PUBLICATIONS
Category
Year
シェア

International Conference

  1. 1. Doya K, Neural circuits for reinforcement learning and mental simulation, SCiNDU: Systems & Computational Neuroscience Down Under, 2017, 2017.12.14, Queensland Brain Institute, The University of Queensland, Brisbane, Australia, invited BibTeX
  2. 2. *Hikida T, Macpherson T, Nucleus accumbens D1 receptor expressing neurons control sutoshaping behavior, 56th Annual Meeting of the American College of Neuropsychopharmacology, 2017, poster BibTeX
  3. 3. Macpherson T, *Hikida T, Dopamine D2L receptors control flexible behavior, OU-ANU 2nd joint symposium Protein Structure and Function, 2017, poster 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, rtFIN, 2017, ATR, Kyoto, invited BibTeX
  5. 5. Tadahiro Taniguchi, Symbol Emergence in Robotics:from sensorimotor information to language, Neurobiology and Neuroinformatics 2017 (NBNI2017), 2017, Wako, Japan, invited BibTeX
  6. 6. Fukai T, Unsupervised reservoir computing for chunking sequence information., NBNI 2017, 2017, Wako, Japan 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, real-time Functional Neuroimaging and Neurofeedback 2017, 2017, Nara BibTeX
  8. 8. *Hirayama J, Ogawa T, Moriya H, Hyvärinen A, Kawanabe M, Exploring EEG source resting-state networks by SPLICE: A simultaneous fMRI study, Real-time Functional Imaging and Neurofeedback Conference (rtFIN2017), 2017, 奈良, reviewed poster BibTeX
  9. 9. *Ogawa T, Moriya H, Yamada T, Kawanabe M, Hirayama J, Prediction of resting state fMRI signatures from EEG signal: a study of EEG-fMRI simultaneous recording, Real-time Functional Imaging and Neurofeedback Conference (rtFIN2017), 2017, 奈良, reviewed poster BibTeX
  10. 10. *Moriya H, Ogawa T, Kawanabe M, Hirayama J, Predictability of amygdala BOLD signal from multiple-electrode EEGs, Real-time Functional Imaging and Neurofeedback Conference (rtFIN2017), 2017, 奈良, reviewed poster BibTeX
  11. 11. *Hikida T, Basal ganglia network mechanisms in cognitive learning, 12th International Symposium of the Institute Network –Driving Next-Generation Medicine: the Spirit of Pioneering Discovery in Medical Science, 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, rtFIN satellite symposium on brain-computer interface and neurofeedback, 2017, ATR, Kyoto, invited BibTeX
  13. 13. Ikegami, T, Life as an Emergent Phenomenon: Studies From Large-Scale Boid Simulation and Web Data, IEEE Symposium on Artificial Life (2017/11/27-12/1), 2017, Hawaii, USA, invited BibTeX
  14. 14. *Reinke C, Doya K, Adaptation of Optimization Algorithms to Problem Domains by Transfer Learning, 2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), 2017, 2017.11.24, OIST, poster BibTeX
  15. 15. *Benucci A., Sensory Representation Plasticity Driven by Single Neurons in the Mouse Cortex, invited talk, University of California San Francisco, 2017, San Francisco, CA, Invited talk BibTeX
  16. 16. Doya K, What can we further learn from the brain?, 24th International Conference on Neural Information Processing ICONIP2017, 2017, 2017.11.16, Guangzhou, China, invited BibTeX
  17. 17. *Jun-ichiro FURUKAWA, Asuka TAKAI,Jun MORIMOTO, Database-driven approach for biosignal-based robot control with collaborative filtering, IEEE-RAS International Conference on Humanoid Robots(Humanoids2017), 2017, Birmingham, UK, reviewed# BibTeX
  18. 18. 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, 2017, Washington DC, USA, poster BibTeX
  19. 19. Haga T, Fukai T, Reverse replay strengthens forward pathways to reward through Hebbian learning and short-term depression., Neuroscience 2017, 2017, Washingon, D.C., U.S.A. BibTeX
  20. 20. *Yoshizawa T, Ito M, Doya K, Neural representation of sensory-state value in the striatal striosome compartment, Society for Neuroscience 47th Annual Meeting, 2017, 2017.11.14, Walter E. Washington Convention Center, Washington DC, USA, poster BibTeX
  21. 21. Ma N, Harasawa N, Ueno K, Ichinohe N, Haruno M, Cheng K, *Nakahara H, Neural mechanisms for deciding with predicting others in human brain, The 47th Annual Meeting of the Society for Neuroscience (sfn 2017), 2017, Washington DC, USA, poster BibTeX
  22. 22. 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, The 47th Annual Meeting of the Society for Neuroscience (sfn 2017), 2017, Washington DC, USA, poster BibTeX
  23. 23. 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, Neuroscience 2017, the 47th annual meeting of the Society for Neuroscience, 2017, Washington DC BibTeX
  24. 24. Misako Komatsu, Noritaka Ichinohe, An anesthetic dose of ketamine disrupts mismatch activity in common marmosets, Neuroscience 2017, 2017, Washingtom, USA, poster BibTeX
  25. 25. Tsubota T., *Benucci A., Plasticity for stimulus selectivity in the visual cortex of adult mice induced by patterned optogenetic stimulation, Neuroscience 2017, 2017, Washington DC BibTeX
  26. 26. Asabuki T, Fukai T, Chunk learning from complex sequences by mutually supervising recurrent neural networks, Neuroscience 2017, 2017, Washingon, D.C., U.S.A. BibTeX
  27. 27. DeCostanzo A, Fukai T, A local supervised learning rule protects memories from catastrophic interference during subsequent unsupervised learning., Neuroscience 2017, 2017, Washingon, D.C., U.S.A. BibTeX
  28. 28. 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., Neuroscience 2017, 2017, Washingon, D.C., U.S.A. BibTeX
  29. 29. 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., Neuroscience 2017, 2017, Washington, DC, USA, poster BibTeX
  30. 30. Takaya Ogasawara, Masahiko Takada, Masayuki Matsumoto, The nigrostriatal dopamine pathway transmits a stop signal during the performance of a saccadic countermanding task in monkeys, 2017, Society for Neuroscience BibTeX
  31. 31. 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., Neuroscience 2017, 2017, Washington, DC, USA, poster BibTeX
  32. 32. *Lehky SR, Phan A, Cichocki A, Tanaka K, Coding of faces by tensor components, 2017, poster BibTeX
  33. 33. Kurikawa T, Handa T, Fukai T, Instability of neural trajectories in medial frontal cortex predicts individual differences in perceptual decision making., Neuroscience 2017, 2017, Washingon, D.C., U.S.A. BibTeX
  34. 34. Matsumoto J, Nishimaru H, Takamura Y, Mimura K, Asaba A, Suzuki W, Ichinohe N, Minamimoto T, Ono T, *Nishijo H, 3D-Tracker, an open-source 3D video based behavioral analysis system for laboratory animals for neuroscience, 2017, Washington DC, US BibTeX
  35. 35. Abekawa Naotoshi, Gomi Hiroaki, Modulation difference in visuomotor responses in implicit and explicit motor tasks depending on postural stability, Annual Meeting of the Society for Neuroscience (2017/11/11-15), 2017 BibTeX
  36. 36. Ito Sho, Gomi Hiroaki, Rotated visual feedback of self-movement affects long-latency stretch reflex, Annual Meeting of the Society for Neuroscience (2017/11/11-15), 2017 BibTeX
  37. 37. Takamuku Shinya, Abekawa Naotoshi,Gomi Hiroaki, Automatic adjustment of walking speed by optic flow benefits from binocular vision, Annual Meeting of the Society for Neuroscience (2017/11/11-15), 2017 BibTeX
  38. 38. Ueda Hiroshi, Abekawa Naotoshi,Gomi Hiroaki, Temporal development of an interaction effect between internal motion and contour signals of drifting target on reaching adjustment, Annual Meeting of the Society for Neuroscience (2017/11/11-15), 2017 BibTeX
  39. 39. Macpherson T, *Hikida T, Nucleus Accumbens D1 receptor expressing neurons control autoshaping behavior, Neuroscience 2017, 2017, poster BibTeX
  40. 40. *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, Neuroscience 2017, 2017, poster BibTeX
  41. 41. Inoue K, Pathway-selective optogenetics for elucidating neural network function in primates., Neuroscience 2017, 2017, Washington, DC, USA, invited BibTeX
  42. 42. *Parmas P, Peters J, Doya K, The optimal-baseline estimator is not the optimal baseline-estimator, Information-based induction sciences workshop (IBIS), 2017, 2017.11.10, Tokyo, Japan, poster BibTeX
  43. 43. 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, The 47th annual meeting of Society for Neuroscience, 2017, Washinton D. C., poster BibTeX
  44. 44. Mao Noguchi, So Fujimoto, Akihiko Nikkuni, Yutaka Komura*, Core of neural network for conscious states and percepts in primate, Conscious Research Network, 2017, Taipei, Taiwan, invited BibTeX
  45. 45. *S. Hashimoto, I. Kobayashi, A basic study on action control using deep reinforcement learning, The 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics (IWACIII 2017), 2017, Beijing, China, reviewed BibTeX
  46. 46. Wataru Shimoda*, Keiji Yanai, Predicting segmentation easiness from the consistency for weakly-supervised segmentation, Asian Conference on Pattern Recognition (ACPR), 2017, Nanjing, China, reviewed BibTeX
  47. 47. Takumi Ege*, Keiji Yanai, Estimating food calories for multiple-dish food photos, Asian Conference on Pattern Recognition (ACPR), 2017, Nanjing, China, reviewed# BibTeX
  48. 48. *Hikida T, Neuronal circuit mechanisms in reward and aversive behavior, Taiwan-Japan Biomedicine Conference NTHU-OU bilateral symposium 2017, 2017, invited BibTeX
  49. 49. *Masumori, A., Maruyama, N., Mita, T., Bakkum, D., Frey, U., Takahashi, H.,& Ikegami, T, Learning by Stimulation Avoidance in Cultured Neuronal Cells, The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics(SWARM 2017), 2017, 京都, reviewed, oral BibTeX
  50. 50. *Maruyama, N., Hashimoto, Y., Mototake, Y., Saito, D., & Ikegami, T, Revisiting Classification of Large Scale Flocking, The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics(SWARM 2017), 2017, 京都, reviewed BibTeX
  51. 51. *Hashimoto, Y., Ikegami, T, Novelty production in tagging crowds, The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics(SWARM 2017), 2017, 京都, reviewed BibTeX
  52. 52. Tadahiro Taniguchi, Symbol Emergence in Robotics:Representation Learning for Real-world Communication and Collaboration, International Field Robotics Forum 2017, 2017, Seoul, Korea, keynote BibTeX
  53. 53. Tanno, T., Horie, K., Izawa, J. and Morita, M, Robustness of Selective Desensitization Perceptron Against Irrelevant and Partially Relevant Features in Pattern Classification, In International Conference on Neural Information Processing, 2017 BibTeX
  54. 54. *Reinke C, Uchibe E, Doya K, Average Reward Optimization with Multiple Discounting Reinforcement Learners, ICONIP (Lecture Notes in Computer Science), 2017, 2017.10.24, Guangzhou, China, oral BibTeX
  55. 55. Doya K, Artificial Intelligence and Brain Science, Seminar, 2017, 2017.10.19, Kyungpook National University, Daegu, Korea, seminar BibTeX
  56. 56. Hidehiko Takahashi, Altered decision-making as endophenotypes to bridge the gap between phenomenology and neurobiology, 2017, Sapporo, invited BibTeX
  57. 57. Takanori Uka, Neural mechanism of flexible sensory decision making, The 12th Biennial Conference of Chinese Neuroscience Society, 2017, Tianjin, CHINA, invited BibTeX
  58. 58. *Uchibe E, Deep inverse reinforcement learning, 3rd International Workshop on Intrinsically Motivated Open-ended learning, 2017, Rome, Italy, oral, invited BibTeX
  59. 59. Masamichi Sakagami, Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum, The 44th Naito Conference on Decision Making in the Brain-Motivation, Prediction, and Learning, 2017, Sapporo, invited BibTeX
  60. 60. *Yoshizawa T, Ito M, Doya K, Coding of value information in the striatal striosome compartment, 44th Naito Conference, 2017, 2017.10.4, CHÂTERAISÉ Gateaux Kingdom SAPPORO, Japan, poster BibTeX
  61. 61. Macpherson T, *Hikida T, Nucleus accumbens dopamine D1-receptor-expresing neurons control Pavlovian approach behaviour, The 44th Naito Conference, Decision Making in the Brain -Motivation, Prediction, and Learning, 2017, poster BibTeX
  62. 62. Ikegami, T, THE FUTURE OF AI IN THE ARTS , Japan Foundation Sydeny, 2017, Sydney, Australia, invited BibTeX
  63. 63. Takufumi Yanagisawa, BMI robotic hand controls phantom limb pain, Yamada Symposium 2017 on neuroimaging of natural behaviors, 2017, Ookayama, Japan, invited BibTeX
  64. 64. Takumi Ege*, Keiji Yanai, Image-based food calorie estimation using knowledge on food categories, ingredients and cooking directions, ACM Multimedia Thematic Workshops on Understanding, 2017, Mountain View, CA, USA, reviewed# BibTeX
  65. 65. Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi, and Tetsunari Inamura, SpCoSLAM: Online Multimodal Place Categorization, Spatial Lexical Acquisition and Mapping by a Mobile Robot, 2nd Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics (ML-HLCR 2017), 2017, Vancouver, Canada, reviewed BibTeX
  66. 66. *Masashi HAMAYA, Takamitsu MATSUBARA, Tomoyuki NODA,Tatsuya TERAMAE,Jun MORIMOTO, User-robot collaborative excitation for PAM model identification in exoskeleton robots, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2017), 2017, Vancouver, Canada, reviewed# BibTeX
  67. 67. Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi and Tetsunari Inamura, Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017, Vancouver, Canada, reviewed BibTeX
  68. 68. Y. Miyuki, Y. Hagiwara, *T. Taniguchi, Unsupervised learning for spoken word production based on simultaneous word and phoneme discovery without transcribed data, IEEE International Conference on Development and Learning and the International Conference on Epigenetic Robotics (ICDL-EpiRob2017), 2017, Lisbon, Portugal, reviewed BibTeX
  69. 69. Y. Tada, Y. Hagiwara, *T. Taniguchi, Comparative study of feature extraction methods for direct word discovery with npb-daa from natural speech signals, IEEE International Conference on Development and Learning and the International Conference on Epigenetic Robotics (ICDL-EpiRob2017), 2017, Lisbon, Portugal, reviewed BibTeX
  70. 70. Hayakawa T, Fukai T, Interplay of microscopic and macroscopic dynamics in randomly connected neuronal networks. , Bernstein Conference 2017, 2017, Goettingen, Germany BibTeX
  71. 71. Inoue K, Pathway-selective manipulation of neural circuits, NIMH Workshop “Neural Circuits: Gaps and Opportunities”, 2017, Bethesda, USA, invited BibTeX
  72. 72. *Sinapayen, L., & Ikegami, T, Online fitting of computational cost to environmental complexity: Predictive coding with the ε-network, 14th European Conference on Artificial Life(ECAL2017), 2017, Lyon, France, reviewed BibTeX
  73. 73. *Hiroki Kojima,Takashi Ikegami, VAEGAN as a New Perception Model, ECAL, Late-Breaking, 2017, Lyon, France, reviewed BibTeX
  74. 74. *Masumori, A., Sinapayen, L., & Ikegami, T, Learning by Stimulation Avoidance Scale to Large Neural Networks, 14th European Conference on Artificial Life, 14th European Conference on Artificial Life(ECAL2017), 2017, Lyon, France, reviewed, oral BibTeX
  75. 75. *Doi, I., Ikegami, T., Masumori, A., Kojima, H., Ogawa K., & Ishiguro, H, A new design principle for an autonomous robot, 14th European Conference on Artificial Life(ECAL2017), 2017, Lyon, France, reviewed, poster BibTeX
  76. 76. *Lana Sinapayen, Takashi Ikegami, Online fitting of computational cost to environmental complexity: Predictive coding with the ε-network, Proc of the 14th European Conference on Artificial Life (ECAL2017), 2017, Lyon, France, oral BibTeX
  77. 77. *Nakahara H, Reinforcement learning with environmental structures and mind of others, The 11th International Conference on Cognitive Science (ICCS 2017), 2017, Taipei, Taiwan, oral, invited BibTeX
  78. 78. Akihiko Nikkuni, Yutaka Komura*, Self-evaluation in vision in monkeys and humans, ICCS, 2017, Taipei, Taiwan, invited BibTeX
  79. 79. Macpherson T, *Hikida T, Nucleus accumbens dopamine D1-receptor-expresing neurons control attribution of incentive salience in an autoshaping task, EBPS Biennial meeting 2017, 2017, poster BibTeX
  80. 80. Takumi Ege*, Keiji Yanai, Comparison of two approaches for direct food calorie estimation, International Workshop on Multimedia Assisted Dietary Management (MADIMA), 2017, Catania, Italy, reviewed# BibTeX
  81. 81. Ikegami, T, Passive Touch, Stimulus Avoidance, and the Android “Alter”, International Society for Theoretical Psychology (2017/8/21-25), 2017, Tokyo, Japan, invited BibTeX
  82. 82. Doya K, Reinforcement learning: basic concepts and recent advances, Workshop on “Human & Machine Learning”, 2017, 2017.8.16-18, Beijing Institute of Technology, China, invited BibTeX
  83. 83. Doya K, Neural mechanisms of reinforcement learning and mental simulation, Workshop on “Human & Machine Learning”, 2017, 2017.8.16-18, Beijing Institute of Technology, China, invited BibTeX
  84. 84. 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, ECCN, 2017, Budapest, invited BibTeX
  85. 85. Mimura K, Sato C, Matsumoto J, Aoki I, Ichinohe N, Suhara T, *Minamimoto T, Atypical Behavioral and Neural Phenotypes in a Common Marmoset Model of Autism Spectrum Disorder, 2017, Yokohama, Japan, invited BibTeX
  86. 86. Doya K, Decoding the contents of mental simulation, Neuroscience 2017 Sattelite Symposium: Computational Principles of the Nervous System, 2017, 2017.7.24, University of Tokyo, Tokyo, invited BibTeX
  87. 87. Doya K, Neural coding, brain imaging and information extraction by circuit modeling, Neuroscience 2017 Sattelite Symposium / CREST Symposium, 2017, invited BibTeX
  88. 88. Asabuki T, Hiratani N, Fukai T, Chunking by mutual supervision in reservoir computing., Topical Problems of Nonlinear Wave Physics (NWP-2017) – Nonlinear Dynamics and Complexity (NWP-1), 2017, Moscow-St. Petersburg, Russia, invited BibTeX
  89. 89. Tohru Kurotani, Toshiki Tani, Kazuhisa Sakai, Naoto Kitamura, Hiroshi Abe, Misako Komatsu, Noritaka Ichinohe, Intrinsic functional connectivity in cortical area 24 of the common marmoset investigated by optical mapping, The 40nd Annual Meeting of the Japan Neuroscience Society, 2017, Chiba, poster BibTeX
  90. 90. Doya K, Exploring the deep brain network for reinforcement learning, Neuroscience 2017; 40th Annual Meeting of the Japan Neuroscience Society; Luncheon Seminar: From mouse to monkey: illuminating neural circuits in action, 2017, 2017.7.21, Makuhari Messe, Chiba, invited BibTeX
  91. 91. Misako Komatsu, Eriko Sugano, Noritaka Ichinohe, Hiroshi Tomita, Naotaka Fujii, Whole-cortical recordings reveal spreading photo-stimulation effects: A optogenetics study in marmosets, The 40nd Annual Meeting of the Japan Neuroscience Society, 2017, Chiba, poster BibTeX
  92. 92. Hamaguchi K, Tanaka M, *Mooney R, Brain cooling and intracellular recording in singing birds revealed distributed coding of song timing,, The 40th Annual Meeting of the Japan Neuroscience Society, 2017, Makuhari, Japan, poster BibTeX
  93. 93. 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, The 40th Annual Meeting of the Japan Neuroscience Society, 2017, Ciba, Japan, poster BibTeX
  94. 94. 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, The 40th Annual Meeting of the Japan Neuroscience Society, 2017, Ciba, Japan, poster BibTeX
  95. 95. 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, The 40th Annual Meeting of the Japan Neuroscience Society, 2017, Chiba BibTeX
  96. 96. *Tanaka K, Object recognition in inferotemporal cortex: from visual features to semantics, 2017, invited plenary lecture BibTeX
  97. 97. *Benucci A., Plasticity for stimulus selectivity in the visual cortex of adult mice induced by patterned optogenetic stimulation, Asia Pacific Conference on Vision, 2017, Tainan, Taiwan, Invited talk BibTeX
  98. 98. *Uchibe E, Doya K, Model-free deep inverse reinforcement learning by logistic regression, Proc. of the 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making, 2017, reviewed# BibTeX
  99. 99. Doya K, What should we further learn from the brain?, Brain-AI Workshop, 2017, 2017.7.7, NYU Shanghai, Shanghai, China, invited BibTeX
  100. 100. *Nakahara H, Learning to make reward-guided decisions: sequential, successive, and social, 2017 Brain-AI Workshop, 2017, Shanghai, China, oral, invited BibTeX
  101. 101. Doya K, What should we further learn from the brain?, Korean AI Flagship Project Workshop, 2017, 2017.7.3, Kyungpook National University, Daegu, Korea, invited BibTeX
  102. 102. *Tanaka K, Object recognition in inferotemporal cortex: from visual features to semantics, 2017, invited plenary lecture BibTeX
  103. 103. *M. Shirasuna, H. Honda, T. Matsuka, K. Ueda, Familiarity-matching in decision making: experimental studies on cognitive processes and analyses of its ecological rationality, the 39th Annual Conference of the Cognitive Science Society(COGSCI2017), 2017, London, UK, reviewed BibTeX
  104. 104. *H. Honda, T. Matsuka, K. Ueda, Decisions based on verbal probabilities: decision bias or decision by sampling?, the 39th Annual Conference of the Cognitive Science Society(COGSCI2017), 2017, London, UK, reviewed BibTeX
  105. 105. Shin Matsuo, Wataru Shimoda*, Keiji Yanai, Partial style transfer using weakly-supervised semantic segmentation, ICME Workshop on Multimedia Artworks Analysis (MMArt), 2017, Hong Kong, reviewed BibTeX
  106. 106. 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., Cold Spring Harbor Asia Conference: Primate Neuroscience, 2017, 蘇州市, 中華人民共和国, poster BibTeX
  107. 107. Macpherson T, *Hikida T, Nucleus accumbens dopamine D1-receptor-expresing neurons control incentive salience to reward-predictive cues, IBNS2017, 2017, invited BibTeX
  108. 108. *Hikida T, Morita M, Macpherson T, D2L receptor-expressing striatal neurons control visual discrimination learning in a touchscreen operant system, IBNS2017, 2017, oral BibTeX
  109. 109. Ishida H, Inoue K, Hoshi E, Takada M, Cells of origin of multisynaptic projections from amygdala to ventral premotor cortex in macaques, Different elements of Primate Neural Networks in the Connectome Era, 2017, Sicily, Italy, poster BibTeX
  110. 110. Masamichi Sakagami, Categorical coding of stimulus and inference of the value in the monkey lateral prefrontal cortex, Max Pranck Institute Germany招聘講演, 2017, Germany, invited BibTeX
  111. 111. Shinomoto S, Inferring the source of fluctuation in neuronal activity, ICERM on Integrating Dynamics and Statistics in Neuroscience (2017/6/19-8/11), 2017, Providence, USA, invited BibTeX
  112. 112. *Reinke C, Uchibe E, Doya K, Fast Adaptation of Behavior to Changing Goals with a Gamma Ensemble, 3rd Multidisciplinary conference on reinforcement learning and decision making, 2017, 2017.6.12, University of Michigan, Ann Arbor, Michigan, USA, poster BibTeX
  113. 113. 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, 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2017), 2017, Michigan, USA, poster BibTeX
  114. 114. *Koji ISHIHARA,Jun-ichiro FURUKAWA,Jun MORIMOTO, A forward and inverse optimal control framework to generate humanoid robot movements with hierarchical MPC, 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making(RLDM2017), 2017, Michigan, USA, reviewed# BibTeX
  115. 115. Tadahiro Taniguchi, Semantic Segmentation of Driving Behavior Data: Double Articulation Analyzer and its Application, The 4th Workshop on Naturalistic Driving Data Analytics, IEEE Intelligent Vehicle 2017 (IV2017), 2017, California, USA, invited BibTeX
  116. 116. Keiji Yanai*, Ryosuke Tanno, Conditional fast style transfer network, ACM International Conference on Multimedia Retrieval (ICMR), 2017, Bucharest, Romania, reviewed BibTeX
  117. 117. *Masashi HAMAYA, Takamitsu MATSUBARA, Tomoyuki NODA,Tatsuya TERAMAE,Jun MORIMOTO, Learning task-parametrized assistive strategies for exoskeleton robots by multi-task reinforcement learning, IEEE International Conference on Robotics and Automation(ICRA2017), 2017, Singapore, reviewed# BibTeX
  118. 118. *Rok Pahic, Jan Babic, Tadej Petric, Luka Peternel, Jun Morimoto, Power-augmentation control approach for arm exoskeleton based on human muscular manipulability, IEEE International Conference on Robotics and Automation(ICRA2017), 2017, Marina Bay Sands, Singapore, reviewed BibTeX
  119. 119. Mimura K, Nakagaki K, *Ichinohe N, Distrbed Vocal Communication in Common Marmoset Family with an Autism-Model Child, 2017, St. Petersburg, Russia, invited BibTeX
  120. 120. *Nakahara H, Neural computations underlying social decision-making, The Seventh International Symposium on “Biology of Decision Making” (SBDM 2017), 2017, Bordeaux, France, oral, invited BibTeX
  121. 121. Masamichi Sakagami, Categorical Coding of Stimulus and Inference of the Value in the Monkey Lateral Prefrontal Cortex, Joint Workshop on AI and Neuroscience, 2017, England BibTeX
  122. 122. Tadahiro Taniguchi, Symbol Emergence in Robotics: Language Acquisition via Real-world Sensorimotor Information, Gatsby-Kaken Joint Workshop on AI and Neuroscience, 2017, London, UK, invited BibTeX
  123. 123. *Nakahara H, Learning to make reward-guided decisions: sequential, successive, and social, Gatsby-Kaken Joint Workshop on AI and Neuroscience, 2017, London, Britain, oral, invited BibTeX
  124. 124. Hidehiko Takahashi, The interface between AI and psychiatry (schizophrenia) research, Gatsby-Kaken Joint Workshop on AI and Neuroscience, 2017, London, UK, invited BibTeX
  125. 125. *Jun Morimoto, Motor learning methods for humanoid control, Gatsby-Kakenhi Joint Workshop on AI and Neuroscience, 2017, London, UK, invited BibTeX
  126. 126. Takumi Ege*, Keiji Yanai, Simultaneous estimation of food categories and calories with multi-task CNN, IAPR International Conference on Machine Vision Applications (MVA), 2017, Nagoya, Japan, reviewed BibTeX
  127. 127. *Waggoner RA, Ueno K, Pfeuffer J, Tanaka K, Cheng K, High-resolution fMRI of the visual system at 3T using zoomed excitation via Tx-SENSE, 2017, reviewed poster BibTeX
  128. 128. *Gupta S, Waggoner RA, Tanaka K, Cheng K, Variation of RF-induced temperature increase in a phantom: comparison of numerical simulations, MR thermometry and measurements from temperature sensors, 2017, reviewed poster BibTeX
  129. 129. Haga T, Fukai T, Dendritic computing gives a meso-scopic level framework of brain’s leaning rule. , Forum on Cognitive Neuroscience in Hangzhou, 2017, Hangzhou, China, invited BibTeX
  130. 130. Masamichi Sakagami, The reward prediction error signal of midbrain dopamine neuron is modulated by the cost paid for the reward, The Forum on Cognitive Neuroscience Frontier, 2017, China, invited BibTeX
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