Cerebellum

N. Schweighofer and M. Arbib. A model of cerebellar metaplasticity.
Learning & Memory. 4:421-428, 1998.

N. Schweighofer. A model of activity-dependent formation of cerebellar
microzones. Biol. Cybern. 79:97-107, 1998.

J. Spoelstra, M. A. Arbib, and N. Schweighofer. Cerebellar adaptive
control of a biomimetic manipulator. Neurocomputing, in press, 1999.

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

N. Schweighofer, K. Doya, and M. Kawato. A model of the
electrophysiological properties of the inferior olive neurons.
Society for Neuroscience Abstracts, volume 24, page 667, 1998.

N. Schweighofer. A model of activity-dependent formation of cerebellar
microzones. Society for Neuroscience abstract, 1997.

Sequence Representation

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

R. S. Bapi and K. Doya. Evidence for effector independent and
dependent components in motor sequence learning. Society for
Neuroscience Abstracts, volume 24, page 167, 1998.

H. Nakahara, K. Doya, and O. Hikosaka. 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, page 29, 1998.

H. Nakahara, K. Doya, O. Hikosaka, and S. Nagano. Reinforcement
learning with multiple representations in the basal ganglia loops for
sequential motor control. International Joint Conference on Neural
Networks, pages 1553-1558, 1997.

H. Nakahara, K. Doya, O. Hikosaka, and S. Nagano. Multiple representations in
the basal ganglia loops for sequential decision making. Technical Report
NC97-24, Institute of Electronics, Information and Communication Engineers,
1997.

H. Nakahara, K. Doya, O. Hikosaka, and S. Nagano. Multiple representations in
the basal ganglia loops for acquisition and execution of sequential motor
control. Society for Neuroscience Abstracts, 23:778, 1997.

Cerebellum, Basal Ganglia, and Cerebral Cortex

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

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

M. Kimura and K. Doya. Motion planning and the basal ganglia.
Kagaku, 68:970-979, 1998. (in Japanese).

K. Doya. Neural computation for motor learning: Functions of basal ganglia,
cerebellum and cerebral cortex. Mathematical Sciences special issue:
Front line of Brain Science, pages 141-152, 1997. (in Japanese).

Reinforcement Learning

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

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

K. Katagiri, K. Doya, and M. Kawato. Multiple model-based
reinforcement learning for non-linear control. Technical Report
NC98-46, Institute of Electronics, Information and Communication
Engineers, 1998. (in Japanese).

J. Morimoto and K. Doya. Learning stand-up trajectories using reinforcement
learning. Technical Report NC97-28, Institute of Electronics, Information and
Communication Engineers, 1997. (in Japanese).

Y. Koike and K. Doya. Acquisition of driving skill by reinforcement learning.
Technical Report NC96-169, Institute of Electronics, Information and
Communication Engineers, 1997. (in Japanese).

Dynamic Perception in the Visual Cortex

M. Okada, N. Matsukawa, K. Fukushima, and M. Kawato. A model of
diffusing motion information along a line: does the visual system use
a relaxation calculatio? Society for Neuroscience Abstracts, 74.4,
1997.

M. Okada, S. Nishina, and M. Kawato. Dynamic contextual modulation in
vision. Mathematical Sciences special issue: Front line of Brain
Science, pages 103-111, 1997. (in Japanese).

N. Matsukawa, M. Okada, M. Kawato, and K. Fukushima. The motion
perception of the contour: Does the visual system use the relaxation
calculation? Technical Report NC96-193, Institute of Electronics,
Information and Communication Engineers, 1997. (in Japanese).

S. Nishina, M. Okada, and M. Kawato. Filling-in Process and global
binding in computation of motion direction. Technical Report NC98-65,
Institute of Electronics, Information and Communication Engineers,
1998. (in Japanese).

Others

M. Okada, T. Fukai, and M. Shiino. Random and systematic dilutions of
synaptic connections in a neural network with a nonmonotonic response
function, Physical Review E, vol.57, pages 2095-2103, 1998.

M. Kawamura, M. Okada, and Y. Hirai. Dynamics of selective recall in
an associative memory model with one-to-many associations. IEEE
Transaction on Neural Networks, in press.

K. Doya and T. J. Sejnowski. A computational model of avian song
learning. Gazzaniga MS (Ed.) The Cognitive Neurosciences, 2nd edition.
MIT Press, Cambridge, in press (1999).

K. Doya. Robotics and the Brain Sciences. Journal of the Robotics
Society of Japan, 17:7-10, 1999. (in Japanese).

K. Mimura, M. Okada, and K. Kurata. Robustness to noise of
associative memory using nonmonotonic analogue neurons. IEICE
Transaction on Information and systems, vol. E81-D, papges 928-932,
1998.

K. Mimura, M. Okada, and K. Kurata. Associative memory model with
forgetting process using nonmonotonic neurons. IEICE Transaction on
Information and systems, vol. E81-D, papges 1298-1304, 1998.

M. Okada. Autocorrelation type associative memory model. Front line
of Brain Science, pages 48-56, 1997. (in Japanese).