Papers in English

※代表的なものにをつけています

• Ma N, Harasawa N, Ueno K, Cheng K, Nakahara H. (2024) Decision-Making with Predictions of Others' Likely and Unlikely Choices in the Human Brain. The Journal of Neuroscience. 44 (37)e2236232024.
• Langdon A, Botvinick M, Nakahara H, Tanaka K, Matsumoto M, Kanai R. (2022) Meta-learning, social cognition and consciousness in brains and machines. Neural Networks. 145: 80-89.
• Sugiyama M, Nakahara H, Tsuda K.(2019) Legendre decomposition for tensors. Journal of Statistical Mechanics: Theory and Experiment. 2019(12):124017.
• Fukuda H, Ma N, Suzuki S, Harasawa N, Ueno K, Gardner JL, Ichinohe N, Haruno M, Cheng K, Nakahara H. (2019) Computing Social Value Conversion in the Human Brain. Journal of Neuroscience. 39 (26): 5153-5172.
• Sugiyama M, Nakahara H, Tsuda K.(2018) Legendre Decomposition for Tensors. NeurIPS2018. 31: 8825-8835.
• Sugiyama M, Tsuda K, Nakahara H.(2018) Transductive Boltzmann Machines. arxiv.org. arXiv:1805.07938.
• Kass RE, Amari S, Arai K, Brown EN, Diekman CO, Diesmann M, Doiron B, Eden U, Fairhall A, Fiddyment GM, Fukai T, Grun S, Harrison MT, Helias M, Nakahara H, Teramae J, Thomas PJ, Reimers M, Rodu J, Rotstein HG, Shea-Brown E, Shimazaki H, Shinomoto S, Yu BM, Kramer MA.(2018) Computational Neuroscience: Mathematical and Statistical Perspectives. Annual Review of Statistics and Its Application. 5: 183-214.
• Dayan P, Nakahara H.(2018) Models and Methods for Reinforcement Learning. Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Volume 5. Methodology. 507-546.
• Terada S, Sakurai Y, Nakahara H, Fujisawa S.(2017) Temporal and Rate Coding for Discrete Event Sequences in the Hippocampus. Neuron. 94(6): 1248-1262.
• Sugiyama M, Nakahara H, Tsuda K.(2017) Tensor Balancing on Statistical Manifold. ICML2017.
• Sugiyama M, Nakahara H, Tsuda K.(2016) Information Decomposition on Structured Space. IEEE International Symposium on Information Theory 2016. 575-579. (arXiv.org: arXiv:1601.05533 version)
• Kaveri S, Nakahara H. (2014) Dual Reward Prediction Components Yield Pavlovian Sign- and Goal-Tracking. PLOS ONE. 9(10): e108142.
• Nakahara H. (2014) Multiplexing signals in reinforcement learning with internal models and dopamine. Current Opinion in Neurobiology. 25: pp.123-129.
• Kim CH, Tsujino H, Nakahara H. (2013) Reinforcement Learning System based on Heuristics Free State Focusing. Advanced Robotics, 27(10): 749-758.
• Nakahara H, Hikosaka O. (2012) Learning to represent reward structure: a key to adapting to complex environments. Neuroscience Research. 74(3-4): 177–183.
• Nakamura K, Santos GS, Matsuzaki R, Nakahara H. (2012) Differential reward coding in the subdivisions of the primate caudate during an oculomotor task. The Journal of Neuroscience. 32(45): 15963–15982.
• Suzuki S, Harasawa N, Ueno K, Gardner JL, Ichinohe N, Haruno M, Cheng K, Nakahara H. (2012) Learning to simulate others’ decisions. Neuron. 74(6): 1125–1137.
• Santos GS, Nagasaka Y, Fujii N, Nakahara H. (2012) Encoding of social state information by neuronal activities in the macaque caudate nucleus. Social Neuroscience. 7(1): 42–58.
• Yu S, Yang H, Nakahara H, Santos GS, Nikolić D, Plenz D. (2011) Higher-order interactions characterized in cortical activity. The Journal of Neuroscience. 31(48): 17514–17526.
• Nakahara H, Kaveri S. (2010) Internal-time temporal difference model for neural value-based decision making. Neural Computation. 22(12): 3062–3106.
• Bromberg-Martin ES, Matsumoto M, Nakahara H, Hikosaka O. (2010) Multiple timescales of memory in lateral habenula and dopamine neurons. Neuron. 67(3): 499–510.
• Kim C. H, Tsujino H, Nakahara H. [inventor] (2010). Learning control system and learning control method. Pub No. US 2010/0318480 A1 (US Patent; Application No. 12/792853; Application date, 2010.6.3; registration date, 2010.12.16) (Patent)
• Santos GS, Gireesh ED, Plenz D, Nakahara H. (2010) Hierarchical interaction structure of neural activities in cortical slice cultures. The Journal of Neuroscience. 30(26): 8720–8733.
• Kim C. H, Tsujino H, Nakahara H. [inventor] (2009). Learning control system and learning control method. Patent No. 5405252 (Japan Patent; Application No. 2009-217454; Application date, 2009.9.18; registration date, 2013.11.8). (Patent)
• Kim C. H, Tsujino H, Nakahara H. [inventor] (2009). Learning control system and learning control method. Patent No. 5346701 (Japan Patent; Application No. 2009-141680; Application date, 2009.6.12; registration date, 2013.8.23). (Patent)
• Bissmark F, Nakahara H, Doya K, Hikosaka O. (2008) Combining modalities with different latencies for optimal motor control. Journal of Cognitive Neuroscience. 20(11): 1966–1979.
• Plessy C, Fagiolini M, Wagatsuma A, Harasawa N, Kuji T, Asaka-Obam A, Kanzaki Y, Fujishima S, Waki K, Nakahara H, Hensch TK, Carninci P. (2008) A resource for transcriptomic analysis in the mouse brain. PLoS ONE. 3(8): e3012.
• Takenaka K, Nagasaka Y, Hihara S, Nakahara H, Iriki A, Kuniyoshi Y, Fujii N. (2007) Linear discrimination analysis of monkey behavior in an alternative free choice task. Journal of Robotics and Mechatronics. 19(4): 416–422.
• Nakahara H, Nakamura K, Hikosaka O. (2006) Extended LATER model can account for trial-by-trial variability of both pre- and post-processes. Neural Networks. 19(8): 1027–1046.
• Nakahara H, Morita K, Wurtz RH, Optican LM. (2006) Saccade-related spread of activity across superior colliculus may arise from asymmetry of internal connections. Journal of Neurophysiology. 96(2): 765–774.
• Amari S, Nakahara H. (2006) Correlation and independence in the neural code. Neural Computation. 18(6): 1259–1267.
• Hikosaka O, Nakamura K, Nakahara H. (2006) Basal ganglia orient eyes to reward. Journal of Neurophysiology. 95(2): 567–584.
• Nakahara H, Amari S, Richmond BJ. (2006) A comparison of descriptive models of a single spike train by information-geometric measure. Neural Computation. 18(3): 545–568. （long version:Technical Report No.05-1 [PDF(352KB)]）
• Bissmarck F, Nakahara H, Doya K, Hikosaka O. (2005) Responding to modalities with different latencies [PDF(197KB)]. In: Saul K, Weiss Y, Bottou L (Ed.), Advances in Neural Information Processing. 17: 169–176. Cambridge, MA: MIT Press.
• Nelson B, Nishimura S, Kanuka H, KuranagaE, Inoue M, Hori G, Nakahara H, Miura M. (2005) Isolation of gene sets affected specifically by polyglutamine expression: Implication of the TOR signaling pathway in neurodegeneration. Cell Death and Differentiation. 12(8): 1115–1123.
• Amari S, Nakahara H. (2005) Difficulty of singularity in population coding. Neural Computation. 17(4): 839–858.
• Inoue M, Nishimura S, Hori G, Nakahara H, Saito M, Yoshihara Y, Amari S. (2004) Improved parameter estimation for variance-stabilizing transformation of gene-expression microarray data. Journal of Bioinformatics and Computational Biology. 2(4): 669–679.
• Wu S, Amari S, Nakahara H. (2004) Information processing in a neuron ensemble with the multiplicative correlation structure. Neural Networks. 17(2): 205–214.
• Nakahara H, Itoh H, Kawagoe R, Takikawa Y, Hikosaka O. (2004) Dopamine neurons can represent context-dependent prediction error. Neuron. 41(2): 269–280.
• Bissmarck F, Nakahara H, Doya K, Hikosaka O. (2004) Efficient learning of real-time motor skills by parallel policies. IEICE NC, Neurocomputing.104 (140): 23-28.
• Saido T, Nakahara H. (2003) Proteolytic degradation of Aβ by neprilysin and other peptidases. In T Saido (Ed.), Aβ Metabolism and Alzheimer’s Disease. 61–80. Georgetown, TX: Landes Bioscience.
• Kasai H, Matsuzaki M, Noguchi J, Yasumatsu N, Nakahara H. (2003) Structure-stability-function relationships of dendritic spines. Trends in Neurosciences. 26(7): 360–368.
• Nakahara H, Nishimura S, Inoue M, Hori G, Amari S. (2003) Gene interaction in DNA microarray data is decomposed by information geometric measure. Bioinformatics. 19(9): 1124–1131. (long version: Technical Report No.02-6 [PDF(233KB)])
• Itoh H, Nakahara H, Hikosaka O, Kawagoe R, Takikawa Y, Aihara K. (2003) Correlation of primate caudate neural activity and saccade parameters in reward-oriented behavior. Journal of Neurophysiology. 89(4): 1774–1783.
• Amari S, Nakahara H, Wu S, Sakai Y. (2003) Synchronous firing and higher-order interactions in neuron pool. Neural Computation. 15(1): 127–142.
• Bissmarck F, Nakahara H, Doya K, Hikosaka O. (2003) Parallel network mechanisms for motor sequence acquisition in real time. IEICE NC, Neurocomputing. 102(731): 113-118.
• Nakahara H, Amari S. (2002) Information geometric measure for neural spikes. Neural Computation. 14(10): 2269–2316.
• Nakahara H, Amari S, Tatsuno M, Kang S, Kobayashi K. (2002) Examples of applications of information geometric measure to neural data [PDF(467KB)]. RIKEN BSI BSIS Technical Report. No.02-1.
• Nakahara H, Amari S. (2002) Information-geometric decomposition in spike analysis [PDF(1.5MB)]. In TG Dietterich, S Becker, Z Ghahramani (Eds.), Advances in Neural Information Processing Systems. 14: 253–260. Cambridge, MA: MIT Press.
• Wu S, Amari S, Nakahara H. (2002a) Asymptotic behaviors of population codes. Neurocomputing. 44-46: 697–702.
• Wu S, Amari S, Nakahara H. (2002b) Population coding and decoding in a neural field: a computational study. Neural Computation. 14(5): 999–1026.
• Takikawa Y, Kawagoe R, Ito H, Nakahara H, Hikosaka O. (2002) Modulation of saccadic eye movements by predicted reward outcome. Experimental Brain Research. 142(2): 284–291.
• Nakahara H, Amari S, Hikosaka O. (2002) Self-organization in the basal ganglia with modulation of reinforcement signals. Neural Computation. 14(4): 819–844.
• Nakahara H, Amari S. (2002) Attention modulation of neural tuning through peak and base rate in correlated firing. Neural Networks. 15(1): 41-55.
• Hikosaka O, Nakamura K, Sakai K, Nakahara H. (2002) Central mechanisms of motor skill learning. Current Opinion in Neurobiology. 12(2): 217–222.
• Hori G, Inoue M, Nishimura S, Nakahara H. (2002) Blind gene classification: An ICA-based gene classification/clustering method [PDF(258KB)]. RIKEN BSI BSIS Technical Report. No.02-5.
• Nakahara H, Nishimura S, Inoue M, Hori G, Amari S. (2002) Log linear model and gene interaction in DNA microarray data [PDF(324KB)]. RIKEN BSI BSIS Technical Report. No.02-2.
• Yamana M, Nakahara H, Pontil M, Amari S. (2002) Kernel machine ensembles by parallel boosting (in Japanese). IEICE PRMU, Pattern Recognition and Media Understanding. 102 (379): 47-51.
• Nakahara H, Wu S, Amari S. (2001) Attention modulation of neural tuning through peak and base rate. Neural Computation. 13(9): 2031–2047.
• Wu S, Nakahara H, Amari S. (2001) Population coding with correlation and an unfaithful model. Neural Computation. 13(4): 775–797.
• Nakahara H, Doya K, Hikosaka O. (2001) Parallel cortico-basal ganglia mechanisms for acquisition and execution of visuomotor sequences - a computational approach. Journal of Cognitive Neuroscience. 13(5): 626–647.
• Hori G, Nakahara H, Inoue M, Nishimura S. [inventor] (2001) Chemical substance classification apparatus, chemical substance classification method, and program. Patent No.3817161 (Japan Patent; Application No. 2001-339396; Application date, 2001.11.5; registeration date, 2006.6.16). (Patent)
• Wu S, Nakahara H, Murata N, Amari S. (2000) Population decoding based on an unfaithful model. [PDF(74KB)] In SA Solla, TK Leen, and K Mueller (Eds.), Advances in Neural Information Processing Systems. 12: 192–198. Cambridge, MA: MIT Press.
• Hikosaka O, Sakai K, Nakahara H, Lu X, Miyachi K, Nakamura K, Rand MK. (2000) Neural mechanisms for learning of sequential procedures. In MS Gazzaniga (Ed.), The New Cognitive Neurosciences. 553–572. Cambridge, UK: MIT Press.
• Ikeda S, Amari S, Nakahara H. (1999) Convergence of the wake-sleep algorithm. [PDF(82KB)] In MS Kearns, SA Solla, DA Cohn (Eds.), Advances in Neural Information Processing Systems. 11: 239–245. Cambridge, MA: MIT Press.
• Hikosaka O, Nakahara H, Rand MK, Sakai K, Lu X, Nakamura K, Miyachi S, Doya K. (1999) Parallel neural networks for learning sequential procedures. Trends in Neurosciences. 22(10): 464–471.
• Nakahara H, Doya K. (1998) Near-saddle-node bifurcation behavior as dynamics in working memory for goal-directed behavior. Neural Computation. 10(1): 113–132.
• Nakahara H, Doya K, Hikosaka O. (1998) Benefit of multiple representations for motor sequence control in the basal ganglia loops. RIKEN BSI BSIS Technical Report. No.98-5.
• Nakahara H, Doya K, Hikosaka O, Nagano S. (1997) Multiple representations in the basal ganglia loops for sequential decision making [PDF(193KB)]. IEICE NC, Neurocomputing. 97(116), 97-104.
• Nakahara H, Doya, K. (1996) Dynamics of attention as near saddle-node bifurcation behavior. [PDF(1.3MB)] In DS Touretzky, MC Mozer, ME Hasselmo (Eds.), Advances in Neural Information Processing Systems. 8: 38–44. Cambridge, MA: MIT Press.
• Nakahara H. (1996) Finger counting as a calendar: A case of distributed cognition [PDF(262KB)]. In Y. Saeki (Ed.), Reports of Cognitive Processing Studies.No.4. pp.97-108.