2007

Elfwing, S., Doya, K., Christensen, H. I. (2007). Evolutionary development of hierarchical learning structures. IEEE Transactions on Evolutionary Computations, 11(2), 249-264.[PDF]

Ogasawara, H., Doi, T., Doya, K., Kawato, M. (2007). Nitric oxide regulates input specificity of long-term depression and context dependence of cerebellar learning. PLoS Computational Biology, 3(1), e179.[PDF]

Schweighofer,N., Tanaka, S. C., Doya, K. (2007). Serotonin and the evaluation of future rewards: Theory, experiments, and possible neural mechanisms. Annals of the New York Academy of Sciences, 14, 289-300.[PDF]

2006

Bando, T., Shibata, T., Doya, K., Ishii, S. (2006). Switching particle filters for efficient visual tracking. Robotics and Autonomous Systems, 54, 873-884.[PDF]

Bapi, R. S., Miyapuram, K. P., Graydon, F. X., Doya, K. (2006). fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor�fs Choice Award, 2006)[PDF]

Daw, N. D. Doya, K. (2006). The computational neurobiology of learning and reward. Current Opinion in Neurobiology, 16, 199-204.[PDF]

Elfwing, S., Doya, K., Christensen, H. I. (in press). Evolutionary development of hierarchical learning structures. IEEE Transactions on Evolutionary Computations.

Kawawaki, D., Shibata, T., Goda, N., Doya, K., Kawato, M. (2006). Anterior and superior lateral occipito-temporal cortex responsible for target motion prediction during overt and covert visual pursuit. Neuroscience Research. 54, 112-123. [PDF]
2006 Neuroscience Research Excellent Paper Award

Matsubara, T., Morimoto, J., Nakanishi, J., Sato, M., Doya, K. (2006). Learning CPG-based biped locomotion with a policy gradient method. Robotics and Autonomous Systems, 54,911-920.

Morimoto, J., Doya, K. (in press). Reinforcement learning state estimator. Neural Computation.

Ogasawara, H., Doi, T., Doya, K., Kawato, M. (2006). Nitric oxide regulates input specificity of long-term depression and context dependence of cerebellar learning. PLoS Computational Biology, 3(1), e179. [PDF]

Schweighofer, N., Shishida, K., Cheol, H. E., Okamoto, Y., Tanaka, S., Yamawaki, S., Doya, K. (2006). Humans can adopt optimal discounting strategy under real-time constraints. PLoS Computational Biology, 2(11), e152, 1349-1356. [PDF]

Tanaka, S. C., Samejima, K., Okada, G., Ueda, K., Okamoto, Y., Yamawaki, S., Doya, K. (2006). Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics. Neural Networks. 19, 1233-1241.

2005

Bando, T., Shibata, T., Doya, K., Ishii, S. (2005). Hard / soft switching particle filters for efficient real-time visual tracking. International Symposium on Artificial Life and Robotics 2005.

Bissmarck, F., Nakahara, H., Doya, K., Hikosaka, O. (2005). Responding to modalities with different latencies. Advances in Neural Information Processing Systems, MIT Press. [pdf]

Bissmarck, F., Franklin, D., Doya, K. (2005). Selective saccades in sequential hand movements. IEICE Technical Report, 105(34), 1-5.

Capi, G., Doya, K. (2005). Evolution of neural architecture fitting environmental dynamics. Adaptive Behavior, 13, 53-66. [pdf]

Capi, G., Doya, K. (2005). Evolution of recurrent neural controllers using an extended parallel genetic algorithm. Robotics and Autonomous Systems, 52, 148-159. [PDF]

Doi, T., Kuroda, S., Michikawa, S., Doya, K., Kawato, M. (2005). Spontaneous activity of parallel fibers autoregulates the amount of AMPA receptors to elicit cerebellar LTD for supervised learning. Society for Neuroscience 35th Annual Meeting.

Doya K., Uchibe E. (2005). The Cyber Rodent project: Exploration of adaptive mechanisms for self-preservation and self-reproduction. Adaptive Behavior, 13 (2), 149-160.

Kawawaki, D., Shibata, T., Goda, N., Doya, K., Kawato, M. (in press). Anterior and superior lateral occipito-temporal cortex responsible for target motion prediction during overt and covert visual pursuit. Neuroscience Research.

Matsubara, T., Morimoto, J., Nakanishi, J., Sato, M., Doya, K. (2005). Learning sensory feedback to CPG with policy gradient for biped locomotion. IEEE International Conference on Robotics and Automation (ICRA2005).

Morimoto, J., Doya, K. (2005). Robust reinforcement learning. Neural Computation, 17, 335-359.

Samejima, K., Ueda, Y., Doya, K., Kimura, M. (2005). Representation of action-specific reward value in the striatum. Science, 310, 1337-1340.

Samejima, K., Ueda, Y., Doya, K., Kimura, M. (2005). A reinforcement learning model predicts monkey's choice and dorsal striatal activities. Society for Neuroscience 35th Annual Meeting

Schweighofer,N., Shishida, K., Okamoto, Y., Tanaka, S., Yamawaki, S., Doya, K. (2005). Reward value is exponentially discounted at short - time scales and modulated by serotonin in humans. Society for Neuroscience 35th Annual Meeting.

Suzuki, H., Schweighofer, N., Hirata, Y., Fujiwara, K., Katori, Y., Shimokawa, H., Aihara, K., Kawato, M. (2005). Can electrical coupling induce chaos in inferior olive neurons? Experimental evidence. Society for Neuroscience 35th Annual Meeting.

Tanaka, S., Shishida, K., Schweighofer, N., Okamoto, Y., Yamawaki, S., Doya, K. (2005). Serotonin affects temporal credit assignment in delayed stimulus-outcome association learning. Society for Neuroscience 35th Annual Meeting.

Ueda, Y., Samejima, K., Doya, K., Kimura, M. (2005). Distinct groups of striate neurons encode action value, action choice, and reinforcement during free - choice task. Society for Neuroscience 35th Annual Meeting.

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2004

Haruno, M., Kuroda, T., Doya, K. , Toyama, K. , Kimura, M. , Samejima, K. , Imamizu, H. , Kawato, M. (2004). A neural correlate of reward-based behavioral learning in caudate nucleus: a functional magnetic resonance imaging study of a stochastic decision task. Journal of Neuroscience, 24(7), 1660-1665.

Ito, M., Doya, K., Shirao, T., Sekino, Y. (2004). Fos imaging reveals that the supramammillary nucleus enhances hippocampal activity of rats placed in a novel open field. Society for Neuroscience 34th Annual Meeting, 96.

Kawawaki, D., Shibata, T., Goda, N., Doya, K., Kawato, M. (2004). Anterior and superior lateral occipito-temporal cortex responsible for target motion prediction during overt and covert visual pursuit. Society for Neuroscience 34th Annual Meeting, 64.

Samejima K., Doya K., Ueda K., Kimura M. (2004). Estimating internal variables and parameters of a learning agent by a particle filter. Advances in Neural Information Processing Systems16, 1335-1342, MIT Press. [pdf]

Sato, M., Yoshioka, T., Kajiwara, S., Toyama, K., Goda, N., Doya, K., Kawato, M. (2004). Hierarchical bayesian estimation for MEG inverse problem. NeuroImage, 23, 806-826.

Schweighofer, N., Doya, K., Kuroda, S. (2004). Cerebellar aminergic neuromodulation: towards a functional understanding. Brain research reviews, 44, 103-116. [pdf]

Schweighofer, N., Doya, K., Fukai, H. , Chiron, Jean V., Furukawa, T., Kawato, M. (2004). Chaos may enhance information transmission in the inferior olive. Proceedings of the National Academy of Sciences, USA, 101(13), 4655-4660. [pdf]

Schweighofer,N., Tanaka, S., Asahi, S., Okamoto, Y., Doya, K., Yamawaki, S. (2004). An fMRI study of the delay discounting of reward after tryptophan depletion and loading. 1: decision-making. Society for Neuroscience 34th Annual Meeting, 97.

Tanaka, S., Doya, K., Okada, G., Ueda, K., Okamoto, Y., Yamawaki, S. (2004). Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops. Nature Neuroscience, 7(8), 887-893. [doi:10.1038/nn1279] [pdf] [pdf-s]

Tanaka, S., Schweighofer,N., Asahi, S., Okamoto, Y., Yamawaki, S., Doya, K. (2004). An fMRI study of the delay discounting of reward after tryptophan depletion and loading. 2: reward expectation. Society for Neuroscience 34th Annual Meeting, 98.

Tanaka S., Doya K., Okada G., Ueda K., Okamoto Y., Yamawaki S. (2004). Different cortico-basal ganglia loops specialize in reward prediction on different time scales. Advances in Neural Information Processing Systems16, 701-708, MIT Press.[pdf]

Uchibe, E., Doya, K. (2004). Competitive-cooperative-concurrent reinforcement learning with importance sampling. The Eighth International Conference on the Simulation of Adaptive Behavior, 287-296.

Wolpert, M. D., Doya, K, Kawato, M. (2004). A unifying computational framework for motor control and social interaction. In Frith C, Wolpert DM (Eds.) The Neuroscience of Social Interaction. Oxford University Press, Oxford, UK, 305-322.

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2003

Bissmarck F., Nakahara H., Doya K., Hikosaka O. (2003). Parallel network mechanisms for motor sequence acquisition in real time. IEICE Technical Report, 102, 113-118.

Capi G., Doya K. (2003). Evolving Recurrent Neural Controllers for Sequential Tasks - A Parallel Implementation. Congress on Evolutionary Computation, 1, 514-519.

Capi G., Uchibe E., Doya K. (2003). Selection of neural architecture and the environment complexity. Dynamic Systems Approach for Embodiment and Sociality From Ecological Psychology to Robotics, 6, 311-317. Advanced Knowledge International.

Daniel M Wolpert, D. M., Doya, K., Kawato, M. (2003). A unifying computational framework for motor control and social interaction.. Philosophical Transactions of the Royal Society, 358, 593-602.

Doya K. (2003). Enjoy now or strive for future: Neural mechanisms of reward prediction at different time scales. Summer Program 2003 Progarm and Abstracts, 36.

Doya K. (2003). Cyber Rodents: Self-preserving, self-reproducing robotic colony. ATR Up to Date, Summer 2003, 12-13.

Doya K. (2003). A Computational Theory of Neuromodulation. International Symposium, New Horizons in Molecular Sciences and Systems: An Integrated Approach, 50.

Doya K., Sugimoto N., Wolpert D.M., Kawato M. (2003). Selecting optimal behaviors based on contexts. International Symposium on Emergent Mechanisms of Communication, Awaji, 19-23. [pdf]

Elfwing S., Uchibe E., Doya K. (2003). An evolutionary approach to automatic construction of the structure in hierarchical reinforcement learning. Genetic and Evolutionary Computation - GECCO 2003 Proceedings, Part 1, Chicago, IL, Springer, GECCO 2003, LNCS 2723, 507-509. [pdf]

Eriksson A., Capi G., Doya K. (2003). Evolution of meta-parameters in reinforcement learning algorithm. IEEE/RSJ IROS. [pdf]

Samejima K., Doya K., Kawato M. (2003). Inter-module credit assignment in modular reinforcement learning. Neural Networks, 16, 985- 994.

Samejima K., Ueda Y., Doya K., Kimura M. (2003). Activity of striate projection neurons encodes action-selective reward expectations. Society for Neuroscience 33rd Annual Meeting, 78.

Schweighofer N., Doya K. (2003). Meta-learning of reinforcement learning. Neural Networks, 16, 5-9.

Tanaka S., Doya K., Okada G., Ueda K., Okamoto Y., Yamawaki S. (2003). Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops. Society for Neuroscience 33rd Annual Meeting, 58.

Ueda Y., Samejima K., Doya K., Kimura M. (2003). Reward value dependent striate neuron activity of monkey performing trial and error behavioral decision task. Neuroscience Research, Vol. 46 Suppl. 1 S1-S220, S50.

Wolpert D.M., Doya K., Kawato M. (2003). A unifying computational framework for motor control and social interaction. Philosophical Transactions of the Royal Society, 358, 593-602. [pdf]

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2002

Asahi S., Okamoto, Y., Okada, G., Morinobu, S., Yamawaki, S., Doya K. (2002). Relationship between brain activation during GO/NOGO task and impulsiveness: A fMRI study. 32nd Annual Meeting, Society for Neuroscience, Orlando, USA.

Capi G., Uchibe E., Doya K. (2002). Selection of neural architecture and the environment complexity. The 3rd International Symposium on Human and Artificial Intelligence Systems: Dynamic Systems Approach for Embodiment and Sociality, Fukui, Japan, 231-237. [pdf]

Doya K. (2002). Metalearning and neuromodulation. Neural Networks, 15, 495-506. [pdf]

Doya K. (2002). Computational models of neuromodulation. Neural Networks 2002 Special Issue on Computational Models of Neuromodulation.

Doya K. (2002). Recurrent neural networks: Supervised Learning. Arbib M, The Handbook of Brain Theory and Neural Networks, Second Edition. [pdf]

Doya K., Samejima K., Katagiri K., Kawato M. (2002). Multiple model-based reinforcement learning. Neural Computation. [pdf]

Okada G., Okamoto, Y., Ueda, K., Morinobu, S., Yamawaki, S., Doya, K. (2002). Selection between small, immediate rewards and large, delayed rewards in prediction of future reward: A functional magnetic resonance imaging study. 8th International Conference on Functional Mapping of the Human Brain, Sendai, Miyagi.

Schweighofer N., Doya K. (2002). A biologically plausible computational model of meta-learning in reinforcement learning. 32nd Annual Meeting, Society for Neuroscience, Orlando, USA.

Ueda Y., Samejima K., Doya K., Kimura M. (2002). Reward value-dependent striate neuron activity of monkey performing trial-and-error behavioral decision task. 32nd Annual Meeting, Society for Neuroscience, Orlando, USA.

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2001

Bapi R.S., Doya K. (2001). Multiple forward model architecture for sequence processing. Sun R, Giles L, Sequence Learning: Paradigms, Algorithms, and Applications, Springer Verlag, 309-320.

Doya K. (2001). Specialization of cerebellum, basal ganglia, and cerebral cortex in supervised, reinforcement, and unsupervised learning. Stockholm Workshop on Computational Neuroscience, Stockholm, 13.

Doya K. (2001). Robotic neuroscience: A synthetic approach to the brain. Neuroscience Research, Supplement, 24, S16.

Doya K. (2001). Metalearning and neuromodulation. CREST Workshop on Metalearning and Neuromodulation, Seika, Kyoto, 6.

Doya K., Kimura H., Kawato M. (2001). Neural mechanisms of learning and control. IEEE Control Systems Magazine, 21, 42-54.

Doya K., Kimura H., Miyamura A. (2001). Motor control: Neural models and system theory. International Journal of Applied Mathematics and Computer Science, 11, 101-128. [pdf]

Doya K., Okada G., Ueda K., Okamoto Y., Yamawaki S. (2001). Prediction of short- and long-term reward: A functional MRI study with a Markov decision problem. 31st Annual Meeting, Society for Neuroscience, San Diego, USA.

Doya K., Samejima K., Katagiri K., Kawato M. (2001). Task decomposition and imitation by MOSAIC architecture. HFSP Arundel Meeting / Wolpert Group, Arundel, Canada.

Haruno M., Kuroda T., Doya K., Toyama K., Kimura M., Samejima K., Imamizu H., Kawato M. (2001). fMRI study of human brain activity during reinforcement learning. 31st Annual Meeting, Society for Neuroscience, San Diego, USA.

Kuroda S., Yamamoto K., Miyamoto H., Doya K., Kawato M. (2001). Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning. Biological Cybernetics, 84, 183-192. [pdf]

Matsumoto N., Okada M., Doya K., Sugase Y., Yamane S., Kawano K. (2001). Dynamics of the face-responsive neurons in the temporal cortex. Neuroscience Research, Supplement, 24, S73.

Miyapuram K.P., Bapi R.S., Samejima K., Doya K. (2001). fMRI investigation of the learning of visuo-motor sequences. 31st Annual Meeting, Society for Neuroscience, San Diego, USA

Morimoto J., Doya K. (2001). Robust reinforcement learning. Advances in Neural Information Processing Systems 13, MIT Press, 1061-1067. [pdf]

Morimoto J., Doya K. (2001). Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning. Robotics and Autonomous Systems, 36, 37-51.

Nakahara H., Doya K., Hikosaka O. (2001). Parallel cortico-basal ganglia mechanisms for acquisition and execution of visuo-motor sequences - A computational approach. Journal of Cognitive Neuroscience, 13, 626-647. [pdf]

Okada G., Okamoto Y., Ueda K., Yamashita H., Kagaya A., Morinobu S., Yamawaki S., Doya K. (2001). Localization of brain activity in prediction of future reward using fMRI and MEG. 31st Annual Meeting, Society for Neuroscience, San Diego, USA.

Schweighofer N., Doya K., Lay F. (2001). Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control. Neuroscience, 103, 35-50. [pdf]

Tabata H., Shibata T., Taguchi S., Doya K., Kawato M. (2001). A simulation study on smooth pursuit and ocular following responses based on an MST neural-field model. Society for Neuroscience, San Diego, USA.

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2000

Bapi R.S., Doya K., Harner A.M. (2000). Evidence for effector independent and dependent representations and their differential time course of acquisition during motor sequence learning. Experimental Brain Research, 132, 149-62.

Bapi R.S., Graydon F.X., Doya K. (2000). Time course of learning of motor sequence representation. 30th Annual Meeting, Society for Neuroscience.

Doya K. (2000). Complementary roles of basal ganglia and cerebellum in learning and motor control. Current Opinion in Neurobiology, 10, 732-739. [pdf]

Doya K. (2000). Metalearning, neuromodulation, and emotion. Hatano G, Okada N, Tanabe H, Affective Minds, Elsevier Science, 101-104. [pdf]

Doya K. (2000). A possible role of serotonin in regulating the time scale of reward prediction. Serotonin Conference.

Doya K. (2000). Possible roles of neuromodulators in the regulation of learning processes. 30th Annual Meeting, Society for Neuroscience.

Doya K. (2000). Reinforcement learning in continuous time and space. Neural Computation, 12, 219-245. [pdf]

Doya K., Katagiri K., Wolpert D.M., Kawato M. (2000). Recognition and imitation of movement paterns by a multiple predictor-controller architecture. Technical Report of IEICE, TL2000-11, 33-40.

Doya K., Samejima K., Katagiri K., Kawato M. (2000). Multiple model-based reinforcement learning. Japan Science and Technology Corporation. [pdf]

Kimura H., Doya K. (2000). Motor control: Neural models and system theory. 14th International Symposium on Mathematical Theory and Networks and Systems, 232.

Kuroda S., Yamamoto K., Miyamoto H., Doya K., Kawato M. (2000). Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning. Kawato Dynamic Brain Project.

Morimoto J., Doya K. (2000). Robust reinforcement learning. Technical Report of IEICE, NC2000-49, 59-66.

Morimoto J., Doya K. (2000). Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning. 17th International Conference on Machine Learning, 1, 623-630.

Nagayuki Y., Ishii S., Doya K. (2000). Multi-agent reinforcement learning: an approach based on the other agent's internal model. Fourth International Conference on Multi-Agent Systems, 215-221.

Nagayuki Y., Ishii S., Ito M., Shimohara K., Doya K. (2000). A multi-agent reinforcement learning method with the estimation of the other agent's actions. Fifth International Symposium on Artifical Life and Robotics, 1, 255-259. [pdf]

Samejima K., Ueda Y., Kimura M., Doya K., Schweighofer N. (2000). Information coding of the striatal neurons during seqential movement. 30th Annual Meeting, Society for Neuroscience.

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1999

Bapi R.S., Doya K. (1999). MFM: Multiple forward model architecture for sequence processing. IJCAI'99 Workshop on Sequence Learning, Stockholm, Sweden.

Bapi R.S., Doya K., Harner A.M. (1999). Visual and motor representations for sequence learning. Japan Science and Technology Corporation.

Doya K. (1999). What are the computations of the cerebellum, the basal ganglia, and the cerebral cortex. Neural Networks, 12, 961-974. [pdf]

Doya K. (1999). Multiple representation and algorithms for sequence learning. 2nd International Conference on Cognitive Science, Tokyo, 17-19. [pdf]

Doya K. (1999). Metalearning, neuromodulation and emotion. 13th Toyota Conference on Affective Minds, Mikkabi, Japan, 46-47. [pdf]

Doya K., Sejnowski T.J. (1999). A computational model of avian song learning. Gazzaniga MS, The New Cognitive Neurosciences, MIT Press, 469-482.

Hikosaka O., Nakahara H., Rand M.K., Sakai K., Lu X., Nakamura K., Miyachi S., Doya K. (1999). Parallel neural networks for learning sequential procedures. Trends in Neurosciences, 22, 464-471. [pdf]

Koike Y., Doya K. (1999). Multi state estimation reinforcement learning for driving model. IEEE International Conference on System, Man and Cybernetics, Tokyo, V, 504-509.

Morimoto J., Doya K. (1999). Hierarchical reinforcement learning for motion learning: learning "stand-up" trajectories. Advanced Robotics, 13, 267-268.

Okada M., Toya K., Kimoto T., Doya K. (1999). Retrieval dynamics of associative memory model can explain temporal dynamics of face-responsive neurons in the IT cortex. 29th Annual Meeting, Society for Neuroscience, Miami Beach, Florida, USA.

Schweighofer N., Doya K., Kawato M. (1999). Electrophysiological properties of inferior olive neurons: A compartmental model. Journal of Neurophysiology, 82, 804-817.

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1998

Bapi R.S., Doya K. (1998). A sequence learning architecture based on cortico-basal ganglionic loops and reinforcement learning. The 5th International Conference on Neural Information Processing, 1, 260-263.

Bapi R.S., Doya K. (1998). Evidence for effector independent and dependent components in motor sequence learning. 28th Annual Meeting, Society for Neuroscience, 24, 167.

Doya K. (1998). Integration of cortical, cerebellar and basal ganglionic modules specialized in unsupervised, supervised and reinforcement learning. International Basal Ganglia Society 6th Triennial Meeting, 27.

Doya K., Sejnowski T.J. (1998). A computational model of birdsong learning by auditory experience and auditory feedback. Brugge J, Poon P, Central Auditory Processing and Neural Modeling, 77-88.

Morimoto J., Doya K. (1998). Reinforcement learning of dynamic motor sequence: Learning to stand up. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 3, 1721-1726.

Morimoto J., Doya K. (1998). Hierarchical reinforcement learning of low-dimensional subgoals and high-dimensional trajectories. The 5th International Conference on Neural Information Processing, 2, 850-853.

Nakahara H., Doya K. (1998). Near saddle-node bifurcation behavior as dynamics in working memory for goal-directed behavior. Neural Computation, 10, 113-132.

Nakahara H., Doya K., Hikosaka O. (1998). Benefit of multiple representations in parallel cortico-basal ganglia mechanisms for acquisition and execution of visuo-motor sequences. International Basal Ganglia Society 6th Triennial Meeting, 29.

Nakahara H., Doya K., Hikosaka O. (1998). Benefit of multiple representaitons for motor sequence control in the basal ganglia loops. RIKEN Brain Science Institute. [pdf]

Nakahara H., Doya K., Hikosaka O., Nagano S. (1998). Reinforcement learning with multiple representations in the basal ganglia loops for sequential motor control. International Joint Conference on Neural Networks, 1553-1558.

Schweighofer N., Doya K., Kawato M. (1998). A model of the electrophysiological properties of the inferior olive neurons. 28th Annual Meeting, Society for Neuroscience, 24, 667.

Schweighofer N., Doya K., Kawato M. (1998). A model of the electrophysiological properties of the inferior olive neurons. The 5th International Conference on Neural Information Processing, 3, 1525-1528.

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1997

Doya K. (1997). How basal ganglia, cerebellum and cerebral motor areas work together in sequential control tasks. Neural Control of Movement, 7th Annual Meeting Abstracts, 28.

Doya K. (1997). Efficient nonlinear control with actor-tutor architecture. Mozer MC, Jordan MI, Petsche T, Advances in Neural Information Processing Systems 9, MIT Press, 1012-1018.

Nakahara H., Doya K., Hikosaka O., Nagano S. (1997). Multiple representations in the basal ganglia loops for acquisition and execution of sequential motor control. 27th Annual Meeting, Society for Neuroscience, 23, 778.

Nakahara H., Doya K., Hikosaka O., Nagano S. (1997). Multiple representations in the basal ganglia loops for sequential decision making. Technical Report of IEICE, NC97-24.

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1996

Doya K. (1996). An integrated model of basal ganglia and cerebellum in sequential control tasks. 26th Annual Meeting, Society for Neuroscience, 22, 2029.

Doya K. (1996). Temporal difference learning in continuous time and space. Touretzky DS, Mozer MC, Hasselmo ME, Advances in Neural Information Processing Systems 8, MIT Press, 1073-1079.

Doya K. (1996). Reinforcement learning in animals and robots. International Workshop on Brainware, 69-71.

Nakahara H., Doya K. (1996). Dynamics of attention as near saddle-node bifurcation behavior. Touretzky DS, Mozer MC, Hasselmo ME, Advances in Neural Information Processing Systems 8, MIT Press, 38-44.

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1995

Doya K. (1995). Recurrent networks: Supervised learning. Arbib M, The Handbook of Brain Theory and Neural Networks, (796-800).

Doya K., Sejnowski T.J. (1995). A novel reinforcement model of birdsong vocalization learning. Tesauro G, Touretzky DS, Leen TK, Advances in Neural Information Processing Systems 7, MIT Press, 101-108.

Doya K., Sejnowski T.J. (1995). A computational model of birdsong vocalization learning. Fourth IBRO World Congress of Neuroscience Abstracts, 502.

Doya K., Sejnowski T.J. (1995). A model of birdsong vocalization learning. Burrows M, Matheson T, Newland PL, Schuppe H, Nervous Systems and Behavior, 76.

1994

Doya K., Sejnowski T.J. (1994). A computational model of song learning in the anterior forebrain pathway of the birdsong control system. 24th Annual Meeting, Society for Neuroscience, 20, 166.

Doya K., Selverston A.I. (1994). Dimension reduction of biological neuron models by artificial neural networks. Neural Computation, 6, 696-717.

Doya K., Selverston A.I., Rowat P.F. (1994). A Hodgkin-Huxley type neuron model that learns slow non-spike oscillation. Cowan JD, Tesauro G, Alspector J, Advances in Neural Information Processing Systems 6, Morgan Kaufmann, 566-573.

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1993

Doya K., Boyle M.E.T., Beauchamp M., Selverston A.I. (1993). Computational modeling of the musculoskeletal system of the lobster gastric mill. 23rd Annual Meeting, Society for Neuroscience, 19, 1602.

Doya K., Boyle M.E.T., Selverston A.I. (1993). Mapping between neural and physical activities of the lobster gastric mill. Giles CL, Hanson SJ, Cowan JD, Advances in Neural Information Processing Systems 5, Morgan Kaufmann, 913-920.

Doya K., Selverston A.I. (1993). A learning algorithm for Hodgkin-Huxley type neuron models. Proceedings of 1993 International Joint Conference on Neural Networks, 1108-1111.

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1992

Doya K. (1992). Bifurcations in the learning of recurrent neural networks. Proceedings of 1992 IEEE International Symposium on Circuits and Systems, 2777-2780.

Doya K., Yoshizawa S. (1992). Adaptive synchronization of neural and physical oscillators. Moody JE, Hanson SJ, Lippmann RP, Advances in Neural Information Processing Systems 4, 109-116.

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1991

Doya K. (1991). A study of learning algorithms for continuous-time recurrent neural networks. Department of Mathematical Engineering and Information Physics, University of Tokyo.

Doya K., Yoshizawa S. (1991). Neural network model of temporal pattern memory. Systems and Computers in Japan, 22, 61-69.

Doya K., Yoshizawa S. (1991). Geometric analysis of the dynamics of autocorrelation associative memory. International Conference on Artificial Neural Networks, 1, 261-266.

1990

Doya K. (1990). Learning temporal patterns in recurrent neural networks. Proceedings of 1990 IEEE System, Man and Cybernetics Conference, 170-172.

Doya K., Yoshizawa S. (1990). Memorizing hierarchical temporal patterns in analog neuron networks. Proceedings of 1990 International Joint Conference on Neural Networks, San Diego, III:299-304.

1989

Doya K., Yoshizawa S. (1989). Adaptive neural oscillator using continuous-time back-propagation learning. Neural Networks, 2, 375-386.

Doya K., Yoshizawa S. (1989). Memorizing oscillatory patterns in the analog neuron network. Proceedings of 1989 International Joint Conference on Neural Networks, I:27-32.

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