研究成果
カテゴリ
発表年

国際会議 講演・発表

  1. 1. Doya K, Neural circuits for reinforcement learning and mental simulation, 2017 , Queensland Brain Institute, The University of Queensland, Brisbane, Australia, 2017.12.14, invited BibTeX
  2. 2. *Hikida T, Macpherson T, Nucleus accumbens D1 receptor expressing neurons control sutoshaping behavior., 2017 BibTeX
  3. 3. Macpherson T, *Hikida T, Dopamine D2L receptors control flexible behavior., 2017 BibTeX
  4. 4. Takufumi Yanagisawa, Ryohei Fukuma, Ben Seymour, Koichi Hosomi, Haruhiko Kishima, Toshiki Yoshimine, Yukiyasu Kamitani, Youichi Saitoh, MEG-Neurofeedback for phantom limb pain, 2017 BibTeX
  5. 5. *Tadahiro Taniguchi, Symbol Emergence in Robotics: from sensorimotor information to language, 2017 , invited BibTeX
  6. 6. Fukai T, Unsupervised reservoir computing for chunking sequence information., 2017 BibTeX
  7. 7. Tanaka S, Kawasaki K, Hasegawa I, Suzuki T, Kawato M and Sakagami M, Elucidating the role of the macaque lateral prefrontal cortex for the value-based decision making using the decoded neurofeeback, 2017 11 BibTeX
  8. 8. *J. Hirayama, T. Ogawa, H. Moriya, A. Hyvärinen & M. Kawanabe, Exploring EEG source resting-state networks by SPLICE: A simultaneous fMRI study, 2017 , reviewed# BibTeX
  9. 9. *T. Ogawa, H. Moriya, T. Yamada, M. Kawanabe & J. Hirayama, Prediction of resting state fMRI signatures from EEG signal: a study of EEG-fMRI simultaneous recording, 2017 , reviewed# BibTeX
  10. 10. *H. Moriya, T. Ogawa, M. Kawanabe, J. Hirayama, Predictability of amygdala BOLD signal from multiple-electrode EEGs, 2017 , reviewed# BibTeX
  11. 11. *Hikida T, Basal ganglia network mechanisms in cognitive learning, 2017 , invited BibTeX
  12. 12. T. Yanagisawa, R. Fukuma, B. Seymour, K. Hosomi, H. Kishima, T. Shimizu, H. Yokoi, M. Hirata, T. Yoshimine, Y. Kamitani, Y. Saitoh, MEG-based BMI controlled the sensorimotor cortical plasticity and phantom limb pain, 2017 , invited BibTeX
  13. 13. *Reinke C, Doya K, Adaptation of Optimization Algorithms to Problem Domains by Transfer Learning, 2017 , OIST, 2017.11.24 BibTeX
  14. 14. Benucci A., Sensory Representation Plasticity Driven by Single Neurons in the Mouse Cortex, 2017 Nov, Invited talk BibTeX
  15. 15. Doya K, What can we further learn from the brain?, 2017 , Guangzhou, China, 2017.11.16, invited BibTeX
  16. 16. *Jun-ichiro FURUKAWA, Asuka TAKAI,Jun MORIMOTO, Database-driven approach for biosignal-based robot control with collaborative filtering, 2017 11, reviewed# BibTeX
  17. 17. Haga T, Fukai T, Reverse replay strengthens forward pathways to reward through Hebbian learning and short-term depression., 2017 BibTeX
  18. 18. *Yoshizawa T, Ito M, Doya K, Neural representation of sensory-state value in the striatal striosome compartment , 2017 , Walter E. Washington Convention Center, Washington DC, USA, 2017.11.14 BibTeX
  19. 19. Fukuda H, Ma N, Suzuki S, Harasawa N, Ueno K, Gardner JL, Ichinohe N, Haruno M, Cheng K, Nakahara H. , Neural mechanisms for converting social value into one’s own decision value, 2017 BibTeX
  20. 20. Ma N, Harasawa N, Ueno K, Ichinohe N, Haruno M, Cheng K, Nakahara H., Neural mechanisms for deciding with predicting others in human brain, 2017 BibTeX
  21. 21. Tanaka S, Kawasaki K, Hasegawa I, Suzuki T, Kawato M and Sakagami M, Spatial and temporal distribution of value-related and the visual information in the macaque lateral prefrontal cortex, 2017 11 BibTeX
  22. 22. Tsubota T., *Benucci A., Plasticity for stimulus selectivity in the visual cortex of adult mice induced by patterned optogenetic stimulation, 2017 Nov BibTeX
  23. 23. Asabuki T, Fukai T, Chunk learning from complex sequences by mutually supervising recurrent neural networks, 2017 BibTeX
  24. 24. DeCostanzo A, Fukai T, A local supervised learning rule protects memories from catastrophic interference during subsequent unsupervised learning., 2017 BibTeX
  25. 25. Watanabe K, Haga T, Tatsuno M, Euston DR, Fukai T, Blind detection of behavior related population activity by using edit similarity measurement and statistical modeling., 2017 ,   BibTeX
  26. 26. Uezono S, Tanabe S, Fujiwara M, Tsuge H, Nakamura K, Inoue K, Takada M, Organization of multisynaptic inputs from the basal ganglia and cerebellum to the anterior and posterior cingulate cortical areas in common marmosets: Retrograde transneuronal double labeling with fluorescent rabies viral vectors., 2017 11, Washington, DC, USA BibTeX
  27. 27. Takaya Ogasawara, Masahiko Takada, Masayuki Matsumoto, The nigrostriatal dopamine pathway transmits a stop signal during the performance of a saccadic countermanding task in monkeys, Society for Neuroscience BibTeX
  28. 28. Inoue K, Fujiwara M, Uezono S, Tanabe S, Ishida H, Hoshi E, Takada M, Arrangement of multisynaptic inputs from the basal ganglia to the dorsal and ventral premotor cortical areas in macaques: retrograde transneuronal double labeling with fluorescent rabies viral vectors., 2017 11, Washington, DC, USA BibTeX
  29. 29. Sidney Lehky, A Phan, A Cichocki, and Keiji Tanaka, Coding of faces by tensor components, ポスター発表 BibTeX
  30. 30. Kurikawa T, Handa T, Fukai T, Instability of neural trajectories in medial frontal cortex predicts individual differences in perceptual decision making., 2017 BibTeX
  31. 31. J. Matsumoto, H. Nishimaru, Y. Takamura, K. Mimura, A. Asaba, W. Suzuki, N. Ichinohe, T. Minamimoto, T. Ono, H. Nishijo, 3D-Tracker, an open-source 3D video based behavioral analysis system for laboratory animals for neuroscience, 2017 November BibTeX
  32. 32. Macpherson T, *Hikida T, Nucleus Accumbens D1 receptor expressing neurons control autoshaping behavior, 2017 BibTeX
  33. 33. *Nakajima H, Nakamura S, Kita A, Itakura M, Senami C, Kuwamura M, Hikida T, Azuma Y-T, Takeuchi T, Blockade of GAPDH nuclear translocation in the hippocampus contributes to anti-depressant-like action in stressed mice, 2017 BibTeX
  34. 34. Inoue K, Pathway-selective optogenetics for elucidating neural network function in primates., 2017 11, invited, Washington, DC, USA BibTeX
  35. 35. *Parmas P, Peters J, Doya K, The optimal-baseline estimator is not the optimal baseline-estimator, 2017 , Tokyo, Japan, 2017.11.10 BibTeX
  36. 36. T. Yoshimoto, J. Chikazoe, S. Okazaki, M. Sumiya, H. K. Takahashi, E. Nakagawa, T. Koike, R. Kitada, S. Okamoto, M. Nakata, H, Kosaka, T. Yada, N. Sadato, Abstractness of value representation in orbitofrontal cortex, 2017 , poster BibTeX
  37. 37. Mao Noguchi, So Fujimoto, Akihiko Nikkuni, Yutaka Komura*, Core of neural network for conscious states and percepts in primate, 2017 , invited BibTeX
  38. 38. *Sayuri Hashimoto and Ichiro Kobayashi, A Basic Study on Action Control Using Deep Reinforcement Learning, 2017 , reviewed BibTeX
  39. 39. *Hikida T, Neuronal circuit mechanisms in reward and aversive behavior., 2017 , invited BibTeX
  40. 40. *Masumori, A., Maruyama, N., Mita, T., Bakkum, D., Frey, U., Takahashi, H.,& Ikegami, T, Learning by Stimulation Avoidance in Cultured Neuronal Cells, 2017 , reviewed BibTeX
  41. 41. *Maruyama, N., Hashimoto, Y., Mototake, Y., Saito, D., & Ikegami, T, Revisiting Classification of Large Scale Flocking, 2017 , reviewed BibTeX
  42. 42. *Hashimoto, Y., Ikegami, T, Novelty production in tagging crowds, 2017 , reviewed BibTeX
  43. 43. Tanno, T., Horie, K., Izawa, J. and Morita, M, Robustness of Selective Desensitization Perceptron Against Irrelevant and Partially Relevant Features in Pattern Classification, 2017 11, 520-529 BibTeX
  44. 44. *Reinke C, Uchibe E, Doya K, Average Reward Optimization with Multiple Discounting Reinforcement Learners, 2017 , Guangzhou, China, 2017.10.24 BibTeX
  45. 45. Doya K, Artificial Intelligence and Brain Science, 2017 , Kyungpook National University, Daegu, Korea, 2017.10.19 BibTeX
  46. 46. Hidehiko Takahashi, Altered decision-making as endophenotypes to bridge the gap between phenomenology and neurobiology, 2017 , invited BibTeX
  47. 47. Takanori Uka, Neural mechanism of flexible sensory decision making, invited BibTeX
  48. 48. BibTeX
  49. 49. Masamichi Sakagami, Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum, 2017 10, invited BibTeX
  50. 50. *Yoshizawa T, Ito M, Doya K, Coding of value information in the striatal striosome compartment, 2017 , CHÂTERAISÉ Gateaux Kingdom SAPPORO, Japan, 2017.10.4 BibTeX
  51. 51. Macpherson T, *Hikida T, Nucleus accumbens dopamine D1-receptor-expresing neurons control Pavlovian approach behaviour., 2017 BibTeX
  52. 52. Takufumi Yanagisawa, BMI robotic hand controls phantom limb pain, 2017 , invited BibTeX
  53. 53. *Masashi HAMAYA, Takamitsu MATSUBARA, Tomoyuki NODA,Tatsuya TERAMAE,Jun MORIMOTO, User-robot collaborative excitation for PAM model identification in exoskeleton robots, 2017 9, reviewed# BibTeX
  54. 54. *Yuki Tada, Yoshinobu Hagiwara, +Tadahiro Taniguchi, Comparative Study of Feature Extraction Methods for Direct Word Discovery with NPB-DAA from Natural Speech Signals, 2017 9, reviewed# BibTeX
  55. 55. *Yuusuke Miyuki, Yoshinobu Hagiwara and +Tadahiro Taniguchi, Unsupervised Learning for Spoken Word Production based on Simultaneous Word and Phoneme Discovery without Transcribed Data, 2017 9, reviewed# BibTeX
  56. 56. Hayakawa T, Fukai T, Interplay of microscopic and macroscopic dynamics in randomly connected neuronal networks. , 2017 BibTeX
  57. 57. *Sinapayen, L., & Ikegami, T, Online fitting of computational cost to environmental complexity: Predictive coding with the ε-network, 2017 , reviewed BibTeX
  58. 58. *Hiroki Kojima,Takashi Ikegami, VAEGAN as a New Perception Model, 2017 , reviewed BibTeX
  59. 59. *Masumori, A., Sinapayen, L., & Ikegami, T, Learning by Stimulation Avoidance Scale to Large Neural Networks, 14th European Conference on Artificial Life, 2017 , reviewed BibTeX
  60. 60. *Doi, I., Ikegami, T., Masumori, A., Kojima, H., Ogawa K., & Ishiguro, H, A new design principle for an autonomous robot, 2017 , reviewed BibTeX
  61. 61. Nakahara H., Reinforcement learning with environmental structures and mind of others, 2017 , invited talk BibTeX
  62. 62. Akihiko Nikkuni, Yutaka Komura*, Self-evaluation in vision in monkeys and humans, 2017 , invited BibTeX
  63. 63. Macpherson T, *Hikida T, Nucleus accumbens dopamine D1-receptor-expresing neurons control attribution of incentive salience in an autoshaping task., 2017 BibTeX
  64. 64. Doya K, Reinforcement learning: basic concepts and recent advances, 2017 , Beijing Institute of Technology, China, 2017.8.16-18, invited BibTeX
  65. 65. Doya K, Neural mechanisms of reinforcement learning and mental simulation, 2017 , Beijing Institute of Technology, China, 2017.8.16-18, invited BibTeX
  66. 66. T. Yanagisawa, R. Fukuma, B. Seymour, K. Hosomi, H. Kishima, T. Shimizu, H. Yokoi, M. Hirata, T. Yoshimine, Y. Kamitani, Y. Saitoh, Magnetoencephalographic-based brain–machine interface robotic hand for controlling sensorimotor cortical plasticity and phantom limb pain, 2017 , invited BibTeX
  67. 67. *Shirasuna, M., Honda, H., Matsuka, T., & Ueda, K., Familiarity-matching in decision making: Experimental studies on cognitive processes and analyses of its ecological rationality, 2017 7, reviewed# BibTeX
  68. 68. *Honda, H., Matsuka, T., & Ueda, K., Decisions based on verbal probabilities: Decision bias or decision by sampling?, 2017 7, reviewed# BibTeX
  69. 69. Koki Mimura, Chika Sato, Jumpei Matsumoto, Ichio Aoki, Noritaka Ichinohe, Suhara Testuya, Takafumi Minamimoto, Atypical Behavioral and Neural Phenotypes in a Common Marmoset Model of Autism Spectrum Disorder, 2017 July, invited BibTeX
  70. 70. Doya K, Decoding the contents of mental simulation, 2017 , University of Tokyo, Tokyo, 2017.7.24, invited BibTeX
  71. 71. Asabuki T, Hiratani N, Fukai T, Chunking by mutual supervision in reservoir computing., 2017 , invited BibTeX
  72. 72. Doya K, Exploring the deep brain network for reinforcement learning, 2017 , Makuhari Messe, Chiba, 2017.7.21, invited BibTeX
  73. 73. Ma N, Harasawa N, Ueno K, Ichinohe N, Haruno M, Cheng K, Nakahara H., Neural mechanisms of predicting others’ decisions for one’s better decisions, 2017 BibTeX
  74. 74. Fukuda H, Ma N, Suzuki S, Harasawa N, Ueno K, Gardner JL, Ichinohe N, Haruno M, Cheng K, Nakahara H. , Neural processes for converting social value into one’s own decision value, 2017 BibTeX
  75. 75. Tanaka S, Kawasaki K, Hasegawa I, Suzuki T, Kawato M and Sakagami M, Distribution of value related information in the multiple areas of the macaque prefrontal cortex, 2017 7 BibTeX
  76. 76. Keiji Tanaka, Object recognition in inferotemporal cortex: from visual features to semantics, 基調講演, invited BibTeX
  77. 77. Eiji Uchibe* and Kenji Doya, Model-free deep inverse reinforcement learning by logistic regression, 2017 , reviewed# BibTeX
  78. 78. Doya K, What should we further learn from the brain?, 2017 , NYU Shanghai, Shanghai, China, 2017.7.7, invited BibTeX
  79. 79. Nakahara H., Learning to make reward-guided decisions: sequential, successive, and social, 2017 , invited talk BibTeX
  80. 80. Doya K, What should we further learn from the brain?, 2017 , Kyungpook National University, Daegu, Korea, 2017.7.3, invited BibTeX
  81. 81. Keiji Tanaka, Object recognition in inferotemporal cortex: from visual features to semantics, 基調講演, invited BibTeX
  82. 82. Inoue K, Fujiwara M, Uezono S, Tanabe S, Ishida H, Hoshi E, Takada M, Organization of multisynaptic inputs from the basal ganglia to the premotor cortex in macaque monkeys – Retrograde transneuronal dual tracing using rabies viral vectors., 2017 6, 蘇州市, 中華人民共和国 BibTeX
  83. 83. Macpherson T, *Hikida T, Nucleus accumbens dopamine D1-receptor-expresing neurons control incentive salience to reward-predictive cues., 2017 , invited BibTeX
  84. 84. *Hikida T, Morita M, Macpherson T, D2L receptor-expressing striatal neurons control visual discrimination learning in a touchscreen operant system., 2017 BibTeX
  85. 85. Ishida H, Inoue K, Hoshi E, Takada M, Cells of origin of multisynaptic projections from amygdala to ventral premotor cortex in macaques , 2017 6, Sicily, Italy BibTeX
  86. 86. Masamichi Sakagami, Categorical coding of stimulus and inference of the value in the monkey lateral prefrontal cortex, 2017 6, invited BibTeX
  87. 87. *Reinke C, Uchibe E, Doya K, Fast Adaptation of Behavior to Changing Goals with a Gamma Ensemble, 2017 , University of Michigan, Ann Arbor, Michigan, USA, 2017.6.12 BibTeX
  88. 88. Fukuda H, Ma N, Suzuki S, Harasawa N, Ueno K, Gardner JL, Ichinohe N, Haruno M, Cheng K, Nakahara H. , Neural mechanisms for social value conversion in decision-making, 2017 BibTeX
  89. 89. *Koji ISHIHARA,Jun-ichiro FURUKAWA,Jun MORIMOTO, A forward and inverse optimal control framework to generate humanoid robot movements with hierarchical MPC, 2017 6, reviewed# BibTeX
  90. 90. *Tadahiro Taniguchi, Semantic Segmentation of Driving Behavior Data: Double Articulation Analyzer and its Application, 2017 , invited BibTeX
  91. 91. *Masashi HAMAYA, Takamitsu MATSUBARA, Tomoyuki NODA,Tatsuya TERAMAE,Jun MORIMOTO, Learning task-parametrized assistive strategies for exoskeleton robots by multi-task reinforcement learning, 2017 5,6, reviewed# BibTeX
  92. 92. Koki Mimura, Keiko Nakagaki, Noritaka Ichinohe, Distrbed Vocal Communication in Common Marmoset Family with an Autism-Model Child, 2017 May, invited BibTeX
  93. 93. Nakahara H., Neural computations underlying social decision-making, 2017 , invited talk BibTeX
  94. 94. Nakahara H., Learning to make reward-guided decisions: sequential, successive, and social, 2017 , invited talk BibTeX
  95. 95. Hidehiko Takahashi, Interface between AI and psychiatric research. , 2017 , invited BibTeX
  96. 96. Masamichi Sakagami, Categorical Coding of Stimulus and Inference of the Value in the Monkey Lateral Prefrontal Cortex, 2017 5 BibTeX
  97. 97. Shubham Gupta, R Allen Waggoner, Keiji Tanaka, and Kang Cheng, Variation of RF-induced temperature increase in a phantom: comparison of numerical simulatitons, MR thermometry and measurements from temperature sensors, ポスター発表 BibTeX
  98. 98. R Allen Waggoner, Ken Ueno, J Pfeuffer, Keiji Tanaka, Kang Cheng, High-resolution fMRI of the visual system at 3T using zoomed excitation via Tx-SENSE, ポスター発表 BibTeX
  99. 99. Haga T, Fukai T, Dendritic computing gives a meso-scopic level framework of brain’s leaning rule. , 2017 , invited BibTeX
  100. 100. J. Chikazoe, Integrated Taste Type Representations in Human Insula, 2017 , oral BibTeX
  101. 101. T. Yoshimoto, J. Chikazoe, S. Okazaki, M. Sumiya, H. K. Takahashi, E. Nakagawa, T. Koike, R. Kitada, S. Okamoto, M. Nakata, H, Kosaka, T. Yada, N. Sadato, State-dependent and -independent representations of food revealed by multi voxel pattern analysis, 2017 , poster BibTeX
  102. 102. Masamichi Sakagami, The reward prediction error signal of midbrain dopamine neuron is modulated by the cost paid for the reward, 2017 4, invited BibTeX
  103. 103. Doya K, Coding of action and state values in the striatal compartments, 2017 , Merida, Mexico, 2017.3.29, invited BibTeX
  104. 104. Keiji Tanaka, Changes in deoxygenation level of bloods and cortical tissues following neuronal activity changes as the bases for intrinsic optical recordings and fMRI, シンポジウム, invited BibTeX
  105. 105. Abekawa Naotoshi, Gomi Hiroaki, Modulation difference in visuomotor responses in implicit and explicit motor tasks depending on postural stability, 2017 BibTeX
  106. 106. Ito Sho, Gomi Hiroaki, Rotated visual feedback of self-movement affects long-latency stretch reflex, 2017 BibTeX
  107. 107. Takamuku Shinya, Abekawa Naotoshi,Gomi Hiroaki, Automatic adjustment of walking speed by optic flow benefits from binocular vision, 2017 BibTeX
  108. 108. Ueda Hiroshi, Abekawa Naotoshi,Gomi Hiroaki, Temporal development of an interaction effect between internal motion and contour signals of drifting target on reaching adjustment, 2017 BibTeX
  109. 109. *Tadahiro Taniguchi, Symbol Emergence in Robotics: Representation Learning for Real-world Communication and Collaboration, 2017 , invited BibTeX
  110. 110. Ikegami, T, THE FUTURE OF AI IN THE ARTS , 2017 , invited BibTeX
  111. 111. Ikegami, T, 2017 , invited BibTeX
  112. 112. Ikegami, T, 2017 , invited BibTeX
  113. 113. S. Shinomoto, Emergence of cascades in the linear and nonlinear Hawkes processes, 2017 , invited BibTeX
  114. 114. S. Shinomoto, Inferring the source of fluctuation in neuronal activity, 2017 June, invited BibTeX
  115. 115. Wataru Shimoda and Keiji Yanai, Predicting Segmentation Easiness from the Consistency for Weakly-Supervised Segmentation, 2017 11, reviewed BibTeX
  116. 116. Takumi Ege and Keiji Yanai, Estimating Food Calories for Multiple-dish Food Photos, 2017 11, reviewed# BibTeX
  117. 117. Takumi Ege and Keiji Yanai, Image-Based Food Calorie Estimation Using Knowledge on Food Categories, Ingredients and Cooking Directions, 2017 10, reviewed# BibTeX
  118. 118. Takumi Ege and Keiji Yanai, Comparison of Two Approaches for Direct Food Calorie Estimation, 2017 9, reviewed# BibTeX
  119. 119. Shin Matsuo, Wataru Shimoda and Keiji Yanai, Partial Style Transfer Using Weakly-Supervised Semantic Segmentation, 2017 7, reviewed BibTeX
  120. 120. Keiji Yanai and Ryosuke Tanno, Conditional Fast Style Transfer Network, 2017 6, reviewed BibTeX
  121. 121. Takumi Ege and Keiji Yanai, Simultaneous Estimation of Food Categories and Calories with Multi-task CNN, 2017 5, reviewed BibTeX
  122. 122. Keiji Yanai, Unseen Style Transfer Based on a Conditional Fast Style Transfer Network, 2017 4, reviewed BibTeX
  123. 123. Shin Matsuo, Wataru Shimoda and Keiji Yanai, Twitter Photo Geo-Localization Using Both Textual and Visual Features, 2017 4, reviewed BibTeX
  124. 124. Wataru Shimoda and Keiji Yanai, Learning Food Image Similarity for Food Image Retrieval, 2017 4, reviewed BibTeX
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