| Year |
Citation |
Score |
| 2023 |
Blackwell KT, Doya K. Enhancing reinforcement learning models by including direct and indirect pathways improves performance on striatal dependent tasks. Plos Computational Biology. 19: e1011385. PMID 37594982 DOI: 10.1371/journal.pcbi.1011385 |
0.364 |
|
| 2021 |
Uchibe E, Doya K. Forward and inverse reinforcement learning sharing network weights and hyperparameters. Neural Networks : the Official Journal of the International Neural Network Society. 144: 138-153. PMID 34492548 DOI: 10.1016/j.neunet.2021.08.017 |
0.325 |
|
| 2020 |
Abe Y, Takata N, Sakai Y, Hamada H, Hiraoka Y, Aida T, Tanaka K, Bihan DL, Doya K, Tanaka KF. Diffusion functional MRI reveals global brain network functional abnormalities driven by targeted local activity in a neuropsychiatric disease mouse model. Neuroimage. 117318. PMID 32882386 DOI: 10.1016/j.neuroimage.2020.117318 |
0.749 |
|
| 2020 |
Girard B, Lienard J, Gutierrez CE, Delord B, Doya K. A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection. The European Journal of Neuroscience. PMID 32564449 DOI: 10.1111/ejn.14869 |
0.55 |
|
| 2020 |
Han D, Doya K, Tani J. Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 129: 149-162. PMID 32534378 DOI: 10.1016/j.neunet.2020.06.002 |
0.67 |
|
| 2019 |
Doya K. Neural circuits for reinforcement learning and mental simulation Ibro Reports. 6. DOI: 10.1016/J.Ibror.2019.07.160 |
0.366 |
|
| 2019 |
Doya K, Taniguchi T. Toward evolutionary and developmental intelligence Current Opinion in Behavioral Sciences. 29: 91-96. DOI: 10.1016/J.Cobeha.2019.04.006 |
0.338 |
|
| 2018 |
Miyazaki K, Miyazaki KW, Yamanaka A, Tokuda T, Tanaka KF, Doya K. Reward probability and timing uncertainty alter the effect of dorsal raphe serotonin neurons on patience. Nature Communications. 9: 2048. PMID 29858574 DOI: 10.1038/S41467-018-04496-Y |
0.343 |
|
| 2018 |
Elfwing S, Uchibe E, Doya K. Sigmoid-weighted linear units for neural network function approximation in reinforcement learning. Neural Networks : the Official Journal of the International Neural Network Society. PMID 29395652 DOI: 10.1016/j.neunet.2017.12.012 |
0.42 |
|
| 2018 |
Doya K, Wang D. Fostering deep learning and beyond Neural Networks. 97: iii-iv. DOI: 10.1016/S0893-6080(17)30270-8 |
0.402 |
|
| 2018 |
Kinjo K, Uchibe E, Doya K. Robustness of linearly solvable Markov games employing inaccurate dynamics model Artificial Life and Robotics. 23: 1-9. DOI: 10.1007/S10015-017-0401-2 |
0.343 |
|
| 2017 |
Yoshida K, Shimizu Y, Yoshimoto J, Takamura M, Okada G, Okamoto Y, Yamawaki S, Doya K. Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression. Plos One. 12: e0179638. PMID 28700672 DOI: 10.1371/journal.pone.0179638 |
0.307 |
|
| 2017 |
Wang J, Uchibe E, Doya K. Adaptive Baseline Enhances EM-Based Policy Search: Validation in a View-Based Positioning Task of a Smartphone Balancer. Frontiers in Neurorobotics. 11: 1. PMID 28167910 DOI: 10.3389/fnbot.2017.00001 |
0.334 |
|
| 2017 |
Miyazaki K, Miyazaki K, Doya K. Brain computation mechanism of prediction and decision making by dorsal raphe serotonin neurons. Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica. 149: 34-39. PMID 28049876 DOI: 10.1254/fpj.149.34 |
0.305 |
|
| 2016 |
Funamizu A, Kuhn B, Doya K. Neural substrate of dynamic Bayesian inference in the cerebral cortex. Nature Neuroscience. PMID 27643432 DOI: 10.1038/nn.4390 |
0.324 |
|
| 2016 |
Elfwing S, Uchibe E, Doya K. From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning. Neural Networks : the Official Journal of the International Neural Network Society. 84: 17-27. PMID 27639720 DOI: 10.1016/j.neunet.2016.07.013 |
0.366 |
|
| 2016 |
Fermin AS, Yoshida T, Yoshimoto J, Ito M, Tanaka SC, Doya K. Model-based action planning involves cortico-cerebellar and basal ganglia networks. Scientific Reports. 6: 31378. PMID 27539554 DOI: 10.1038/srep31378 |
0.547 |
|
| 2016 |
Sharpee TO, Destexhe A, Kawato M, Sekulić V, Skinner FK, Wójcik DK, Chintaluri C, Cserpán D, Somogyvári Z, Kim JK, Kilpatrick ZP, Bennett MR, Josić K, Elices I, Arroyo D, ... ... Doya K, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6 |
0.715 |
|
| 2016 |
Caligiore D, Pezzulo G, Baldassarre G, Bostan AC, Strick PL, Doya K, Helmich RC, Dirkx M, Houk J, Jörntell H, Lago-Rodriguez A, Galea JM, Miall RC, Popa T, Kishore A, et al. Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex. Cerebellum (London, England). PMID 26873754 DOI: 10.1007/S12311-016-0763-3 |
0.331 |
|
| 2016 |
Wang J, Uchibe E, Doya K. EM-based policy hyper parameter exploration: application to standing and balancing of a two-wheeled smartphone robot Artificial Life and Robotics. 1-7. DOI: 10.1007/s10015-015-0260-7 |
0.342 |
|
| 2015 |
Ito M, Doya K. Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum. Plos Computational Biology. 11: e1004540. PMID 26529522 DOI: 10.1371/journal.pcbi.1004540 |
0.372 |
|
| 2015 |
Shimizu Y, Yoshimoto J, Toki S, Takamura M, Yoshimura S, Okamoto Y, Yamawaki S, Doya K. Toward Probabilistic Diagnosis and Understanding of Depression Based on Functional MRI Data Analysis with Logistic Group LASSO. Plos One. 10: e0123524. PMID 25932629 DOI: 10.1371/journal.pone.0123524 |
0.319 |
|
| 2015 |
Funamizu A, Ito M, Doya K, Kanzaki R, Takahashi H. Condition interference in rats performing a choice task with switched variable- and fixed-reward conditions. Frontiers in Neuroscience. 9: 27. PMID 25741231 DOI: 10.3389/fnins.2015.00027 |
0.338 |
|
| 2015 |
Nakano T, Otsuka M, Yoshimoto J, Doya K. A spiking neural network model of model-free reinforcement learning with high-dimensional sensory input and perceptual ambiguity. Plos One. 10: e0115620. PMID 25734662 DOI: 10.1371/Journal.Pone.0115620 |
0.542 |
|
| 2015 |
Ito M, Doya K. Distinct neural representation in the dorsolateral, dorsomedial, and ventral parts of the striatum during fixed- and free-choice tasks. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 35: 3499-514. PMID 25716849 DOI: 10.1523/JNEUROSCI.1962-14.2015 |
0.355 |
|
| 2015 |
Elfwing S, Uchibe E, Doya K. Expected energy-based restricted Boltzmann machine for classification. Neural Networks : the Official Journal of the International Neural Network Society. 64: 29-38. PMID 25318375 DOI: 10.1016/j.neunet.2014.09.006 |
0.363 |
|
| 2015 |
Balleine BW, Dezfouli A, Ito M, Doya K. Hierarchical control of goal-directed action in the cortical-basal ganglia network Current Opinion in Behavioral Sciences. 5: 1-7. DOI: 10.1016/J.Cobeha.2015.06.001 |
0.331 |
|
| 2014 |
Okada G, Okamoto Y, Shishida K, Ueda K, Onoda K, Kunisato Y, Tanaka SC, Doya K, Yamawaki S. [Brain mechanisms of depression--preliminary evidence from fMRI studies]. Seishin Shinkeigaku Zasshi = Psychiatria Et Neurologia Japonica. 116: 825-31. PMID 25672209 |
0.428 |
|
| 2014 |
Miyazaki KW, Miyazaki K, Tanaka KF, Yamanaka A, Takahashi A, Tabuchi S, Doya K. Optogenetic activation of dorsal raphe serotonin neurons enhances patience for future rewards. Current Biology : Cb. 24: 2033-40. PMID 25155504 DOI: 10.1016/J.Cub.2014.07.041 |
0.329 |
|
| 2014 |
Miyapuram KP, Pamnani U, Doya K, Bapi RS. Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence learning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8834: 35-41. |
0.742 |
|
| 2013 |
Nakano T, Yoshimoto J, Doya K. A model-based prediction of the calcium responses in the striatal synaptic spines depending on the timing of cortical and dopaminergic inputs and post-synaptic spikes. Frontiers in Computational Neuroscience. 7: 119. PMID 24062681 DOI: 10.3389/Fncom.2013.00119 |
0.452 |
|
| 2013 |
Kinjo K, Uchibe E, Doya K. Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task. Frontiers in Neurorobotics. 7: 7. PMID 23576983 DOI: 10.3389/fnbot.2013.00007 |
0.361 |
|
| 2013 |
Elfwing S, Uchibe E, Doya K. Scaled free-energy based reinforcement learning for robust and efficient learning in high-dimensional state spaces. Frontiers in Neurorobotics. 7: 3. PMID 23450126 DOI: 10.3389/fnbot.2013.00003 |
0.406 |
|
| 2012 |
Miyazaki KW, Miyazaki K, Doya K. Activation of dorsal raphe serotonin neurons is necessary for waiting for delayed rewards. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 32: 10451-7. PMID 22855794 DOI: 10.1523/JNEUROSCI.0915-12.2012 |
0.334 |
|
| 2012 |
Okamoto Y, Okada G, Shishida K, Fukumoto T, Machino A, Yamashita H, Tanaka SC, Doya K, Yamawaki S. [Effects of serotonin on delay discounting for rewards--an application for understanding of pathophysiology in psychiatric disorders]. Seishin Shinkeigaku Zasshi = Psychiatria Et Neurologia Japonica. 114: 108-14. PMID 22568113 |
0.401 |
|
| 2012 |
Funamizu A, Ito M, Doya K, Kanzaki R, Takahashi H. Uncertainty in action-value estimation affects both action choice and learning rate of the choice behaviors of rats. The European Journal of Neuroscience. 35: 1180-9. PMID 22487046 DOI: 10.1111/j.1460-9568.2012.08025.x |
0.404 |
|
| 2012 |
Miyazaki K, Miyazaki KW, Doya K. The role of serotonin in the regulation of patience and impulsivity. Molecular Neurobiology. 45: 213-24. PMID 22262065 DOI: 10.1007/s12035-012-8232-6 |
0.319 |
|
| 2012 |
Demoto Y, Okada G, Okamoto Y, Kunisato Y, Aoyama S, Onoda K, Munakata A, Nomura M, Tanaka SC, Schweighofer N, Doya K, Yamawaki S. Neural and personality correlates of individual differences related to the effects of acute tryptophan depletion on future reward evaluation. Neuropsychobiology. 65: 55-64. PMID 22222380 DOI: 10.1159/000328990 |
0.501 |
|
| 2012 |
Sugimoto N, Haruno M, Doya K, Kawato M. MOSAIC for multiple-reward environments. Neural Computation. 24: 577-606. PMID 22168558 DOI: 10.1162/NECO_a_00246 |
0.636 |
|
| 2012 |
Pammi VS, Miyapuram KP, Ahmed, Samejima K, Bapi RS, Doya K. Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network. Neuroimage. 59: 1180-9. PMID 21867758 DOI: 10.1016/J.Neuroimage.2011.08.006 |
0.772 |
|
| 2011 |
Onoda K, Okamoto Y, Kunisato Y, Aoyama S, Shishida K, Okada G, Tanaka SC, Schweighofer N, Yamaguchi S, Doya K, Yamawaki S. Inter-individual discount factor differences in reward prediction are topographically associated with caudate activation. Experimental Brain Research. 212: 593-601. PMID 21695536 DOI: 10.1007/s00221-011-2771-3 |
0.515 |
|
| 2011 |
Ito M, Doya K. Multiple representations and algorithms for reinforcement learning in the cortico-basal ganglia circuit. Current Opinion in Neurobiology. 21: 368-73. PMID 21531544 DOI: 10.1016/j.conb.2011.04.001 |
0.43 |
|
| 2011 |
Miyazaki K, Miyazaki KW, Doya K. Activation of dorsal raphe serotonin neurons underlies waiting for delayed rewards. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 31: 469-79. PMID 21228157 DOI: 10.1523/JNEUROSCI.3714-10.2011 |
0.322 |
|
| 2011 |
Miyazaki KW, Miyazaki K, Doya K. Activation of the central serotonergic system in response to delayed but not omitted rewards. The European Journal of Neuroscience. 33: 153-60. PMID 21070390 DOI: 10.1111/j.1460-9568.2010.07480.x |
0.32 |
|
| 2011 |
Yoshimoto J, Doya K. 1SK-05 A statistical learning method for identifying synaptic connections from spike train data(1SK High Performance Computational Approaches to Biological Functions,The 49th Annual Meeting of the Biophysical Society of Japan) Seibutsu Butsuri. 51. DOI: 10.2142/Biophys.51.S9_4 |
0.342 |
|
| 2011 |
Elfwing S, Uchibe E, Doya K, Christensen HI. Darwinian embodied evolution of the learning ability for survival Adaptive Behavior. 19: 101-120. DOI: 10.1177/1059712310397633 |
0.388 |
|
| 2011 |
Doya K, Ito M, Samejima K. Model-based analysis of decision variables Decision Making, Affect, and Learning: Attention and Performance Xxiii. DOI: 10.1093/acprof:oso/9780199600434.003.0009 |
0.447 |
|
| 2011 |
Uchibe E, Doya K. Evolution of rewards and learning mechanisms in Cyber Rodents Neuromorphic and Brain-Based Robots. 109-128. DOI: 10.1017/CBO9780511994838.007 |
0.316 |
|
| 2011 |
Cutsuridis V, Heida T, Duch W, Doya K. Neurocomputational models of brain disorders Neural Networks. 24: 513-514. DOI: 10.1016/j.neunet.2011.03.016 |
0.316 |
|
| 2011 |
Miyapuram KP, Doya K, Bapi RS. Chunking During Learning of Visuomotor Sequences with Spatial and Arbitrary Rules: Preliminary Findings Psychological Studies. 57: 22-28. DOI: 10.1007/S12646-011-0118-6 |
0.758 |
|
| 2010 |
Fermin A, Yoshida T, Ito M, Yoshimoto J, Doya K. Evidence for model-based action planning in a sequential finger movement task. Journal of Motor Behavior. 42: 371-9. PMID 21184355 DOI: 10.1080/00222895.2010.526467 |
0.439 |
|
| 2010 |
Nakano T, Doi T, Yoshimoto J, Doya K. A kinetic model of dopamine- and calcium-dependent striatal synaptic plasticity. Plos Computational Biology. 6: e1000670. PMID 20169176 DOI: 10.1371/Journal.Pcbi.1000670 |
0.422 |
|
| 2010 |
Klein M, Kamp H, Palm G, Doya K. A computational neural model of goal-directed utterance selection. Neural Networks : the Official Journal of the International Neural Network Society. 23: 592-606. PMID 20116973 DOI: 10.1016/j.neunet.2010.01.003 |
0.384 |
|
| 2010 |
Morimura T, Uchibe E, Yoshimoto J, Peters J, Doya K. Derivatives of logarithmic stationary distributions for policy gradient reinforcement learning. Neural Computation. 22: 342-76. PMID 19842990 DOI: 10.1162/Neco.2009.12-08-922 |
0.355 |
|
| 2010 |
Nakashi T, Yoshimoto J, Wickens J, Doya K. Electrophysiological and molecular mechanisms of synaptic plasticity in the striatum Neuroscience Research. 68. DOI: 10.1016/J.Neures.2010.07.1534 |
0.547 |
|
| 2010 |
Nonomura S, Samejima K, Doya K, Tanji J. Neural activity in the dorsal striatum during cognitive decision making Neuroscience Research. 68: e299. DOI: 10.1016/J.Neures.2010.07.1328 |
0.631 |
|
| 2010 |
Fermin A, Yoshida T, Ito M, Yoshimoto J, Doya K. Neural mechanisms for model-free and model-based reinforcement strategies in humans performing a multi-step navigation task Neuroscience Research. 68. DOI: 10.1016/J.Neures.2010.07.1269 |
0.315 |
|
| 2009 |
Tanaka SC, Shishida K, Schweighofer N, Okamoto Y, Yamawaki S, Doya K. Serotonin affects association of aversive outcomes to past actions. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 29: 15669-74. PMID 20016081 DOI: 10.1523/JNEUROSCI.2799-09.2009 |
0.533 |
|
| 2009 |
Ito M, Doya K. Validation of decision-making models and analysis of decision variables in the rat basal ganglia. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 29: 9861-74. PMID 19657038 DOI: 10.1523/JNEUROSCI.6157-08.2009 |
0.441 |
|
| 2009 |
Fujiwara Y, Yamashita O, Kawawaki D, Doya K, Kawato M, Toyama K, Sato MA. A hierarchical Bayesian method to resolve an inverse problem of MEG contaminated with eye movement artifacts. Neuroimage. 45: 393-409. PMID 19150653 DOI: 10.1016/j.neuroimage.2008.12.012 |
0.546 |
|
| 2009 |
Ito M, Doya K. Different representation of action and reward in the dorsal and the ventral striatum Neuroscience Research. 65. DOI: 10.1016/J.Neures.2009.09.505 |
0.316 |
|
| 2009 |
Yoshida T, Ito M, Morimura T, Samejima K, Okuda J, Yoshimoto J, Doya K. Brain mechanisms for evaluating probabilistic and delayed rewards Neuroscience Research. 65: S239. DOI: 10.1016/J.Neures.2009.09.1350 |
0.536 |
|
| 2009 |
Fermin A, Takehiko Y, Tanaka S, Ito M, Yoshimoto J, Doya K. Reinforcement learning strategies for sequential action learning Neuroscience Research. 65. DOI: 10.1016/J.Neures.2009.09.1332 |
0.556 |
|
| 2009 |
Nakano T, Yoshimoto J, Wickens J, Doya K. Calcium responses model in striatum dependent on timed input sources Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5768: 249-258. DOI: 10.1007/978-3-642-04274-4_26 |
0.582 |
|
| 2008 |
Uchibe E, Doya K. Finding intrinsic rewards by embodied evolution and constrained reinforcement learning. Neural Networks : the Official Journal of the International Neural Network Society. 21: 1447-55. PMID 19013054 DOI: 10.1016/j.neunet.2008.09.013 |
0.385 |
|
| 2008 |
Ito M, Doya K. [Mathematical models of decision making and learning]. Brain and Nerve = Shinkei Kenkyå« No Shinpo. 60: 791-8. PMID 18646619 |
0.346 |
|
| 2008 |
Schweighofer N, Bertin M, Shishida K, Okamoto Y, Tanaka SC, Yamawaki S, Doya K. Low-serotonin levels increase delayed reward discounting in humans. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 28: 4528-32. PMID 18434531 DOI: 10.1523/JNEUROSCI.4982-07.2008 |
0.54 |
|
| 2008 |
Bissmarck F, Nakahara H, Doya K, Hikosaka O. Combining modalities with different latencies for optimal motor control. Journal of Cognitive Neuroscience. 20: 1966-79. PMID 18416676 DOI: 10.1162/jocn.2008.20133 |
0.412 |
|
| 2008 |
Doya K. Modulators of decision making. Nature Neuroscience. 11: 410-6. PMID 18368048 DOI: 10.1038/nn2077 |
0.341 |
|
| 2008 |
Elfwing S, Uchibe E, Doya K, Christensen HI. Co-evolution of shaping rewards and meta-parameters in reinforcement learning Adaptive Behavior. 16: 400-412. DOI: 10.1177/1059712308092835 |
0.442 |
|
| 2008 |
Sato T, Uchibe E, Doya K. Learning how, what, and whether to communicate: Emergence of protocommunication in reinforcement learning agents Artificial Life and Robotics. 12: 70-74. DOI: 10.1007/s10015-007-0444-x |
0.388 |
|
| 2008 |
Uchibe E, Doya K. Finding exploratory rewards by embodied evolution and constrained reinforcement learning in the cyber rodents Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4985: 167-176. DOI: 10.1007/978-3-540-69162-4_18 |
0.325 |
|
| 2008 |
Samejima K, Doya K. Estimating internal variables of a decision maker's brain: A model-based approach for neuroscience Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4984: 596-603. DOI: 10.1007/978-3-540-69158-7_62 |
0.462 |
|
| 2008 |
Schweighofer N, Bertin M, Shishida K, Okamoto Y, Tanaka SC, Yamawaki S, Doya K. Low-serotonin levels increase delayed reward discounting in humans (Journal of Neuroscience (2008) (4528-4532)) Journal of Neuroscience. 28: 5619. |
0.385 |
|
| 2007 |
Doya K. Reinforcement learning: Computational theory and biological mechanisms. Hfsp Journal. 1: 30-40. PMID 19404458 DOI: 10.2976/1.2732246/10.2976/1 |
0.423 |
|
| 2007 |
Tanaka SC, Schweighofer N, Asahi S, Shishida K, Okamoto Y, Yamawaki S, Doya K. Serotonin differentially regulates short- and long-term prediction of rewards in the ventral and dorsal striatum. Plos One. 2: e1333. PMID 18091999 DOI: 10.1371/journal.pone.0001333 |
0.486 |
|
| 2007 |
Corrado G, Doya K. Understanding neural coding through the model-based analysis of decision making. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 27: 8178-80. PMID 17670963 DOI: 10.1523/JNEUROSCI.1590-07.2007 |
0.318 |
|
| 2007 |
Bertin M, Schweighofer N, Doya K. Multiple model-based reinforcement learning explains dopamine neuronal activity. Neural Networks : the Official Journal of the International Neural Network Society. 20: 668-75. PMID 17611074 DOI: 10.1016/j.neunet.2007.04.028 |
0.4 |
|
| 2007 |
Samejima K, Doya K. Multiple representations of belief states and action values in corticobasal ganglia loops. Annals of the New York Academy of Sciences. 1104: 213-28. PMID 17435124 DOI: 10.1196/Annals.1390.024 |
0.569 |
|
| 2007 |
Schweighofer N, Tanaka SC, Doya K. Serotonin and the evaluation of future rewards: theory, experiments, and possible neural mechanisms. Annals of the New York Academy of Sciences. 1104: 289-300. PMID 17360806 DOI: 10.1196/annals.1390.011 |
0.507 |
|
| 2007 |
Morimoto J, Doya K. Reinforcement learning state estimator. Neural Computation. 19: 730-56. PMID 17298231 DOI: 10.1162/neco.2007.19.3.730 |
0.345 |
|
| 2007 |
Ogasawara H, Doi T, Doya K, Kawato M. Nitric oxide regulates input specificity of long-term depression and context dependence of cerebellar learning. Plos Computational Biology. 3: e179. PMID 17222054 DOI: 10.1371/journal.pcbi.0020179 |
0.638 |
|
| 2007 |
Elfwing S, Uchibe E, Doya K, Christensen HI. Evolutionary development of hierarchical learning structures Ieee Transactions On Evolutionary Computation. 11: 249-264. DOI: 10.1109/TEVC.2006.890270 |
0.381 |
|
| 2007 |
Uchibe E, Doya K. Constrained reinforcement learning from intrinsic and extrinsic rewards 2007 Ieee 6th International Conference On Development and Learning, Icdl. 163-168. DOI: 10.1109/DEVLRN.2007.4354030 |
0.321 |
|
| 2007 |
Miyazaki K, Miyazaki K, Doya K. Activity of serotonergic neurons in the dorsal raphe nucleus of freely moving rats during reward and non-reward delay period Neuroscience Research. 58. DOI: 10.1016/J.Neures.2007.06.715 |
0.301 |
|
| 2007 |
Samejima K, Ueda Y, Doya K, Kimura M. Action value in the striatum and reinforcement-learning model of cortico-basal ganglia network Neuroscience Research. 58: S22. DOI: 10.1016/J.Neures.2007.06.127 |
0.609 |
|
| 2007 |
Ueda Y, Samejima K, Doya K, Kimura M. Selective impairment of reward-based adaptive choice of actions by intra-striatal injection of dopamine D1 receptor antagonist Neuroscience Research. 58: S114. DOI: 10.1016/J.Neures.2007.06.1237 |
0.513 |
|
| 2007 |
Doya K. In pursuit of the brain mechanism of reinforcement learning Neuroscience Research. 58. DOI: 10.1016/J.Neures.2007.06.007 |
0.397 |
|
| 2007 |
Tanaka SC, Samejima K, Okada G, Ueda K, Okamoto Y, Yamawaki S, Doya K. Erratum to “Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics” [Neural Netw. 19 (8) (2006) 1233–1241] Neural Networks. 20: 285-286. DOI: 10.1016/J.Neunet.2006.12.001 |
0.588 |
|
| 2007 |
Matsubara T, Morimoto J, Nakanishi J, Sato MA, Doya K. Learning a dynamic policy by using policy gradient: Application to biped walking Systems and Computers in Japan. 38: 25-38. DOI: 10.1002/scj.20441 |
0.352 |
|
| 2006 |
Schweighofer N, Shishida K, Han CE, Okamoto Y, Tanaka SC, Yamawaki S, Doya K. Humans can adopt optimal discounting strategy under real-time constraints. Plos Computational Biology. 2: e152. PMID 17096592 DOI: 10.1371/Journal.Pcbi.0020152 |
0.502 |
|
| 2006 |
Tanaka SC, Samejima K, Okada G, Ueda K, Okamoto Y, Yamawaki S, Doya K. Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics. Neural Networks : the Official Journal of the International Neural Network Society. 19: 1233-41. PMID 16979871 DOI: 10.1016/J.Neunet.2006.05.039 |
0.675 |
|
| 2006 |
Bapi RS, Miyapuram KP, Graydon FX, Doya K. fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32: 714-27. PMID 16798015 DOI: 10.1016/j.neuroimage.2006.04.205 |
0.76 |
|
| 2006 |
Daw ND, Doya K. The computational neurobiology of learning and reward. Current Opinion in Neurobiology. 16: 199-204. PMID 16563737 DOI: 10.1016/j.conb.2006.03.006 |
0.442 |
|
| 2006 |
Kawawaki D, Shibata T, Goda N, Doya K, Kawato M. Anterior and superior lateral occipito-temporal cortex responsible for target motion prediction during overt and covert visual pursuit. Neuroscience Research. 54: 112-23. PMID 16337706 DOI: 10.1016/j.neures.2005.10.015 |
0.569 |
|
| 2006 |
Capi G, Doya K. Application of evolutionary computation for efficient reinforcement learning Applied Artificial Intelligence. 20: 35-55. DOI: 10.1080/08839510500191299 |
0.427 |
|
| 2006 |
Matsubara T, Morimoto J, Nakanishi J, Sato Ma, Doya K. Learning CPG-based biped locomotion with a policy gradient method Robotics and Autonomous Systems. 54: 911-920. DOI: 10.1016/j.robot.2006.05.012 |
0.343 |
|
| 2006 |
Samejima K, Katagiri K, Doya K, Kawato M. Symbolization and imitation learning of motion sequence using competitive modules Electronics and Communications in Japan, Part Iii: Fundamental Electronic Science (English Translation of Denshi Tsushin Gakkai Ronbunshi). 89: 42-53. DOI: 10.1002/Ecjc.20267 |
0.702 |
|
| 2006 |
Samejima K, Katagiri K, Doya K, Kawato M. Multiple model-based reinforcement learning for nonlinear control Electronics and Communications in Japan, Part Iii: Fundamental Electronic Science (English Translation of Denshi Tsushin Gakkai Ronbunshi). 89: 54-69. DOI: 10.1002/Ecjc.20266 |
0.727 |
|
| 2006 |
Miyapuram KP, Bapi RS, Pammi CVS, Ahmed, Doya K. Hierarchical chunking during learning of visuomotor sequences Ieee International Conference On Neural Networks - Conference Proceedings. 249-253. |
0.744 |
|
| 2005 |
Samejima K, Ueda Y, Doya K, Kimura M. Representation of action-specific reward values in the striatum. Science (New York, N.Y.). 310: 1337-40. PMID 16311337 DOI: 10.1126/Science.1115270 |
0.548 |
|
| 2005 |
Morimoto J, Doya K. Robust reinforcement learning. Neural Computation. 17: 335-59. PMID 15720771 DOI: 10.1162/0899766053011528 |
0.312 |
|
| 2005 |
Ogasawara H, Doi T, Doya K, Kawato M. NO Regulates Input-Specificity of LTD and Context Dependence of Cerebellar Learning Plos Computational Biology. DOI: 10.1371/Journal.Pcbi.0020179.Eor |
0.637 |
|
| 2005 |
Doya K, Uchibe E. The cyber rodent project: Exploration of adaptive mechanisms for self-preservation and self-reproduction Adaptive Behavior. 13: 149-160. DOI: 10.1177/105971230501300206 |
0.356 |
|
| 2005 |
Capi G, Doya K. Evolution of neural architecture fitting environmental dynamics Adaptive Behavior. 13: 53-66. DOI: 10.1177/105971230501300103 |
0.332 |
|
| 2004 |
Sato MA, Yoshioka T, Kajihara S, Toyama K, Goda N, Doya K, Kawato M. Hierarchical Bayesian estimation for MEG inverse problem. Neuroimage. 23: 806-26. PMID 15528082 DOI: 10.1016/j.neuroimage.2004.06.037 |
0.557 |
|
| 2004 |
Tanaka SC, Doya K, Okada G, Ueda K, Okamoto Y, Yamawaki S. Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops. Nature Neuroscience. 7: 887-93. PMID 15235607 DOI: 10.1038/nn1279 |
0.552 |
|
| 2004 |
Schweighofer N, Doya K, Fukai H, Chiron JV, Furukawa T, Kawato M. Chaos may enhance information transmission in the inferior olive. Proceedings of the National Academy of Sciences of the United States of America. 101: 4655-60. PMID 15070773 DOI: 10.1073/pnas.0305966101 |
0.576 |
|
| 2004 |
Miyamoto H, Morimoto J, Doya K, Kawato M. Reinforcement learning with via-point representation. Neural Networks : the Official Journal of the International Neural Network Society. 17: 299-305. PMID 15037348 DOI: 10.1016/j.neunet.2003.11.004 |
0.648 |
|
| 2004 |
Schweighofer N, Doya K, Kuroda S. Cerebellar aminergic neuromodulation: towards a functional understanding. Brain Research. Brain Research Reviews. 44: 103-16. PMID 15003388 DOI: 10.1016/j.brainresrev.2003.10.004 |
0.409 |
|
| 2004 |
Haruno M, Kuroda T, Doya K, Toyama K, Kimura M, Samejima K, Imamizu H, Kawato M. A neural correlate of reward-based behavioral learning in caudate nucleus: a functional magnetic resonance imaging study of a stochastic decision task. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 24: 1660-5. PMID 14973239 DOI: 10.1523/Jneurosci.3417-03.2004 |
0.731 |
|
| 2004 |
Uchibe E, Doya K. Hierarchical Reinforcement Learning for Multiple Reward Functions Journal of the Robotics Society of Japan. 22: 120-129. DOI: 10.7210/Jrsj.22.120 |
0.433 |
|
| 2004 |
Chandrasekhar Pammi VS, Miyapuram KP, Bapi RS, Doya K. Chunking phenomenon in complex sequential skill learning in humans Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3316: 294-299. |
0.734 |
|
| 2004 |
Elfwing S, Uchibe E, Doya K, Christensen HI. Multi-agent reinforcement learning: Using macro actions to learn a mating task 2004 Ieee/Rsj International Conference On Intelligent Robots and Systems (Iros). 4: 3164-3169. |
0.303 |
|
| 2004 |
Samejima K, Doya K, Ueda Y, Kimura M. Estimating internal variables and parameters of a learning agent by a particle filter Advances in Neural Information Processing Systems. |
0.477 |
|
| 2003 |
Samejima K, Doya K, Kawato M. Inter-module credit assignment in modular reinforcement learning. Neural Networks : the Official Journal of the International Neural Network Society. 16: 985-94. PMID 14692633 DOI: 10.1016/S0893-6080(02)00235-6 |
0.716 |
|
| 2003 |
Wolpert DM, Doya K, Kawato M. A unifying computational framework for motor control and social interaction. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 358: 593-602. PMID 12689384 DOI: 10.1098/rstb.2002.1238 |
0.555 |
|
| 2003 |
Schweighofer N, Doya K. Meta-learning in reinforcement learning. Neural Networks : the Official Journal of the International Neural Network Society. 16: 5-9. PMID 12576101 DOI: 10.1016/S0893-6080(02)00228-9 |
0.417 |
|
| 2003 |
Koike Y, Doya K. Driver model based on reinforced learning with multiple-step state estimation Electronics and Communications in Japan, Part Iii: Fundamental Electronic Science (English Translation of Denshi Tsushin Gakkai Ronbunshi). 86: 85-95. DOI: 10.1002/ecjc.10123 |
0.392 |
|
| 2002 |
Doya K. Metalearning and neuromodulation. Neural Networks : the Official Journal of the International Neural Network Society. 15: 495-506. PMID 12371507 DOI: 10.1016/S0893-6080(02)00044-8 |
0.371 |
|
| 2002 |
Doya K, Samejima K, Katagiri K, Kawato M. Multiple model-based reinforcement learning. Neural Computation. 14: 1347-69. PMID 12020450 DOI: 10.1162/089976602753712972 |
0.727 |
|
| 2002 |
Doya K, Dayan P, Hasselmo ME. Introduction for 2002 Special Issue: Computational models of neuromodulation Neural Networks. 15: 475-477. DOI: 10.1016/S0893-6080(02)00042-4 |
0.439 |
|
| 2001 |
Nakahara H, Doya K, Hikosaka O. Parallel cortico-basal ganglia mechanisms for acquisition and execution of visuomotor sequences - a computational approach. Journal of Cognitive Neuroscience. 13: 626-47. PMID 11506661 DOI: 10.1162/089892901750363208 |
0.412 |
|
| 2001 |
Schweighofer N, Doya K, Lay F. Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control. Neuroscience. 103: 35-50. PMID 11311786 DOI: 10.1016/S0306-4522(00)00548-0 |
0.377 |
|
| 2001 |
Kuroda S, Yamamoto K, Miyamoto H, Doya K, Kawat M. Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning. Biological Cybernetics. 84: 183-92. PMID 11252636 DOI: 10.1007/s004220000206 |
0.401 |
|
| 2001 |
Morimoto J, Doya K. Acquisition of Stand-up Behavior by a 3-link 2-joint Robot using Hierarchical Reinforcement Learning Journal of the Robotics Society of Japan. 19: 574-579. DOI: 10.7210/Jrsj.19.574 |
0.344 |
|
| 2001 |
Samejima K, Doya K, Kawato M. Journal of the Robotics Society of Japan. 19: 551-556. DOI: 10.7210/Jrsj.19.551 |
0.657 |
|
| 2001 |
Doya K, Kimura H, Kawato M. Neural mechanisms of learning and control Ieee Control Systems Magazine. 21: 42-51. DOI: 10.1109/37.939943 |
0.667 |
|
| 2001 |
Morimoto J, Doya K. Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning Robotics and Autonomous Systems. 36: 37-51. DOI: 10.1016/S0921-8890(01)00113-0 |
0.417 |
|
| 2000 |
Doya K. Complementary roles of basal ganglia and cerebellum in learning and motor control. Current Opinion in Neurobiology. 10: 732-9. PMID 11240282 DOI: 10.1016/S0959-4388(00)00153-7 |
0.42 |
|
| 2000 |
Bapi RS, Doya K, Harner AM. Evidence for effector independent and dependent representations and their differential time course of acquisition during motor sequence learning. Experimental Brain Research. 132: 149-62. PMID 10853941 DOI: 10.1007/s002219900332 |
0.353 |
|
| 2000 |
Doya K. Reinforcement learning in continuous time and space. Neural Computation. 12: 219-45. PMID 10636940 DOI: 10.1162/089976600300015961 |
0.366 |
|
| 1999 |
Doya K. What are the computations of the cerebellum, the basal ganglia and the cerebral cortex? Neural Networks : the Official Journal of the International Neural Network Society. 12: 961-974. PMID 12662639 DOI: 10.1016/S0893-6080(99)00046-5 |
0.462 |
|
| 1999 |
Hikosaka O, Nakahara H, Rand MK, Sakai K, Lu X, Nakamura K, Miyachi S, Doya K. Parallel neural networks for learning sequential procedures. Trends in Neurosciences. 22: 464-71. PMID 10481194 DOI: 10.1016/S0166-2236(99)01439-3 |
0.441 |
|
| 1999 |
Schweighofer N, Doya K, Kawato M. Electrophysiological properties of inferior olive neurons: A compartmental model. Journal of Neurophysiology. 82: 804-17. PMID 10444678 DOI: 10.1152/Jn.1999.82.2.804 |
0.542 |
|
| 1999 |
Morimoto J, Doya K. Hierarchical reinforcement learning for motion learning: Learning `stand-up' trajectories Advanced Robotics. 13: 267-268. DOI: 10.1163/156855399X00513 |
0.4 |
|
| 1994 |
Doya K, Selverston AI. Dimension Reduction of Biological Neuron Models by Artificial Neural Networks Neural Computation. 6: 696-717. DOI: 10.1162/neco.1994.6.4.696 |
0.583 |
|
| 1991 |
Doya K, Yoshizawa S. Neural network model of temporal pattern memory Systems and Computers in Japan. 22: 61-69. DOI: 10.1002/Scj.4690220907 |
0.433 |
|
| 1989 |
Doya K, Yoshizawa S. Adaptive neural oscillator using continuous-time back-propagation learning Neural Networks. 2: 375-385. DOI: 10.1016/0893-6080(89)90022-1 |
0.385 |
|
| Show low-probability matches. |