 2014<\/em>, Chicago, USA, Aug 26-30, 2014.<\/li>\n
                                                                            4. Morales-Saiki LY, Abdur-Rahim JA<\/u>, Even J, Watanabe A, Kondo T, Hagita N, Ogawa T<\/u>, Ishii S<\/u>
                                                                              \nModeling of Human Velocity Habituation for Robotic Wheelchair
                                                                              \nIEEE\/RAS International Conference on Humanoid Robots<\/em>, Madrid, Spain, Sept 14-18, 2014.<\/li>\n
                                                                            5. Abdur-Rahim JA<\/u>, Ogawa T<\/u>, Hirayama J<\/u>, Ishii S<\/u>
                                                                              \nDatabase-driven artifact detection method for EEG systems with few channels
                                                                              \nIEEE Biomedical Circuits and Systems Conference<\/em>, 5-7, Lausanne, Switzerland, Oct 22-24, 2014.<\/li>\n<\/ol>\n

                                                                              \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                                                \n
                                                                              1. Kawanabe M<\/u>, \u201cRobust feature construction against non-stationarity for EEG-BMI decoders\u201d, 2nd International Winter Workshop on Brain-Computer Interface, High1 Resort, Korea, Feg 17-19, 2014.(invited)<\/li>\n
                                                                              2. \u77f3\u4e95 \u4fe1\u3001\u201c\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306b\u57fa\u3065\u304f\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u201d\u3001\u7b2c37\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a\u30b5\u30c6\u30e9\u30a4\u30c8\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0 \u300c\u8133\u60c5\u5831\u306e\u7523\u696d\u5fdc\u7528\u306b\u5411\u3051\u305f\u52d5\u5411\u3068\u793e\u4f1a\u57fa\u76e4\u6574\u5099\u300d(\u6a2a\u6d5c\u5e02\u3001\u795e\u5948\u5ddd\u770c)\u3000(2014.9.10)<\/li>\n
                                                                              3. Ogawa,T., Gupta, P., Abdur-Rahim, J.A., Yano, K., Morioka, H., Hirayama, J., Yamaguchi, S., Ishikawa, A., Inoue, Y., Kawanabe, M., Ishii, S., \u201cDecoding daily-life behavioral signatures in the real environment: portable NIRS signal using behavior labels\u201d, \u7b2c37\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a (\u6a2a\u6d5c\u5e02\u3001\u795e\u5948\u5ddd\u770c) (2014.9.11-9.13)<\/li>\n
                                                                              4. Abdur-Rahim, J.A., Ogawa, T., Kawanabe, M., Ishii, S., \u201cExploring the role of eye blinking in terms of attention\/arousal: a method to quantify a person’s mental\u201d, \u7b2c37\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a (\u6a2a\u6d5c\u5e02\u3001\u795e\u5948\u5ddd\u770c) (2014.9.11-9.13)<\/li>\n
                                                                              5. Morioka, H., Kanemura, K., Hirayama, J., Shikauchi, M., Ogawa, T., Ikeda, S., Kawanabe, M., Ishii, S., \u201cSubject-independent BMI through sparse learning of spatial bases common across sessions and subjects\u201d, \u7b2c37\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a (\u6a2a\u6d5c\u5e02\u3001\u795e\u5948\u5ddd\u770c) (2014.9.11-9.13)<\/li>\n
                                                                              6. Morioka, H., Kanemura, A., Hirayama, J., Ogawa, T., Ikeda, S., Kawanabe, M., Ishii, S, \u201cSubject-independent decoding from EEG through sparse learning of spatial bases common across sessions and subjects\u201d, Advance in Neuroinformatics 2014 (Wako, Saitama) (2014.9.25-9.26)<\/li>\n
                                                                              7. Ogawa, T., Gupta, P., Yano, K., Abdur-Rahim, J. A., Morioka, H., Hirayama, J., Yamaguchi, S., Ishikawa, A., Inoue, Y., Kawanabe, M., Ishii, S., \u201cDecoding daily behaviors from NIRS signatures by using a portable NIRS device in the daily-life\u201d, Neuroscience 2014, Washington DC, USA, 2014.11.15-11.19.<\/li>\n
                                                                              8. Hyvarinen, A., Hirayama, J., Kawanabe, M., “Dynamic Connectirity Factorization: Interpretable decompositions of non-stationarity,” Proc. 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI2014), 4 pp., Tuebingen, Germany, 2014.<\/li>\n<\/ol>\n

                                                                                <\/a><\/p>\n

                                                                                2013\u5e74<\/h3>\n

                                                                                \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                                                  \n
                                                                                1. Oztop E<\/u>, Kawato M, Arbib MA
                                                                                  \n                                                                                  Mirror neurons: functions, mechanisms and models<\/a>
                                                                                  \nNeuroscience Letters<\/em>, 540<\/b>, 43-55, 2013.<\/li>\n
                                                                                2. Samek W, Kawanabe M<\/u>, Mueller KR
                                                                                  \n                                                                                  Divergence-based Framework for Common Spatial Patterns Algorithms<\/a>
                                                                                  \nIEEE Rev Biomed Eng<\/em>, 7<\/b>, 50-72, 2013.<\/li>\n<\/ol>\n

                                                                                  \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                                                    \n
                                                                                  1. Singh A<\/u>, Ogawa T<\/u>, Hirayama J<\/u>, Maruyama M<\/u>, Kawanabe M<\/u>, Ishii S<\/u>
                                                                                    \nSpatio-temporal and cortical characterization of EEG changes during motor imagery
                                                                                    \n6th Congress of Neuroinformatics<\/em>, 150-151, Stockholm, Sweden, Aug 27-29, 2013.<\/li>\n
                                                                                  2. Kanemura A<\/u>, Morales-Saiki LY, Kawanabe M<\/u>, Morioka H<\/u>, Kallakuri N, Ikeda T, Miyashita T, Hagita N, Ishii S<\/u>
                                                                                    \nA waypoint-based framework in brain-controlled smart home environments: brain interfaces, domotics, and robotics integration
                                                                                    \nIEEE\/RSJ International Conference on Intelligent Robots and Systems<\/em>, Tokyo, Nov 3-7, 2013.<\/li>\n
                                                                                  3. Samek W, Blythe D, Mueller KR, Kawanabe M<\/u>
                                                                                    \nRobust spatial filtering with beta divergence
                                                                                    \nProc. Neural Information Processing Systems (NIPS2013)<\/em>, 9<\/b>, Lake Tahoe, USA, 2013.<\/li>\n<\/ol>\n

                                                                                    \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                                                      \n
                                                                                    1. Ugur, E., \u201cUnsupervised discovery of actions and action possibilities\u201d, Mechanisms of Ongoing Development in Cognitive Robotics (Wadern, Germany) (2013.2.10-2.15)<\/li>\n
                                                                                    2. Ishii, S., \u201cNetwork-based BMI: toward brain machine interface in real environments\u201d, Multimodal Neuroimaging Workshop, UCLA IPAM, invited (Los Angeles, USA) (2013.3.04-3.08)<\/li>\n
                                                                                    3. Morishige, K., Yoshioka, T., Ishii, S., Sato, M., Kawato, M., \u201cSource separation of cortical and extra-brain source activities in real MEG data during covert pursuit eye movement\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c) (2013.6.20-6.23)<\/li>\n
                                                                                    4. Hirayama, J., Shikauchi, Y., Nakamura, Y., Maeda, S., Takenouchi, T., Kanemura, A., Kawanabe, M., Ishii, S., \u201cDecoding hand movements in everyday activities actions from magnetoencephalography\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c)\u3000(2013.6.20-6.23)<\/li>\n
                                                                                    5. Ogawa, T., Azuma, Y., Ishii, S., \u201cChange of brain activity effect from motor imagery training: application for EEG-based brain machine interface\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c) (2013.6.20-6.23)<\/li>\n
                                                                                    6. Singh, A., Ogawa, T., Yoshioka, T., Hirayama, J., Maruyama, M., Kawanabe, M., Ishii, S., \u201cEvent related dynamics of EEG oscillations in cued motor imagery\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c)\u3000(2013.6.20-6.23)<\/li>\n
                                                                                    7. Hosoya, H., Sasaki, K., Ohzawa, I., \u201cEstimating invariant dimensions in V2\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c)\u3000(2013.6.20-6.23)<\/li>\n
                                                                                    8. Ishido, N., Morimoto, S., Kanemura, A., Maruyama, M., Kawanabe, M., Ishii, S., Saruwatari, H., Shikano, K., \u201cAn auditory ERP-based BMI for a universal controller in a real environment\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c)\u3000(2013.6.20-6.23)<\/li>\n
                                                                                    9. Shikauchi, Y., Ishii, S., \u201cDecoding scene prediction associated with decision making\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c)\u3000(2013.6.20-6.23)<\/li>\n
                                                                                    10. Morioka, H., Kanemura, A., Morimoto, S., Yoshioka, T., Kawanabe, M., Ishii, S., \u201cDecoding of spatial attention from cortical currents estimated from EEG with NIRS prior\u201d, \u7b2c36\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a,\u7b2c56\u56de\u65e5\u672c\u795e\u7d4c\u5316\u5b66\u4f1a\u5927\u4f1a,\u7b2c23\u56de\u65e5\u672c\u795e\u7d4c\u56de\u8def\u5b66\u4f1a\u5927\u4f1a \u5408\u540c\u5927\u4f1a (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c)\u3000(2013.6.20-6.23)<\/li>\n
                                                                                    11. Ishii, S., \u201cBrain machine interface and decoding in mobile environments\u201d, Modeling Neural Activity: Statistics, Dynamical Systems, and Networks, invited (Hawaii USA) (2013.6.26-6.28)<\/li>\n
                                                                                    12. Shikauchi, Y., Ishii, S., \u201cPrediction was predictable from human brain activity in fronto-parietal cortex\u201d, Computational Neuroscience Meeting (Paris, France) (2013.7.13-7.18)<\/li>\n
                                                                                    13. \u77f3\u5802\u3000\u306a\u3064\u307f\u3001\u5c0f\u5ddd\u3000\u525b\u53f2\u3001 \u68ee\u672c\u3000\u667a\u5fd7\u3001 \u517c\u6751\u3000\u539a\u7bc4\u3001 \u4e38\u5c71\u3000\u96c5\u7d00\u3001 \u5ddd\u934b\u3000\u4e00\u6643\u3001 \u77f3\u4e95\u3000\u4fe1\u3001 \u733f\u6e21\u3000\u6d0b\u3001 \u9e7f\u91ce\u3000\u6e05\u5f18\u3001 \u4e2d\u6751\u3000\u54f2\u3001 \u201c\u8074\u899a\u6ce8\u610f\u3092\u7528\u3044\u305f\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u306b\u95a2\u3059\u308b\u57fa\u790e\u691c\u8a0e\u201d\u3001 \u5fdc\u7528\u97f3\u97ff\u7814\u7a76\u4f1a\u3001\u5317\u6d77\u9053\u533b\u7642\u5927\u5b66 (\u77f3\u72e9\u90e1\u3001\u5317\u6d77\u9053) (2013.7.18-7.19)<\/li>\n
                                                                                    14. \u9e7f\u5185\u3000\u5b66\u3001\u6c34\u539f\u3000\u5553\u6681\u3001 \u201c\u76f8\u624b\u306e\u975e\u5354\u8abf\u6027\u306b\u95a2\u308f\u308b\u8133\u6d3b\u52d5\u306b\u3088\u308a\u5909\u5316\u3059\u308b\u5831\u916c\u7cfb\u9818\u91ce\u9593\u306e\u60c5\u5831\u4f1d\u9054\u201d\u3001 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u30cb\u30e5\u30fc\u30ed\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u7814\u7a76\u4f1a\u3000\u5fb3\u5cf6\u5927\u5b66 (\u5fb3\u5cf6\u5e02\u3001\u5fb3\u5cf6\u770c)\u3000(2013.7.19-7.20)<\/li>\n
                                                                                    15. Kawanabe, M., Abdur-Rahim, J. A., \u5742\u91ce \u907c\u5e73, \u7af9\u5185 \u4ea8,\u3000\u795e\u6797 \u9686, \u6b66\u672c\u5145\u6cbb, \u201cNovel and innovative R&D making use of brain structures\u201d, 37th Annual International Computer Software & Applications Conference (COMPSAC2013), (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c) (2013.7.22-7.26)<\/li>\n
                                                                                    16. Maruyama, M., \u201cIntegration of reward and pain in pavlovian and instrumental decision-making\u201d, 8th Congress of the European Federation of IASP Chapters (Florence, Italy) (2013.10.9-10.12)<\/li>\n
                                                                                    17. Kawanabe, M., Kanemura, A., Morales-Saiki, L. Y., Morioka, H., Kallakuri, N., Ikeda, T., Miyashita, T., Hagita,N., Ishii, S., \u201cA Waypoint-based Framework and Data-driven Decoder for Brain-Machine Interface in Smart Home Environments\u201d, IEEE\/RSJ International Conference on Intelligent Robots and Systems, invited, Tokyo Big Site, (Koto-ku, Tokyo) (2013.11.3-11.8)<\/li>\n
                                                                                    18. Shikauchi, M., Mizuhara, H., \u201cBrain activity by selfish partner dynamically modulates the reward-related cortical network\u201d, Neuroscience 2013, San Diego, USA, Nov, 2013<\/li>\n
                                                                                    19. \u690d\u91ce \u525b, \u524d\u7530 \u65b0\u4e00, \u5ddd\u934b \u4e00\u6643, “\u7d71\u8a08\u5b66\u306e\u89b3\u70b9\u304b\u3089\u898b\u305fTD\u5b66\u7fd2”, \u8a08\u6e2c\u3068\u5236\u5fa1\u3001\u30ea\u30ec\u30fc\u89e3\u8aac\u300c\u5f37\u5316\u5b66\u7fd2\u306e\u6700\u8fd1\u306e\u767a\u5c55\u300d, 52(3):277-283, 2013.<\/li>\n<\/ol>\n

                                                                                      <\/a><\/p>\n

                                                                                      2012\u5e74<\/h3>\n

                                                                                      \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                                                        \n
                                                                                      1. Samek W, Vidaurre C, M\u00fcller KR, Kawanabe M<\/u>
                                                                                        \nStationary common spatial patterns for brain-computer interfacing
                                                                                        \nJ Neural Eng<\/em>, 9(2)<\/b>, 026013, 2012.<\/li>\n
                                                                                      2. Binder A, Nakajima S, Kloft M, M\u00fcller C, Samek W, Brefeld U, M\u00fcller KR, Kawanabe M<\/u>
                                                                                        \nInsights from classifying visual concepts with multiple kernel learning
                                                                                        \nPLoS ONE<\/em>, 7(8)<\/b>, e38897, 2012.<\/li>\n
                                                                                      3. Binder A, Samek W, M\u00fcller KR, Kawanabe M<\/u>
                                                                                        \nEnhanced representation and multi-task learning for image annotation
                                                                                        \nComputer Vision and Image Understanding<\/em>, 117(5)<\/b>, 466-478, 2012.<\/li>\n<\/ol>\n

                                                                                        \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                                                          \n
                                                                                        1. Samek W, M\u00fcller KR, Kawanabe M<\/u>, Vidaurre V
                                                                                          \nBrain-Computer Interfacing in discriminative and stationary subspaces
                                                                                          \nIEEE-EMBC2012<\/em>, 4<\/b>, San Diego, USA, 2012.<\/li>\n
                                                                                        2. Ugur E<\/u>
                                                                                          \nSelf-discovery of motor primitives and learning grasp affordances
                                                                                          \nIEEE\/RSJ International Conference on Intelligent Robots and Systems<\/em>, 3260-3267, Vilamoura, Portugal, Oct 7-12, 2012.<\/li>\n<\/ol>\n

                                                                                          \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                                                            \n
                                                                                          1. Ishii S<\/u>, \u201cToward brain machine interface in real environments\u201d, 4th International Symposium on Brain and Cognitive Engineering, Seoul, Korea, May 31-Jun 1, 2012 (invited).<\/li>\n
                                                                                          2. Fukushima M, Yamashita O, Kanemura A<\/u>, Ishii S<\/u>, Kawato M, Sato M, \u201cA state-space modeling approach for reconstructing the spatially focal and temporally smooth current sources using the spatially inhomogeneous dynamical model\u201d, BIOMAG 2018, Paris, France, Aug 28, 2012.<\/li>\n
                                                                                          3. Kawanabe M<\/u>, “Challenges towards brain-machine interfaces for supporting elderly and disabled people in daily life,” Beriln Brain-Computer Interface(BBCI) Workshop 2012 on Advances in Neurotechnology, Berlin, Germany, 2012 (invited).<\/li>\n
                                                                                          4. Singh AK<\/u>, Takeda Y, Asho H, Philiips S, \u201cEmpirical bayes inference for analyzing functional connectivity from EEG data\u201d, Neuroscience 2012<\/em>, Nagoya, Japan, Sept 18-21, 2012.<\/li>\n
                                                                                          5. Ishii S<\/u>, \u201cToward brain machine interface in real environment\u201d, Neuroscience 2012<\/em>, Nagoya, Japan, Sept 18-21, 2012.<\/li>\n
                                                                                          6. \u517c\u6751 \u539a\u7bc4<\/u>, \u201c\u7d71\u8a08\u7684\u753b\u50cf\u51e6\u7406\u306b\u304a\u3051\u308b\u30e2\u30c7\u30ea\u30f3\u30b0\u306e\u65b9\u5411\u6027\u306b\u3064\u3044\u3066\u201d, \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a \u7b2c87\u56de \u4eba\u5de5\u77e5\u80fd\u57fa\u672c\u554f\u984c\u7814\u7a76\u4f1a<\/em>, 25, \u6176\u61c9\u5927\u5b66\u65e5\u5409\uff77\uff6c\uff9d\uff8a\uff9f\uff7d, \u6a2a\u6d5c\u5e02, \u795e\u5948\u5ddd\u770c, Nov 17, 2012.<\/li>\n<\/ol>\n

                                                                                            <\/a><\/p>\n

                                                                                            2011\u5e74<\/h3>\n

                                                                                            \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles<\/p>\n

                                                                                            \u67fb\u8aad\u4ed8\u304d\u53e3\u982d\u767a\u8868\u8ad6\u6587\/Reviewed presentations<\/p>\n

                                                                                            \u305d\u306e\u4ed6\u5b66\u8853\u767a\u8868\/Other academic presentations<\/p>\n

                                                                                              \n
                                                                                            1. \u77f3\u4e95 \u4fe1\u3001\u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u793e\u4f1a\u306e\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9\u201d\u3001 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u901a\u4fe1\u30bd\u30b5\u30a4\u30a8\u30c6\u30a3\u7dcf\u4f1a\u3000\u62db\u5f85\u8b1b\u6f14\u3001\u5317\u6d77\u9053\u5927\u5b66 (\u672d\u5e4c\u5e02\u3001\u5317\u6d77\u9053) (2011.09.13-9.16)<\/li>\n
                                                                                            2. \u77f3\u4e95 \u4fe1\u3001\u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9\u306b\u5411\u3051\u3066\u201d\u3001 \u7b2c34\u56de\u65e5\u672c\u795e\u7d4c\u79d1\u5b66\u5927\u4f1a (\u6a2a\u6d5c\u5e02\u3001\u795e\u5948\u5ddd\u770c) (2011.9.14-9.17)<\/li>\n<\/ol>\n

                                                                                              <\/a><\/p>\n

                                                                                              \u305d\u306e\u4ed6\/Other<\/h3>\n

                                                                                              \u305d\u306e\u4ed6\u767a\u8868\/Other presentations<\/p>\n

                                                                                                \n
                                                                                              1. \u5ddd\u934b\u3000\u4e00\u6643, \u300c\u8133\u578b\u4eba\u5de5\u77e5\u80fd\u300d\uff08\u62c5\u5f53\uff1a\u8133\u6a5f\u80fd\u30a4\u30e1\u30fc\u30b8\u30f3\u30b0\u3001\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u3001\u30cb\u30e5\u30fc\u30ed\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\uff09, \u4e5d\u5dde\u5de5\u696d\u5927\u5b66\u96c6\u4e2d\u8b1b\u7fa9\uff08\u5206\u62c53\u30b3\u30de\uff09, 2017.<\/li>\n
                                                                                              2. \u5ddd\u934b\u3000\u4e00\u6643, “\u5b9f\u74b0\u5883BMI\u7814\u7a76\u306e\u73fe\u72b6\u3068\u8ab2\u984c\uff0d\u5de5\u5b66\u8005\u304b\u3089\u8133\u5916\u79d1\u533b\u3078\uff0d”, \u7b2c4\u56de\u8133\u795e\u7d4c\u5916\u79d1BMI\u61c7\u8ac7\u4f1a\u7279\u5225\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u6771\u4eac\u533b\u79d1\u6b6f\u79d1\u5927\u5b66\uff08\u6771\u4eac\u90fd\uff09, 2017.<\/li>\n
                                                                                              3. \u5ddd\u934b\u3000\u4e00\u6643, “\u30cb\u30e5\u30fc\u30ed\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30c3\u30af\u306e\u6700\u65b0\u52d5\u5411”, JOEM Workshop ’17\u300c\u30c7\u30b8\u30bf\u30eb\u30d8\u30eb\u30b9\u30b1\u30a2\u300d, \u65b0\u5bbfNS\u30d3\u30eb\uff08\u6771\u4eac\u90fd\uff09, 2017\uff08\u62db\u5f85\uff09.<\/li>\n
                                                                                              4. Akasaki,T., Kawasaki, M., \u201cConstruction of a system for managing and reuse the physiological data with various modalities\u201d, \u65b0\u5b66\u8853\u9818\u57df\u300c\u975e\u7dda\u5f62 \u767a\u632f\u73fe\u8c61\u3092\u57fa\u76e4\u3068\u3057\u305f\u30d2\u30e5\u30fc\u30de\u30f3\u30cd\u30a4\u30c1\u30e3\u30fc\u306e\u7406\u89e3\u300d\u795e\u7d4c\u30c7\u30fc\u30bf\u89e3\u6790\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7 (\u4eac\u90fd\u5927\u5b66\u9644\u5c5e\u75c5\u9662\uff09(2016.2.22)<\/li>\n
                                                                                              5. \u5ddd\u934b\u3000\u4e00\u6643, \u201c\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u201d,\u516c\u76ca\u793e\u56e3\u6cd5\u4eba\u65e5\u672c\u78c1\u6c17\u5b66\u4f1a\u3000\u7b2c4\u56de\u5ca9\u5d0e\u30b3\u30f3\u30d5\u30a1\u30ec\u30f3\u30b9
                                                                                                \n\u300c\u533b\u5de5\u5b66\u3068\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u304c\u62d3\u304f\u533b\u7642\u306e\u672a\u6765\u300d, \u62db\u5f85\u8b1b\u6f14, (\u4e2d\u592e\u5927\u5b66\u99ff\u6cb3\u53f0\u8a18\u5ff5\u9928, \u6771\u4eac\u90fd) (2016.5.16-5.17)<\/li>\n
                                                                                              6. \u9808\u5c71\u3000\u656c\u4e4b, \u201c\u65e5\u5e38\u751f\u6d3b\u306e\u652f\u63f4\u3092\u53ef\u80fd\u3068\u3059\u308b\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u306e\u7814\u7a76\u958b\u767a\u201d, \u62db\u5f85\u8b1b\u6f14, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a \u77e5\u7684\u74b0\u5883\u3068\u30bb\u30f3\u30b5\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u7814\u7a76\u4f1a(ASN), (\u69cb\u9020\u8a08\u753b\u7814\u7a76\u6240,\u6771\u4eac\u90fd) (2016.5.12-5.13)<\/li>\n
                                                                                              7. \u77f3\u4e95 \u4fe1\u3001\u9808\u5c71 \u656c\u4e4b\u3001\u5ddd\u934b \u4e00\u6643\u3001\u201c\u65e5\u5e38\u751f\u6d3b\u306e\u652f\u63f4\u3092\u76ee\u6307\u3059\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u201d\u3001\u7b2c7\u56de\u8133\u30d7\u30ed\u516c\u958b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u300c\u80b2\u3061\u30fb\u66ae\u3089\u3057\u30fb\u8001\u3044\u300d\u5b66\u8853\u7dcf\u5408\u30bb\u30f3\u30bf\u30fc (\u6771\u4eac\u90fd) (2015.2.7)<\/li>\n
                                                                                              8. \u5b88\u8c37\u3000\u5927\u6a39\u3001\u201c\u8133\u6ce2\u3092\u7528\u3044\u305f\u60c5\u52d5\u89e3\u8aad\u7814\u7a76\uff1a\u5b9f\u74b0\u5883\u3068\u5b9f\u9a13\u5ba4\u306b\u304a\u3051\u308b\u691c\u8a3c\u201d\u3001\u300c\u5b9f\u74b0\u5883\u5fdc\u7528\u3092\u5fd7\u3057\u305f\u60c5\u52d5\u306e\u5fc3\u7406\u751f\u7406\u5b66\u30fb\u795e\u7d4c\u79d1\u5b66\u7814\u7a76\u300d\u56fd\u7acb\u7814\u7a76\u958b\u767a\u6cd5\u4eba\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240\u4eba\u9593\u60c5\u5831\u90e8\u9580\u60c5\u5831\u6570\u7406\u7814\u7a76\u30b0\u30eb\u30fc\u30d7\uff08\u3064\u304f\u3070\u5e02\u3001\u8328\u57ce\u770c\uff09\uff082015.6.18)<\/li>\n
                                                                                              9. \u5bae\u897f\u3000\u5927\u6a39\u3001\u201c\u4eba\u9593\u306e\u8996\u899a\u8a18\u61b6\u62e1\u5f35\u306b\u5411\u3051\u305f\u4e00\u4eba\u79f0\u59cb\u70b9\u6620\u50cf\u306e\u691c\u7d22”\u3001\u4eba\u5de5\u77e5\u80fd\u30b2\u30b9\u30c8\u30ec\u30af\u30c1\u30e3\u30fc\u3000\u7532\u5357\u5927\u5b66(\u5175\u5eab\u770c\uff09\uff082015.7.6)<\/li>\n
                                                                                              10. \u9808\u5c71\u3000\u656c\u4e4b\u3001\u201c\u5b9f\u751f\u6d3b\u74b0\u5883\u306b\u304a\u3051\u308b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9\u306e\u5b9f\u73fe\u306b\u5411\u3051\u3066\u201d\u3001\u30bb\u30f3\u30b7\u30f3\u30b0\u6280\u8853\u5fdc\u7528\u7814\u7a76\u4f1a\u7b2c192\u56de\u7814\u7a76\u4f8b\u4f1a (\u5927\u962a\u5e9c\uff09\uff082015.9.4)<\/li>\n
                                                                                              11. \u5ddd\u934b\u3000\u4e00\u6643\u3001\u5c0f\u5ddd\u3000\u525b\u53f2\u3001\u5b88\u8c37\u3000\u5927\u6a39\u3001\u5bae\u897f\u3000\u5927\u6a39\u3001\u77e2\u91ce\u3000\u61b2\u3001\u9808\u5c71\u3000\u656c\u4e4b\u3001\u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u301c\u65e5\u5e38\u7684\u74b0\u5883\u306b\u304a\u3051\u308b\u751f\u6d3b\u652f\u63f4\u306e\u5b9f\u73fe\u306b\u5411\u3051\u305fBMI\u301c\u201d, ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92015 (\u4eac\u90fd\u5e9c)(2015.10.29-10.30)<\/li>\n
                                                                                              12. \u9e7f\u5185 \u53cb\u7f8e\u3001\u77f3\u4e95 \u4fe1\u3001\u201cfMRI \u8133\u6d3b\u52d5\u304b\u3089prior belief\u3092\u8aad\u307f\u51fa\u3059\u201d\u3001 \u8133\u3068\u5fc3\u306e\u30e1\u30ab\u30cb\u30ba\u30e0 \u7b2c14\u56de\u51ac\u306e\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7 (\u30eb\u30b9\u30c4\u3001\u5317\u6d77\u9053) (2014.1.8-1.9)<\/li>\n
                                                                                              13. \u5c0f\u5c71\u7530\u3000\u5275\u54f2\u3001\u9e7f\u5185\u3000\u53cb\u7f8e\u3001 \u77f3\u4e95\u3000\u4fe1\u3001\u201c\u5927\u898f\u6a21fMRI\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u304b\u3089\u306e\u8133\u6d3b\u52d5\u8868\u73fe\u306e\u5b66\u7fd2\u201d\u3001\u3000\u8133\u3068\u5fc3\u306e\u30e1\u30ab\u30cb\u30ba\u30e0 \u7b2c14\u56de\u51ac\u306e\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7 (\u30eb\u30b9\u30c4\u3001\u5317\u6d77\u9053) (2014.1.8-1.9)<\/li>\n
                                                                                              14. \u5ddd\u934b \u4e00\u6643\u3001\u77f3\u4e95 \u4fe1\u3001”\u65e5\u5e38\u751f\u6d3b\u306e\u652f\u63f4\u3092\u76ee\u6307\u3059\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9”, \u7b2c6\u56de\u8133\u30d7\u30ed\u516c\u958b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u300c\u3064\u306a\u304c\u308a\u306e\u8133\u79d1\u5b66\u300d, \u5b66\u8853\u7dcf\u5408\u30bb\u30f3\u30bf\u30fc (\u6771\u4eac\u90fd), 2014.<\/li>\n
                                                                                              15. \u5ddd\u934b \u4e00\u6643\u3001\u201c\u8133\u60c5\u5831\u89e3\u8aad\u6280\u8853\u306e\u672a\u6765\u3068\u60c5\u5831\u901a\u4fe1\u5206\u91ce\u3078\u306e\u5c55\u958b\u201d\u3001\u7b2c31\u56de\u60c5\u5831\u51e6\u7406\u901a\u4fe1\u5b66\u4f1a\u5927\u4f1a \u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u5927\u962a\u5927\u5b66\u4e2d\u4e4b\u5cf6\u30bb\u30f3\u30bf\u30fc (\u5927\u962a\u5e02\u3001\u5927\u962a\u5e9c) (2014.6.28)<\/li>\n
                                                                                              16. \u5ddd\u934b \u4e00\u6643\u3001\u201c\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u306e\u305f\u3081\u306e\u975e\u5b9a\u5e38\u6027\u306b\u5bfe\u3057\u3066\u30ed\u30d0\u30b9\u30c8\u306a\u8133\u6ce2\u7279\u5fb4\u91cf\u306e\u69cb\u7bc9\u6cd5\u306b\u3064\u3044\u3066\u201d\u3001\u5317\u9678\u5148\u7aef\u79d1\u5b66\u6280\u8853\u5927\u5b66\u9662\u5927\u5b66\u60c5\u5831\u79d1\u5b66\u7814\u7a76\u79d1\u30bb\u30df\u30ca\u30fc (\u80fd\u7f8e\u5e02\u3001\u77f3\u5ddd\u770c) (2014.10.17)<\/li>\n
                                                                                              17. \u5ddd\u934b \u4e00\u6643\u3001\u201c\u65e5\u5e38\u74b0\u5883\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u306e\u305f\u3081\u306e\u8133\u60c5\u5831\u89e3\u8aad\u6cd5\u306b\u3064\u3044\u3066\u201d\u3001NAIST\u30bc\u30df\u30ca\u30fc\u30eb, \u5948\u826f\u5148\u7aef\u79d1\u5b66\u6280\u8853\u5927\u5b66\u9662\u5927\u5b66\u3000(\u751f\u99d2\u5e02\u3001\u5948\u826f\u770c)\u3000(2014.10.22)<\/li>\n
                                                                                              18. \u9808\u5c71 \u656c\u4e4b\u3001\u201c\u8133\u306e\u4ed5\u7d44\u307f\u3092\u6d3b\u304b\u3057\u305f\u30a4\u30ce\u30d9\u30fc\u30b7\u30e7\u30f3 \u301c\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u201d\u3001\u793e\u4f1a\u30a4\u30ce\u30d9\u30fc\u30b7\u30e7\u30f3 Smart City Week 2014 (\u6a2a\u6d5c\u5e02\u3001\u795e\u5948\u5ddd\u770c) (2014.10.31)<\/li>\n
                                                                                              19. \u9808\u5c71 \u656c\u4e4b\u3001\u5ddd\u934b \u4e00\u6643\u3001 Abdur-Rahim, J.A.\u3001\u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9 \u301c\u65e5\u5e38\u7684\u74b0\u5883\u306b\u304a\u3051\u308b\u751f\u6d3b\u652f\u63f4\u306e\u5b9f\u73fe\u306b\u5411\u3051\u305fBMI\u201d\u3001ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92014 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2014.11.6-11.7)<\/li>\n
                                                                                              20. \u5e73\u5c71 \u6df3\u4e00\u90ce\u3001\u897f \u5927\u6a39\u3001 \u77e2\u91ce \u61b2\u3001\u201c\u8133\u6ce2\u306e\u5171\u6d3b\u6027\u6210\u5206\u5206\u6790 \u301cBMI\u306b\u95a2\u9023\u3057\u305f\u8133\u6d3b\u52d5\u72b6\u614b\u306e\u767a\u898b\u30fb\u62bd\u51fa\u301c\u201d\u3001ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92014 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2014.11.6-11.7)<\/li>\n
                                                                                              21. Oztop, E., \u201cAction understanding and generation\u201d, Turkish German Multimodal Interaction Summit (Istanbul, Turkey) (2014.11.11)<\/li>\n
                                                                                              22. \u68ee\u5ca1 \u535a\u53f2\u3001\u517c\u6751 \u539a\u7bc4\u3001 \u5ddd\u934b \u4e00\u6643\u3001 \u5409\u5ca1 \u7422\u3001 \u68ee\u672c \u667a\u5fd7\u3001 \u77f3\u4e95 \u4fe1\u3001 \u201cNIRS\u3092\u4e8b\u524d\u60c5\u5831\u3068\u3057EEG\u304b\u3089\u63a8\u5b9a\u3055\u308c\u305f\u76ae\u8cea\u96fb\u6d41\u304b\u3089\u306e\u7a7a\u9593\u6ce8\u610f\u306e\u30c7\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u201d\u3001 \u8133\u3068\u5fc3\u306e\u30e1\u30ab\u30cb\u30ba\u30e0\u7b2c13\u56de\u51ac\u306e\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7 (\u30eb\u30b9\u30c4\u3001\u5317\u6d77\u9053) (2013.1.9-1.11)<\/li>\n
                                                                                              23. \u9e7f\u5185 \u53cb\u7f8e\u3001\u77f3\u4e95 \u4fe1\u3001 \u201c\u4e09\u6b21\u5143\u30ca\u30d3\u30b2\u30fc\u30b7\u30e7\u30f3\u74b0\u5883\u306b\u304a\u3051\u308b\u30b7\u30fc\u30f3\u4e88\u6e2c\u306e\u30c7\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u201d\u3001 \u8133\u3068\u5fc3\u306e\u30e1\u30ab\u30cb\u30ba\u30e0\u7b2c13\u56de\u51ac\u306e\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7 (\u30eb\u30b9\u30c4\u3001\u5317\u6d77\u9053) (2013.1.9-1.11)<\/li>\n
                                                                                              24. \u77f3\u4e95 \u4fe1\u3001 \u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9\u3068\u4e00\u822c\u751f\u6d3b\u74b0\u5883\u3078\u306e\u5fdc\u7528\u53ef\u80fd\u6027\u201d\u3001 \u4f4e\u6d88\u8cbb\u96fb\u529b\u9ad8\u5727LSI\u6280\u8853\u61c7\u8ac7\u4f1a \u62db\u5f85\u8b1b\u6f14\u3001\u6771\u4eac\u5927\u5b66\u751f\u7523\u6280\u8853\u7814\u7a76\u6240\u3001\u99d2\u5834\u30ea\u30b5\u30fc\u30c1\uff77\uff6c\uff9d\uff8a\uff9f\uff7d (\u76ee\u9ed2\u533a\u3001\u6771\u4eac\u90fd) (2013.3.11)<\/li>\n
                                                                                              25. \u9e7f\u5185 \u53cb\u7f8e\u3001\u77f3\u4e95 \u4fe1\u3001\u201c\u8133\u5185\u3067\u4e88\u6e2c\u3055\u308c\u305f\u6b21\u6642\u523b\u30b7\u30fc\u30f3\u306e\u30c7\u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u201d\u3001 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u30cb\u30e5\u30fc\u30ed\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u7814\u7a76\u4f1a\u3001Vol.112, No.480, pp.239-242\u3001\u7389\u5ddd\u5927\u5b66 (\u753a\u7530\u5e02\u3001\u6771\u4eac\u90fd) (2013.3.15)<\/li>\n
                                                                                              26. \u5ddd\u934b \u4e00\u6643\u3001 \u201c\u65e5\u5e38\u751f\u6d3b\u652f\u63f4\u3092\u76ee\u6307\u3059\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u201d\u3001 \u7b2c5\u56de \u8133\u30d7\u30ed\u516c\u958b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u5b66\u8853\u7dcf\u5408\u30bb\u30f3\u30bf\u30fc (\u5343\u4ee3\u7530\u533a\u3001\u6771\u4eac\u90fd) (2013.2.2)<\/li>\n
                                                                                              27. \u77f3\u4e95 \u4fe1\u3001 \u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30fb\u30de\u30b7\u30f3\u30fb\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9\u3068\u751f\u6d3b\u652f\u63f4\u3078\u306e\u5fdc\u7528\u201d\u3001 \u7b2c1\u56de\u533b\u5de5\u9023\u643a\u4eba\u6750\u80b2\u6210\u30bb\u30df\u30ca\u30fc\u3001\u62db\u5f85\u8b1b\u6f14\u3000\u4eac\u90fd\u5927\u5b66 (\u4eac\u90fd\u5e02\u3001\u4eac\u90fd\u5e9c) (2013.9.16)<\/li>\n
                                                                                              28. \u5ddd\u934b \u4e00\u6643\u3001\u9e7f\u5185 \u5b66\u3001 \u77f3\u4e95 \u4fe1\u3001 \u201c\u65e5\u5e38\u751f\u6d3b\u306e\u652f\u63f4\u3092\u76ee\u6307\u3059\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578b\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u201d\u3001 \u8133\u30d7\u30ed\u516c\u958b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0 IN \u540d\u53e4\u5c4b, (\u540d\u53e4\u5c4b\u5e02\u3001\u611b\u77e5\u770c) (2013.9.14)<\/li>\n
                                                                                              29. \u7af9\u5185 \u4ea8\u3001\u77f3\u4e95 \u4fe1\u3001\u5ddd\u91ce \u54f2\u751f\u3001\u201cJGN-X\u3092\u6d3b\u7528\u3057\u305f\u7814\u7a76\u958b\u767a\u6210\u679c\u306e\u4e8b\u4f8b \uff5e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578bBMI\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u304a\u3051\u308b\u5206\u6563\u7ba1\u7406\u30fb\u51e6\u7406\u57fa\u76e4\u306e\u7814\u7a76\u958b\u767a\uff5e\u201d\u3001JGN-X\u306eHP\u7b49(NICT)\u3000(2013.5.17)<\/li>\n
                                                                                              30. \u7af9\u5185 \u4ea8\u3001\u77f3\u4e95 \u4fe1\u3001\u5ddd\u91ce \u54f2\u751f\u3001\u201cJGN-X\u3092\u6d3b\u7528\u3057\u305f\u7814\u7a76\u958b\u767a\u6210\u679c\u306e\u4e8b\u4f8b \uff5e\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578bBMI\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306b\u304a\u3051\u308b\u5206\u6563\u7ba1\u7406\u30fb\u51e6\u7406\u57fa\u76e4\u306e\u7814\u7a76\u958b\u767a\uff5e\u201d\u3001JGN-X\u306eHP\u7b49(NICT)\u3000(2013.6.20)<\/li>\n
                                                                                              31. \u5c0f\u5ddd \u525b\u53f2\u3001\u9e7f\u5185 \u5b66\u3001 Abdur-Rahim Jamilah\u3001 \u77e2\u91ce \u61b2\u3001Gupta Pankaji\u3001 \u5ddd\u934b \u4e00\u6643\u3001 \u77f3\u4e95 \u4fe1\u3001 \u201c\u65e5\u5e38\u7684\u74b0\u5883\u306b\u304a\u3051\u308b\u751f\u6d3b\u652f\u63f4\u306e\u5b9f\u73fe\u306b\u5411\u3051\u305f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578bBMI (BMI\u30cf\u30a6\u30b9\u4e00\u822c\u516c\u958b)\u201d\u3001 ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92013 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2013.11.7-11.8)<\/li>\n
                                                                                              32. \u68ee\u5ca1 \u535a\u53f2\u3001\u5ddd\u934b \u4e00\u6643\u3001 \u5e73\u5c71 \u6df3\u4e00\u90ce\u3001 \u4e38\u5c71 \u96c5\u7d00\u3001 \u9e7f\u5185 \u5b66\u3001 \u201cNIRS-EEG\u306b\u3088\u308b\u7a7a\u9593\u6ce8\u610f\u306e\u8b58\u5225\u201d\u3001 ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92013 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2013.11.7-11.8)<\/li>\n
                                                                                              33. \u5ddd\u934b \u4e00\u6643\u3001\u5e73\u5c71 \u6df3\u4e00\u90ce\u3001 \u68ee\u5ca1 \u535a\u53f2\u3001 \u4e38\u5c71 \u96c5\u7d00\u3001 \u9e7f\u5185 \u5b66\u3001 \u201c\u65e5\u5e38\u74b0\u5883\u306b\u304a\u3051\u308b\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578bBMI\u201d\u3001 ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92013 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2013.11.7-11.8)<\/li>\n
                                                                                              34. Abdur-Rahim, J. A., \u201cBMI House\u201d \u3001 \u56fd\u969b\u30b5\u30a4\u30a8\u30f3\u30b9\u30ab\u30d5\u30a7\u300c\u6700\u5148\u7aef\u8133\u79d1\u5b66\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u300d\u3001\u62db\u5f85\u8b1b\u6f14 (\u5927\u962a\u5e02\u3001\u5927\u962a\u5e9c) (2013.11.18)<\/li>\n
                                                                                              35. \u77f3\u4e95 \u4fe1\u3001\u517c\u6751 \u539a\u7bc4\u3001\u201c\u65e5\u5e38\u751f\u6d3b\u306e\u652f\u63f4\u3092\u76ee\u6307\u3059\u30cd\u30c3\u30c8\u30ef\u30fc\u30afBMI\u201d\u3001 \u7b2c4\u56de\u8133\u30d7\u30ed\u516c\u958b\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0, \u5b66\u8853\u7dcf\u5408\u30bb\u30f3\u30bf\u30fc (\u5343\u4ee3\u7530\u533a\u3001\u6771\u4eac\u90fd) (2012.2.4)<\/li>\n
                                                                                              36. \u77f3\u4e95 \u4fe1\u3001 \u201cBMI\u30b9\u30de\u30fc\u30c8\u30cf\u30a6\u30b9\u301c\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u306b\u3088\u308b\u751f\u6d3b\u652f\u63f4\u201d\u3001 ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92012, \u7814\u7a76\u958b\u767a\u8b1b\u6f14 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2012.11.8-11.9)<\/li>\n
                                                                                              37. \u5e73\u5c71 \u6df3\u4e00\u90ce\u3001\u68ee\u672c \u667a\u5fd7\u3001 \u4e38\u5c71 \u96c5\u7d00\u3001 \u201c\u8133\u6d3b\u52d5\u304b\u3089\u624b\u306e\u52d5\u304d\u3092\u89e3\u8aad\u4e88\u6e2c\u3059\u308b\u624b\u6cd5\u201d\u3001 ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92012 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2012.11.8-11.9)<\/li>\n
                                                                                              38. \u5ddd\u934b \u4e00\u6643\u3001\u517c\u6751 \u539a\u7bc4\u3001 \u5c0f\u5ddd \u525b\u53f2\u3001 Ugur Emre\u3001 Singh Archana\u3001 Abdur-Rahim Jamilah\u3001 Ahamed Toshif\u3001 \u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578bBMI\u306b\u3088\u308b\u5b9f\u74b0\u5883BMI\u30b7\u30b9\u30c6\u30e0\u306e\u958b\u767a\u201d, ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92012 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2012.11.8-11.9)<\/li>\n
                                                                                              39. \u77f3\u4e95 \u4fe1\u3001 \u201c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u578bBMI\u306b\u3088\u308b\u30a4\u30ce\u30d9\u30fc\u30b7\u30e7\u30f3\u5275\u6210\u201d\u3001ATR\u30aa\u30fc\u30d7\u30f3\u30cf\u30a6\u30b92011 (\u76f8\u697d\u90e1\u3001\u4eac\u90fd\u5e9c) (2011.11.11-11.12)<\/li>\n<\/ol>\n

                                                                                                \u53d7\u8cde\/Award<\/p>\n

                                                                                                  \n
                                                                                                1. Morioka, H., Best Poster Award of the10th AEARU Workshop on Computer Science and Web Technology, \u201cSubject-transfer decoding by learning a common dictionary from multisubject dataset\u201d, 2014.2.25<\/li>\n<\/ol>\n

                                                                                                  \u4ee5\u524d\u306e\u51fa\u7248\u7269<\/p>\n

                                                                                                  DBI\u8a2d\u7acb\uff082010\u5e74\uff09\u4ee5\u524d\u306e\u51fa\u7248\u7269\u306b\u3064\u3044\u3066\u306f\u3001DBI\u306e\u5206\u6d3e\u5143\u3067\u3042\u308bCBI\u306e\u30da\u30fc\u30b8<\/a>\u3092\u3054\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

                                                                                                  2026\u5e74 \u67fb\u8aad\u4ed8\u304d\u8a8c\u4e0a\u767a\u8868\u8ad6\u6587\/Journal articles Tsutsumi M, Kishi T, Ogawa T, Kuroda T, Kobler R, Kawanabe M. An EEG dataset […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-78","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/pages\/78","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/comments?post=78"}],"version-history":[{"count":279,"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/pages\/78\/revisions"}],"predecessor-version":[{"id":2782,"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/pages\/78\/revisions\/2782"}],"wp:attachment":[{"href":"https:\/\/bicr.atr.jp\/dbi\/wp-json\/wp\/v2\/media?parent=78"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}