PUBLICATIONS
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Year
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International Journal Paper

  1. 1. *Li N+, Wang Y+, Jing F, Zha R, Wei Z, Yang LZ, Geng X, Tanaka K, *Zhang X, A role of the lateral prefrontal cortex in the congruency sequence effect revealed by transcranial direct current stimulation, Psychophysiology, 2021, 58, 5, e13784, reviewed & BibTeX
  2. 2. Taisei Sugiyama, Nicolas Schweighofer, *Jun Izawa, Reinforcement learning establishes a minimal metacognitive process to monitor and control motor learning performance, Nature communications, 2023, 14, 3988, reviewed BibTeX
  3. 3. *Tsuyuzaki, K., Yamamoto, K., Toyoshima, Y., Sato, H., Kanamori, M., Teramoto, T., Ishihara, T., Iino, Y., and Nikaido, I., WormTensor: a clustering method for time-series whole-brain activity data from C. elegans., BMC Bioinformatics, 2023, 24, 254, reviewed BibTeX
  4. 4. *Yoshizawa T, Ito M, Doya K, Neuronal Representation of a Working Memory-Based Decision Strategy in the Motor and Prefrontal Cortico-Basal Ganglia Loops, eNeuro, 2023, 10, 6, 0413-22, reviewed, Open access BibTeX
  5. 5. *Fung Chi Chung Alan、*Fukai Tomoki, Competition on Presynaptic Resources Enhances the Discrimination of Interfering Memories, PNAS Nexus, 2023, 2, 6, online journal BibTeX
  6. 6. *Fung C.C.A, *Fukai T, Competition on Presynaptic Resources Enhances the Discrimination of Interfering Memories, PNAS Nexus, 2023, 2, 6, ad161, online journal BibTeX
  7. 7. *Nishioka T, Attachaipanich S, Hamaguchi K, Lazarus M, de Kerchove d’Exaerde A, *Macpherson T, *Hikida T, Error-related signaling in nucleus accumbens D2 receptor-expressing neurons guides inhibition-based choice behavior in mice, Nature Communications, 2023, 14, 1, 2284, reviewed#& BibTeX
  8. 8. Nishioka, Tadaaki, Attachaipanich, Suthinee, Hamaguchi, Kosuke, Lazarus, Michael, de Kerchove d’Exaerde, Alban, Macpherson, Tom, Hikida, Takatoshi, Error-related signaling in nucleus accumbens D2 receptor-expressing neurons guides inhibition-based choice behavior in mice, Nature Communications, 2023, 14, 2284, reviewed# BibTeX
  9. 9. Nakamura D, *Gomi H, Decoding self-motion from visual image sequence predicts distinctive features of reflexive motor responses to visual motion, Neural Networks, 2023, 162, 516-530, open access: https://doi.org/10.1016/j.neunet.2023.03.020. BibTeX
  10. 10. *Yuya Kobayashi, Masahiro Suzuki, Yutaka Matsuo, Learning global spatial information for multi-view object-centric models, Advanced Robotics, 2023, 37, 8, reviewed BibTeX
  11. 11. *Tomoki Fukai, Computational models of Idling brain activity for memory processing. In NSR special issue “The idling brain in cognition”, Neuroscience Research, 2023, 189, 75-87, review airticle, Epub ahead of print on 2022/12/30 BibTeX
  12. 12. *Fukai T , Computational models of Idling brain activity for memory processing. In NSR special issue “The idling brain in cognition”, Neuroscience Research, 2023, 189, 75-87, review airticle, Epub ahead of print on 2022/12/30 BibTeX
  13. 13. Oguchi M, Li Y, Matsumoto Y, Kiyonari T, Yamamoto K, Sugiura S, Sakagami M*, Proselfs depend more on model-based than model-free learning in a non-social probabilistic state-transition task, Scientific Reports, 2023, 13, 1, reviewed BibTeX
  14. 14. *Abekawa N, Doya K, Gomi H, Body and visual instabilities functionally modulate implicit reaching corrections, iSience, 2023, 26, 1, 105751 BibTeX
  15. 15. Inagaki M, Inoue K, Tanabe S, Kimura K, Takada M, Fujita I, Morphological changes of large layer V pyramidal neurons in cortical motor-related areas after spinal cord injury in macaque monkeys.., Cereb Cortex, 2023, 33, 895-915, reviewed BibTeX
  16. 16. Abekawa N, Doya K, *Gomi H, Body and visual instabilities functionally modulate implicit reaching corrections, iScience, 2023, 26, 1, 105751, DOI:https://doi.org/10.1016/j.isci.2022.105751 BibTeX
  17. 17. *Jun Izawa, Noriyuki Higo, Yumi Murata, Accounting for the valley of recovery during post-stroke rehabilitation training via a model-based analysis of macaque manual dexterity, Frontiers in rehabilitation sciences, 2022, 3, 1042912, reviewed BibTeX
  18. 18. Hamaguchi K, Aoki-Takahashi H, Watanabe D, Prospective and retrospective values integrated in frontal cortex drive predictive choice, Proceedings of the National Academy of Sciences, 2022, 119, e2206067119, reviewed# BibTeX
  19. 19. Cheng, D., Lee, J.S., Brown, M., Ebert, M.S., McGrath, P.T., Tomioka, M., Iino, Y., and *Bargmann, C.I., Insulin/IGF signaling regulates presynaptic glutamate release in aversive olfactory learning, Cell Rep, 2022, 41, 8, 111685, reviewed BibTeX
  20. 20. Tanaka H, Shou Q, Kiyonari T, Matsuda T, Sakagami M, Takagishi H*, Right dorsolateral prefrontal cortex regulates default prosociality preference, Cerebral Cortex, 2022, 33, 1, 5420-5425, reviewed BibTeX
  21. 21. Taisei Sugiyama, Keita Nakae, *Jun Izawa, Transcranial magnetic stimulation on the dorsal premotor cortex facilitates human visuomotor adaptation, NeuroReport, 2022, 33, 16, 723-727, reviewed BibTeX
  22. 22. *Tatsuki Kuribayashi, Yohei Oseki, Ana Brassard, Kentaro Inui, Context limitations make neural language models more human-like, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022, Long Paper, 10421-10436, reviewed BibTeX
  23. 23. *Ryo Yoshida, Yohei Oseki, Composition, attention, or both?, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022, Findings, 5822-5834, reviewed BibTeX
  24. 24. Mabardi, L., Sato, H., Toyoshima, Y., *Iino, Y., and *Kunitomo, H., Different modes of stimuli delivery elicit changes in glutamate driven, experience-dependent interneuron response in C. elegans, Neurosci Res, 2023, 186, 33-42, reviewed BibTeX
  25. 25. Yoshida R, Takamori M, Matsumoto H, *Miura K, Tropical support vector machines: Evaluations and extension to function spaces, Neural Networks, 2022, 157, 77-89, reviewed BibTeX
  26. 26. *Lalande F, Trani A, Predicting the stability of hierarchical triple systems with convolutional neural networks, The Astrophysical Journal, 2022, 938, 18, Research article BibTeX
  27. 27. *Ito S, Kimura T, Gomi H, Attribution of sensory prediction error to perception of muscle fatigue, Scientific Reports, 2022, 12, 1, 16708, https://www.nature.com/articles/s41598-022-20765-9 BibTeX
  28. 28. Fermin ASR*, Kiyonari T, Matsumoto Y, Takagishi H, Li Y, Kanai R, Sakagami M, Akaishi R, Ichikawa N, Takamura M, Yokoyama S, Machizawa MG, Chan HL, Matani A, Yamawaki S, Okada G, Okamoto Y, Yamagishi T, The neuroanatomy of social trust predicts depression vulnerability, Scientific Reports, 2022, 12, 1, reviewed BibTeX
  29. 29. Yihao Wu, Masahiko Morita, *Jun Izawa, Reward prediction errors, not sensory prediction errors, play a major role in model selection in human reinforcement learning, Neural Networks, 2022, 154, 109-121, reviewed BibTeX
  30. 30. *De Havas J, Ito S, Bestmann S, Gomi H, Neural dynamics of illusory tactile pulling sensations, iScience, 2022, 25, 9, 105018, https://linkinghub.elsevier.com/retrieve/pii/S2589004222012901 BibTeX
  31. 31. Lucas Rebelo Dal’Bello, *Jun Izawa, Computational role of exploration noise in error-based de novo motor learning, Neural Networks, 2022, 153, 349-372, reviewed BibTeX
  32. 32. *Tatsuya Matsushima, Yuki Noguchi, Jumpei Arima, Toshiki Aoki, Yuki Okita, Yuya Ikeda, Koki Ishimoto, Shohei Taniguchi, Yuki Yamashita, Shoichi Seto, Shixiang Shane Gu, Yusuke Iwasawa, Yutaka Matsuo., World robot challenge 2020 – partner robot: a data-driven approach for room tidying with mobile manipulator, Advanced Robotics, 2022, 36, 17－18, 850-869, reviewed BibTeX
  33. 33. *Doya K (Guest Editors), Friston K, Sugiyama M,Tenenbaum J, Neural Networks special issue on Artificial Intelligence and Brain Science, Neural Networks, 2022, 155, 328-329, Editorial BibTeX
  34. 34. *Hongjie Bi and Tomoki Fukai, Amplitude-mediated chimera states in nonlocally coupled Stuart-Landau oscillators., Chaos, 2022, 32, 83125, reviewed BibTeX
  35. 35. *Bi H, Fukai T, Amplitude-mediated chimera states in nonlocally coupled Stuart-Landau oscillators., Chaos, 2022, 32, 83125, reviewed BibTeX
  36. 36. *Ozawa T+, Kaseda K+, Ichitani Y, Yamada K, Caffeine facilitates extinction of auditory fear conditioning in rats, Neuropsychopharmacology Reports, 2022, 42, 4, 521-525, reviewed BibTeX
  37. 37. *Rikunari Sagara, Ryo Taguchi, Akira Taniguchi, Tadahiro Taniguchi, Automatic Selection of Coordinate Systems for Learning Relative and Absolute Spatial Concepts, Frontiers in Robotics and AI, 2022, 9 BibTeX
  38. 38. Kei Oyama+, Yukiko Hori+, Koki Mimura+, Yuji Nagai, Mark AG Eldridge, Richard C Saunders, Naohisa Miyakawa, Toshiyuki Hirabayashi, Yuki Hori, Ken-ichi Inoue, Tetsuya Suhara, Masahiko Takada, Makoto Higuchi, Barry J Richmond, Takafumi Minamimoto*, Chemogenetic disconnection between the orbitofrontal cortex and the rostromedial caudate nucleus disrupts motivational control of goal-directed action, Journal of Neuroscience, 2022, 42, 32, 6267-6275, reviewed BibTeX
  39. 39. *Hamasaki Y, Pionnié-Dax N, Dorard G, Tajan N, Hikida T, Preliminary study of the social withdrawal (hikikomori) spectrum in French adolescents: focusing on the differences in pathology and related factors compared with Japanese adolescents, BMC Psychiatry, 2022, 22, 1, 477, reviewed BibTeX
  40. 40. Aomine Y, Sakurai K, Macpherson T, Ozawa T, Miyamoto Y, Yoneda Y, Oka M, *Hikida T, Importin α3 (KPNA3) deficiency augments effortful reward-seeking behavior in mice, Frontiers in Neuroscience, 2022, 16, 905991, reviewed BibTeX
  41. 41. *Macpherson T+, Kim JY+ and *Hikida T, Nucleus accumbens core dopamine D2 receptor-expressing neurons control reversal learning but not set-shifting in behavioral flexibility in male mice, Frontiers in Neuroscience, 2022, 16, 885380, reviewed BibTeX
  42. 42. *Suzuki S, Takeda S, Makishima N, Ando A, Shouno H, Knowledge Transferred Fine-Tuning: Convolutional Neural Network Is Born Again With Anti-Aliasing Even in Data-Limited Situations, IEEE Access, 2022, 10, 68384-68396 BibTeX
  43. 43. *Toshitake Asabuki, Prajakta Kokate and Tomoki Fukai, Neural circuit mechanisms of hierarchical sequence learning tested on large-scale recording data., PLOS Computational Biology, 2022, 18, e1010214, reviewed BibTeX
  44. 44. *TAsabuki T, Kokate P, Fukai T, Neural circuit mechanisms of hierarchical sequence learning tested on large-scale recording data., PLOS Computational Biology, 2022, 18, e1010214, reviewed BibTeX
  45. 45. Hiroki, S., Yoshitane, H., Mitsui, H., Sato, H., Umatani, C., Kanda, S., Fukada, Y., and *Iino, Y., Molecular encoding and synaptic decoding of context during salt chemotaxis in C. elegans, Nat Commun, 2022, 13, 1, e2928, reviewed BibTeX
  46. 46. Oguchi M, Sakagami M*, Dissecting the Prefrontal Network With Pathway-Selective Manipulation in the Macaque Brain—A Review, Frontiers in Neuroscience, 2022, 16, reviewed BibTeX
  47. 47. *Doya K, Ema A, Kitano H, Sakagami M, Russell S, Social impact and governance of AI and neurotechnologies, Neural Networks, 2022, 152, 542-554, Perspective article BibTeX
  48. 48. *Abekawa N, Ito S, Gomi H, Gaze-specific motor memories for hand-reaching, Current Biology, 2022, S0960982222007011., open access: https://doi.org/10.1016/j.cub.2022.04.065 BibTeX
  49. 49. Doya, K*., Ema, A., Kitano, H., Sakagami, M. Russell, S., Social impact and governance of AI and neurotechnologies, Neural Networks, 2022, 152, 542-554, reviewed BibTeX
  50. 50. Mori, K., Koebis, M., Nakao, K., Kobayashi, S., Kiyama, Y., Watanabe, M., Manabe, T., Iino, Y., and *Aiba, A., Loss of calsyntenin paralogs disrupts interneuron stability and mouse behavior, Mol Brain, 2022, 15, 1, 23, reviewed BibTeX
  51. 51. Uchida Y, *Hikida T, *Yamashita Y, Computational mechanisms of osmoregulation: a reinforcement learning model for sodium appetite, Frontiers in Neuroscience, 2022, 16, 857009, reviewed&# BibTeX
  52. 52. *Giorgia Dellaferrera, Toshitake Asabuki and Tomoki Fukai, Modeling the Repetition-based Recovering of Acoustic and Visual Sources with Dendritic Neurons., Frontiers in Neuroscience, 2022, 16, 855753, reviewed BibTeX
  53. 53. *Dellaferrera G, Asabuki T, Fukai T, Modeling the Repetition-based Recovering of Acoustic and Visual Sources with Dendritic Neurons., Frontiers in Neuroscience, 2022, 16, 855753, reviewed BibTeX
  54. 54. Matsuo Y, Lecun Y, Sahani M, Precup D, Silver D, Sugiyama M, Uchibe E, *Morimoto, J, Deep learning, reinforcement learning, and world models, Neural Networks, 2022, 152, 267-275, reviewed BibTeX
  55. 55. *Ito J, Joana C, Yamane Y, Fujita I, Tamura H, Maldonado P, Grün S, Latency shortening with enhanced sparseness and responsiveness in V1 during active visual sensing, Scientific Reports, 2022, 12, 6021, Research BibTeX
  56. 56. *Akira Taniguchi, Ayako Fukawa, Hiroshi Yamakawa, Hippocampal formation-inspired probabilistic generative model, Neural Networks, 2022, 151, 317-335, https://doi.org/10.1080/01691864.2022.2029762 BibTeX
  57. 57. Ike, Y., *Tomioka, M., and *Iino, Y., Involvement of HECT-type E3 ubiquitin ligase genes in salt chemotaxis learning in Caenorhabditis elegans, Genetics, 2022, 220, 4, iyac025, reviewed BibTeX
  58. 58. *Fehring DJ, Pascoe AJ, Haque ZZ, Samandra R, Yokoo S, Abe H, Rosa MGP, Tanaka K, Yamamori T, Mansouri FA., Dimension of visual information interacts with working memory in monkeys and humans, Scientific Report, 2022, 12, 1, 5335, reviewed BibTeX
  59. 59. *Tadahiro Taniguchi, Hiroshi Yamakawa, Takayuki Nagai, Kenji Doya, Masamichi Sakagami, Masahiro Suzuki, Tomoaki Nakamura, Akira Taniguchi, A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots, Neural Networks, 2022, 150, 293-312, https://doi.org/10.1016/j.neunet.2022.02.026 BibTeX
  60. 60. Nishina K, Shou Q, Takahashi H, Sakagami M, Inoue-Murayama M, Takagishi H*, Association Between Polymorphism (5-HTTLPR) of the Serotonin Transporter Gene and Behavioral Response to Unfair Distribution, Frontiers in Behavioral Neuroscience, 2022, 16, reviewed BibTeX
  61. 61. Hiroyuki Miyawaki, Kenji Mizuseki, De novo inter-regional coactivations of preconfigured local ensembles support memory, Nature Communications, 2022, 13, 1, 1272 BibTeX
  62. 62. *Taniguchi T, Yamakawa H, Nagai T, Doya K, Sakagami M, Suzuki M, Nakamura T, Taniguchi A, A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots, Neural Networks, 2022, 150, 293-312, Review BibTeX
  63. 63. *Masahiro Suzuki, Yutaka Matsuo, A survey of multimodal deep generative models, Advanced Robotics, 2022, 36, 261–278, reviewed BibTeX
  64. 64. Umeda R, Teranishi H, Hada K, Shimizu N, Shiraishi H, Shaohong L, Shide M, Higa R, Shikano K, Shin T, Mimata H, Hikida T, Hanada T, *Hanada R., Vrk2 deficiency elicits aggressive behavior in female zebrafish, Genes to Cells, 2022, 27, 4, 254-265, reviewed BibTeX
  65. 65. Jaaro-Peled H, Kumar S, Hughes D, Sumitomo A, Kim S-H, Zoubovsky S, Hirota-Tsuyada Y, Zala D, Bruyere J, Katz B, Huang B, Flores R, Narayan S, Hou Z, Economides A, Hikida T, Wetsel W, Deisseroth K, Mori S, Brandon N, Tanaka M, Ishizuka K, Houslay M, Saudou F, *Dzirasa K, *Sawa A, *Tomoda T, Regulation of sensorimotor gating via Disc1/Huntingtin-mediated Bdnf transport in the cortico-striatal circuit, Molecular Psychiatry, 2022, 27, 3, 1805-1815, reviewed BibTeX
  66. 66. *Yuki Katsumata, Akinori Kanechika, Akira Taniguchi, Lotfi El Hafi, Yoshinobu Hagiwara, and Tadahiro Taniguchi, Map completion from partial observation using the global structure of multiple environmental maps, Advanced Robotics, 2022, 36, 279-290, DOI: 10.1080/01691864.2022.2029762 BibTeX
  67. 67. *Ryo Yoshida, Yohei Oseki, Learning argument structures with recurrent neural network grammars, Proceedings of the Society for Computation in Linguistics (SCiL), 2022, Long Paper, 101-111, reviewed BibTeX
  68. 68. Hiroki, S., and Iino, Y., The redundancy and diversity between two novel PKC isotypes that regulate learning in Caenorhabditis elegans, Proc Natl Acad Sci U S A, 2022, 119, 3, e2106974119, reviewed BibTeX
  69. 69. *Matsumoto M, Abe H, Tanaka K, Matsumoto K, Different types of uncertainty distinguished by monkey prefrontal neurons, Cerebral Cortex Communications, 2022, 3, 1-17, reviewed BibTeX
  70. 70. *Tomioka, M., Jang, M.S., and Iino, Y., DAF-2c signaling promotes taste avoidance after starvation in Caenorhabditis elegans by controlling distinct phospholipase C isozymes, Commun Biol, 2022, 5, 1, 30, reviewed BibTeX
  71. 71. *Mansouri FA, Buckley MJ, Tanaka K, The neural substrate and underlying mechanisms of executive control fluctuations in primates, Progress in Neurobiology, 2022, 209, 102216, reviewed BibTeX
  72. 72. Ide, S., Kunitomo, H., Iino, Y., and Ikeda, K., Caenorhabditis Elegans Exhibits Morphine Addiction-like Behavior via the Opioid-like Receptor NPR-17, Front Pharmacol, 2022, 12, 802701, reviewed BibTeX
  73. 73. *Onitsuka T, Hirano Y, Nemoto K, Hashimoto N, Kushima I, Koshiyama D, Koeda M, Takahashi T, Noda Y, Matsumoto J, Miura K, Nakazawa T, Hikida T, Kasai K, Ozaki N, *Hashimoto R, Trends in big data analyses by multicenter collaborative translational research in psychiatry, Psychiatry and Clinical Neurosciences, 2022, 76, 1, 1-14, reviewed BibTeX
  74. 74. Rikunari Sagara, *Ryo Taguchi, Akira Taniguchi, Tadahiro Taniguchi,Koosuke Hattori, Masahiro Hoguro, Taizo Umezaki, Unsupervised lexical acquisition of relative spatial concepts using spoken user utterances, Advanced Robotics, 2022, 36, 1-2, 54-70, reviewed BibTeX
  75. 75. Takeshi D. Itoh, Takatomi Kubo, Kazushi Ikeda, Multi-level attention pooling for graph neural networks: Unifying graph representations with multiple localities, Neural Networks, 2022, 145, 356-373, reviewed BibTeX
  76. 76. *Shingo Shimoda, Lorenzo Jamone, Dimitri Ognibene, Takayuki Nagai, Alessandra Sciutti, Alvaro Costa-Garcia, Yohei Oseki, Tadahiro Taniguchi, What is the role of the next generation of cognitive robotics?, Advanced Robotics, 2022, 36, 3-16, reviewed BibTeX
  77. 77. Sato, H., Kunitomo, H., Fei, X., Hashimoto, K., and *Iino, Y., Simultaneous recording of behavioral and neural responses of free-moving nematodes, STAR Protoc, 2021, 2, 4, 101011, reviewed BibTeX
  78. 78. Ryota Ishikawa, Saho Ayabe-Kanamura, *Jun Izawa, The role of motor memory dynamics in structuring bodily self-consciousness, Iscience, 2021, 24, 12, 103511, reviewed BibTeX
  79. 79. *Tomoki Fukai, Toshitake Asabuki and Tatsuya Haga, Neural mechanisms for learning hierarchical structures of information., Current Opinion in Neurobiology, 2021, 70, 145-153, reviewed BibTeX
  80. 80. *Fukai T, Asabuki T, Haga T, Neural mechanisms for learning hierarchical structures of information., Current Opinion in Neurobiology, 2021, 70, 145-153, reviewed BibTeX
  81. 81. *Hirai S, Miwa H, Tanaka T, Toriumi K, Kunii Y, Shimbo H, Sakamoto T, Hino M, Izumi R, Nagaoka A, Yabe H, Nakamachi T, Shioda S, Dan T, Miyata T, Nishito Y, Suzuki K, Miyashita M, Tomoda T, Hikida T, Horiuchi J, Itokawa M, Arai M, *Okado H, High Sucrose Diets Contribute to Brain Angiopathy with Impaired Glucose Uptake, and Psychosis-related Higher Brain Dysfunctions in Mice, Science Advances, 2021, 7, 46, eabl6077, reviewed BibTeX
  82. 82. Sakurai K, Itou T, Morita M, Kasahara E, Moriyama T, Macpherson T, Ozawa T, Miyamoto Y, Yoneda Y, Sekiyama A, Oka M, *Hikida T, Effects of Importin α1/KPNA1 deletion and adolescent social isolation stress on psychiatric disorder-associated behaviors in mice, PLoS ONE, 2021, 16, 11, e0258364, reviewed# BibTeX
  83. 83. *Takamuku S, Gomi H, Vision-based speedometer regulates human walking, iScience, 2021, 24, 12, 103390, https://www.sciencedirect.com/science/article/pii/S2589004221013614 BibTeX
  84. 84. *Langdon A, Botvinick M, Nakahara H, Tanaka K, Matsumoto M, Kanai R, Meta-learning, social cognition and consciousness in brains and machines, Neural Networks, 2021, 145, 80-89, reviewed BibTeX
  85. 85. Mori, K., Yamauchi, N., Wang, H., Sato, K., Toyoshima, Y., and *Iino, Y., Probabilistic generative modeling and reinforcement learning extract the intrinsic features of animal behavior, Neural Netw, 2021, 145, 107-120, reviewed BibTeX
  86. 86. Macpherson T, Matsumoto M, Gomi H, Morimoto J, Uchibe E, *Hikida T, Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control, Neural Networks, 2021, 144, 507-521, reviewed# BibTeX
  87. 87. Macpherson T, Churchland A, Sejnowski A, DiCarlo J, Kamitani Y, Takahashi H, *Hikida T, Natural and Artificial Intelligence: a brief introduction to the interplay between AI and neuroscience research, Neural Networks, 2021, 144, 603-613, reviewed# BibTeX
  88. 88. Tanaka S, Taylor JE, Sakagami M*, The effect of effort on reward prediction error signals in midbrain dopamine neurons, Current Opinion in Behavioral Sciences, 2021, 41, 152-159, reviewed BibTeX
  89. 89. Lucas Rebelo Dal’Bello, *Jun Izawa, Task-relevant and task-irrelevant variability causally shape error-based motor learning, Neural Networks, 2021, 142, 583-596, reviewed BibTeX
  90. 90. Macpherson T, Churchland A, Sejnowski A, DiCarlo J, Kamitani Y, Takahashi H, *Hikida T, Natural and Artificial Intelligence: a brief introduction to the interplay between AI and neuroscience research, Neural Networks, 2021, 144, 603-613, reviewed#& BibTeX
  91. 91. Mimura K, Nagai Y, Inoue K, Matsumoto J, Hori Y, Sato C, Kimura K, Okauchi T, Hirabayashi T, Nishijyo H, Yahata N, Takada M, Suhara T, Higuchi M, *Minamimoto T, Chemogenetic activation of nigrostriatal dopamine neurons in freely moving common marmosets., iScience, 2021, 24, 103066, reviewed BibTeX
  92. 92. Koki Mimura, Yuji Nagai, Ken-ichi Inoue, Jumpei Matsumoto, Yukiko Hori, Chika Sato, Kei Kimura, Takashi Okauchi, Toshiyuki Hirabayashi, Hisao Nishijo, Noriaki Yahata, Masahiko Takada, Tetsuya Suhara, Makoto Higuchi, Takafumi Minamimoto*, Chemogenetic activation of nigrostriatal dopamine neurons in freely moving common marmosets, iScience, 2021, 24, 9, 103066, reviewed&# BibTeX
  93. 93. *Hamasaki Y, Pionnié-Dax N, Dorard G, Tajan N, Hikida T, Identifying Social Withdrawal (Hikikomori) Factors in Adolescents: Understanding the Hikikomori Spectrum, Child Psychiatry & Human Development, 2021, 52, 5, 808-817, reviewed BibTeX
  94. 94. Karl Friston, Rosalyn J. Moran, Yukie Nagai, Tadahiro Taniguchi, *Hiroaki Gomi, Josh Tenenbaum, World model learning and inference, Neural Networks, 2021, 144, 573-590, https://doi.org/10.1016/j.neunet.2021.09.011 BibTeX
  95. 95. Ozawa T+, Itokazu T+, Ichitani Y, *Yamada K, Pharmacologically induced N-methyl-D-aspartate receptor hypofunction impairs goal-directed food seeking in rats, Neuropsychopharmacology Reports, 2021, 41, 4, 526-531, reviewed BibTeX
  96. 96. *Doya K, Canonical cortical circuits and the duality of Bayesian inference and optimal control, Current Opinion in Behavioral Sciences, 2021, 41, 160-167, Review BibTeX
  97. 97. Morisaki I, Shiraishi H, Fujinami H, Shimizu N, Hikida T, Arai Y, Kobayashi T, Hanada R, Penninger JM, Fujiki M, *Hanada T, Modeling a human CLP1 mutation in mouse identifies an accumulation of tyrosine pre-tRNA fragments causing pontocerebellar hypoplasia type 10, Biochemical and Biophysical Research Communications, 2021, 570, 60-66, reviewed BibTeX
  98. 98. Macpherson T, Matsumoto M, Gomi H, Morimoto J, Uchibe E, *Hikida T, Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control, Neural Networks, 2021, 144, 507-521, reviewed#& BibTeX
  99. 99. Macpherson T, Matsumoto M, Gomi H, Morimoto J, Uchibe E, *Hikida, T, Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control, Neural Networks, 2021, 144, 507-521, reviewed BibTeX
  100. 100. Oguchi M, Tanaka S, Pan X, Kikusui T, Moriya-Ito K, Kato S, Kobayashi K, Sakagami M*, Chemogenetic inactivation reveals the inhibitory control function of the prefronto-striatal pathway in the macaque brain, Communications Biology, 2021, 4, 1, reviewed BibTeX
  101. 101. *Miyazaki K, Miyazaki KW, Increased serotonin prevents compulsion in addiction, Science, 2021, 373, 1197-1198, Commentry BibTeX
  102. 102. Yeh LF+, Ozawa T+, *Johansen JP, Functional organization of the midbrain periaqueductal gray for regulating aversive memory formation, Molecular Brain, 2021, 14, 1, 136, reviewed BibTeX
  103. 103. Abekawa N, Diedrichsen J, *Gomi H, Gaze control during reaching is flexibly modulated to optimize task outcome, J Neurophysiol., 2021, 126, 3, 816-826, https://journals.physiology.org/doi/10.1152/jn.00134.2021 BibTeX
  104. 104. *Uchibe E, Doya K, Forward and inverse reinforcement learning sharing network weights and hyperparameters, Neural Networks, 2021, 144, 138-153, Research BibTeX
  105. 105. *Suzuki S, Takeda S, Takagi M, Tanida R, Kimata H, Shouno H, Deep Feature Compression Using Spatio-Temporal Arrangement Toward Collaborative Intelligent World, IEEE Transactions on Circuits and Systems for Video Technology, 2021, 32, 6, 3934-3946 BibTeX
  106. 106. Oguchi M, Jiasen J, Yoshioka T, Tanaka YR, Inoue K, Takada M, Kikusui T, Nomoto K, Sakagami M*, Microendoscopic calcium imaging of the primary visual cortex of behaving macaques, Scientific Reports, 2021, 11, 1, reviewed BibTeX
  107. 107. *Tatsuya Haga and *Tomoki Fukai, Multiscale representations of community structures in attractor neural networks., PLOS Computational Biology, 2021, 17, 8, e1009296, reviewed BibTeX
  108. 108. *Haga T, *Fukai T, Multiscale representations of community structures in attractor neural networks., PLOS Computational Biology, 2021, 17, 8, e1009296, reviewed BibTeX
  109. 109. Oguchi M, Jiasen J, Yoshioka TW, Tanaka YR, Inoue K, Takada M, Kikusui T, Nomoto K, *Sakagami M., Microendoscopic calcium imaging of the primary visual cortex of behaving macaques., Sci Rep, 2021, 11, 17021, reviewed BibTeX
  110. 110. *Uchibe E, Doya K, Forward and inverse reinforcement learning sharing network weights and hyperparameters, Neural Networks, 2021, 144, 138-153, reviewed BibTeX
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