The role of chaotic resonance in cerebellar learning

Neural Networks

Volumn 23, Issue 7, 2010, Pages 836-842

  Tokuda, Isao T ^a   Han, Cheol E ^b   Aihara, Kazuyuki ^c   Kawato, Mitsuo ^d   Schweighofer, Nicolas ^e  

^a JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

^b University of Southern California ^*  (United States)

^c INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

^d ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

^e UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Cerebellar learning; Chaotic resonance; Inferior olive; Synchronization

Indexed keywords

BRAIN; NEURONS; SYNCHRONIZATION;

CEREBELLAR CORTEX; CEREBELLAR LEARNING; CHAOTIC RESONANCE; EFFICIENT LEARNING; ELECTRICAL COUPLING; INFERIOR OLIVE; NEURAL CONTROLLER; NOISE INTENSITIES;

RESONANCE;

ALGORITHM; ARTICLE; CELL INTERACTION; GRANULE CELL; INFORMATION PROCESSING; LEARNING; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; MEMBRANE POTENTIAL; MOLECULAR DYNAMICS; NERVE CELL; PLASTICITY; PRIORITY JOURNAL; PURKINJE CELL; SIGNAL TRANSDUCTION; SIMULATION; ACTION POTENTIAL; BIOLOGICAL MODEL; CEREBELLUM; COMPUTER SIMULATION; FEEDBACK SYSTEM; OLIVARY NUCLEUS; PHYSIOLOGY;

ACTION POTENTIALS; CEREBELLUM; COMPUTER SIMULATION; FEEDBACK, PHYSIOLOGICAL; LEARNING; MODELS, NEUROLOGICAL; NEURONS; OLIVARY NUCLEUS;

EID: 77955056412     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2010.04.006     Document Type: Article

References (42)

1. Albus J.S. The theory of cerebellar function. Mathematical Biosciences 1971, 10:25-61.
2. Best A.R., Regehr W.G. Inhibitory regulation of electrically coupled neurons in the inferior olive is mediated by asynchronous release of GABA. Neuron 2009, 62(4):555-565.
3. Collins J.J., Chow C.C., Imhoff T.T. Stochastic resonance without tuning. Nature 1995, 376:236-238.
4. Flash T., Hogan N. The coordination of arm movements: an experimentally confirmed mathematical model. Journal of Neuroscience 1985, 5:1688-1703.
5. Fox R.F., Gatland I.R., Roy R., Vemuri G. Fast accurate algorithm for numerical simulation of exponentially correlated colored noise. Physical Review A 1988, 38:5938-5940.
6. Fujii H., Tsuda I. Itinerant dynamics of class I* neurons coupled by gap junctions. Lecture Notes in Computer Science 2004, 3146:140-160.
7. Gilbert P.F., Thach W.T. Purkinje cell activity during motor learning. Brain Research 1977, 128:309-328.
8. Holmström L., Koistinen P. Using additive noise in back-propagation training. IEEE Transactions on Neural Networks 1992, 3:24-38.
9. Hubbard J.I., Stenhouse D., Eccles R.M. Origin of synaptic noise. Science 1967, 157:330-331.
10. Ito M. Neurophysiological aspects of the cerebellar motor control system. International Journal of Neuroscience 1970, 7:162-176.
11. Ito M. A new physiological concept on cerebellum. Revue Neurologique (Paris) 1990, 146:564-569.
12. Ito M., Sakurai M., Tongroach P. Climbing fibre induced long term depression of both mossy fibre responsiveness and glutamate sensitivity of cerebellar Purkinje cells. The Journal of Physiology 1982, 324:113-134.
13. Kaplan J.L., Yorke J.A. Chaotic behavior of multidimensional difference equations. Lecture notes in mathematics 1970, Vol. 730:204-227. Springer-Verlag, Berlin. H.O. Walter, H. Peitgen (Eds.).
14. Katayama M., Kawato M. Virtual trajectory and stiffness ellipse during multijoint arm movement predicted by neural inverse models. Biological Cybernetics 1993, 69:353-362.
15. Kawato M., Furukawa K., Suzuki R. A hierarchical neural-network model for control and learning of voluntary movement. Biological Cybernetics 1987, 57:169-185.
16. Kawato M., Gomi H. A computational model of four regions of the cerebellum based on feedback-error learning. Biological Cybernetics 1992, 68:95-103.
17. Kitazawa S., Kimura T., Yin P.B. Cerebellar complex spikes encode both destinations and error in arm movements. Nature 1998, 392:494-497.
18. Kobayashi Y., Kawano K., Takemura A., Inoue Y., Kitama T., Gomi H., Kawato M. Temporal firing patterns of Purkinje cells in the cerebellar ventral paraflocculus during ocular following responses in monkeys II. Complex spikes. Journal of Neurophysiology 1998, 80:832-848.
19. Kuramoto Y. Chemical oscillations, waves and turbulence 1984, Springer, Berlin.
20. Lang E.J., Sugihara I., Llinas R. GABAergic modulation of complex spike activity by the cerebellar nucleoolivary pathway in rat. Journal of Neurophysiology 1996, 76:255-275.
21. Lennie P. The cost of cortical computation. Current Biology 2003, 13:493-497.
22. Makarenko V., Llinas R. Experimentally determined chaotic phase synchronization in a neuronal system. Proceedings of the National Academy of Sciences of the United States of America 1998, 95:15747-15752.
23. Manor Y., Rinzel J., Segev I., Yarom Y. Low-amplitude oscillations in the inferior olive: a model based on electrical coupling of neurons with heterogeneous channel densities. Journal of Neurophysiology 1997, 77:2736-2752.
24. Marr D. A theory of cerebellar cortex. The Journal of Physiology 1969, 202:437-470.
25. Masuda N., Aihara K. Briding rate coding and temporal spike coding by effect of noise. Physical Review Letters 2002, 88:248101.
26. Masuda N., Aihara K. Duality of rate coding and temporal coding in multilayered feedforward networks. Neural Computation 2003, 15:103-125.
27. Matsuoka K. Noise injection into inputs in back-propagation learning. IEEE Transactions on Systems, Man, and Cybernetics 1992, 22:436-440.
28. Miall R.C., Christensen L.O., Cain O., Stanley J. Disruption of state estimation in the human lateral cerebellum. PLoS Biology 2007, 5:e316.
29. Miall R.C., Weir D.J., Wolpert D.M., Stein J.F. Is the cerebellum a Smith predictor?. Journal of Motor Behavior 1993, 25:203-216.
30. Nishimura H., Katada N., Aihara K. Coherent response in a chaotic neural network. Neural Processing Letters 2000, 12:49-58.
31. Pikovsky A., Rosenblum M., Kurths J. Synchronization: a universal concept in nonlinear sciences 2001, Cambridge University Press, Cambridge.
32. Rényi A. Probability theory 1970, North-Holland, Amsterdam.
33. Rössler O.E. Continuous chaos. Annals of the New York Academy of Sciences 1979, 31:376-392.
34. Schweighofer N. A model of activity-dependent formation of cerebellar microzones. Biological Cybernetics 1998, 79:97-107.
35. Schweighofer N., Doya K., Fukai H., Chiron J.V., 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 2004, 101:4655-4660.
36. Schweighofer N., Doya K., Kawato M. Electrophysiological properties of inferior olive neurons: a compartmental model. Journal of Neurophysiology 1999, 82:804-817.
37. Schweighofer N., Doya K., Lay F. Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control. Neuroscience 2001, 103:35-50.
38. Schweighofer N., Spoelstra J., Arbib M.A., Kawato M. Role of the cerebellum in reaching movements in humans. II. A neural model of the intermediate cerebellum. European Journal of Neuroscience 1998, 10:95-105.
39. Shidara M., Kawano K., Gomi H., Kawato M. Inverse-dynamics model eye movement control by Purkinje cells in the cerebellum. Nature 1993, 365:50-52.
40. Shimada I., Nagashima T. A numerical approach to ergodic problem of dissipative dynamical systems. Progress of Theoretical Physics 1979, 61:1605-1616.
41. Tseng Y.W., Diedrichsen J., Krakauer J.W., Shadmehr R., Bastian A.J. Sensory prediction errors drive cerebellum-dependent adaptation of reaching. Journal of Neurophysiology 2007, 98:54-62.
42. Tsuda I., Fujii H., Tadokoro S., Yasuoka T., Yamaguti Y. Chaotic itinerancy as a mechanism of irregular changes between synchronization and desynchronization in a neural network. Journal of Integrative Neuroscience 2004, 3:159-182.