Cogprints

Investigation of sequence processing: A cognitive and computational neuroscience perspective

Bapi, Dr Raju S. and Pammi, V.S. Chandrasekhar and Miyapuram, K.P. and Ahmed, Ahmed (2005) Investigation of sequence processing: A cognitive and computational neuroscience perspective. [Journal (On-line/Unpaginated)]

Full text available as:

[img]
Preview
PDF
75Kb

Abstract

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes.

Item Type:Journal (On-line/Unpaginated)
Keywords:Cognitive science, computational modelling, reinforcement learning, serial order, sequence learning
Subjects:Neuroscience > Computational Neuroscience
JOURNALS
Psychology > Cognitive Psychology
ID Code:4640
Deposited By:Miyapuram, Mr Krishna
Deposited On:19 Dec 2005
Last Modified:11 Mar 2011 08:56

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

1. Lashley, K. S., The problem of serial order in behavior. In Cerebral Mechanisms in Behavior (ed. Jeffress, L. A.), New York: Wiley, 1951, pp. pp. 112–136.

2. Yarbus, A. L., Eye movements during perception of complex objects. In Eye Movements and Vision (ed. Riggs, L. A.), Plenum Press, New York, 1967, chapter VII, pp. 171–196.

3. Berridge, K. C. and Whishaw, I. Q., Cortex, striatum, and cerebellum: control of syntactic grooming sequences. Experimental Brain Research, 1992, 90, 275–290.

4. Diamond, A., Evidence for the importance of dopamine for prefrontal cortex functions early in life. Philosophical Transactions for the Royal Society of London, 1996, Series B, 351, 1483–1494.

5. Arbib, M. and Rizzolatti, G., Neural expectations: a possible evolutionary path from manual skills to language. Communication and Cognition, 1996, 29(2–4), 393–424.

6. Schaal, S., Is Imitation learning the route to humanoid robots?. Trends in Cognitive Sciences, 1999, 3, 233–242.

7. Georgopoulos, A. P., Lurito, J. T., Petrides, M. and Schwartz, A. B., Mental rotation of the neuronal population vector. Science, 1989, 243, 234–236.

8. Lu, X. and Ashe, J., Anticipatory activity in primary motor cortex codes memorized movement sequences. Neuron, 2005, 45, 967–973.

9. Tanji, J. and Shima, K., Role for supplementary motor area cells in planning several movements ahead. Nature, 1994, 371, 413–416.

10. Chomsky, N., Syntactic structures, The Hague: Mouton & Co., 1957.

11. Newell, A., Shaw, J. C. and Simon, H. A., Elements of a theory of human problem solving. Psychological Review, 1958, 65, 151–166.

12. Miller, G. A., Galanter, E. and Pribram, K. H., Plans and the Structure of Behaviour, New York: Holt Rinehart & Winston, 1960.

13. Newell, A. and Simon, H., Human Problem Solving, Englewood Cliffs, NJ: Prentice Hall, 1972.

14. Wickelgren, W. A., Context sensitive coding, associative memory, and serial order in (speech) behavior. Psychological Review, 1969, 76, 1–15.

15. Wickelgren, W. A., Webs, cell assemblies, and chunking in neural nets: Introduction. Canadian Journal of Experimental Psychology, 1999, 53(1), 118–131.

16. MacKay, D. G., The problem of flexibility, fluency, and speed-accuracy trade-off in skilled behavior. Psychological Review, 1982, 89, 483–506.

17. Rosenbaum, D. A., Kenny, S. B. and Derr, M. A., Hierarchical control of rapid movement sequences. Journal of Experimental Psychology: Human Perception and Performance, 1983, 9, 86–102.

18. Sakai, K., Kitaguchi, K. and Hikosaka, O., Chunking during human visuomotor sequence learning. Experimental Brain Research, 2003, 152, 229–242.

19. Pammi, V. S. C., Miyapuram, K. P., Bapi, R. S. and Doya, K., Chunking phenomenon in complex sequential skill learning in humans. In LNCS, Proceedings of International Conference on Neural Information Processing (eds. Pal, N. R., Kasabov, N., Mudi, R. K., Pal, S., Parui, S. K.), Springer–Verlag Heidelberg, 2004, 3316, pp. 294–299.

20. Miller, G. A., The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 1956, 63, 81–97.

21. Grossberg, S., Some networks that can learn, remember, and reproduce any number of complicated space time patterns I. Journal of Mathematics and Mechanics, 1969, 19, 53–91.

22. Janata, P. and Grafton, S. T., Swinging in the brain: shared neural substrates for behaviors related to sequencing and music, Nature Neuroscience, 2003, 6, 682–687.

23. Anderson, J. R., Acquisition of cognitive skill. Psychological Review, 1982, 89, 369–406.

24. Curran, T., On the Neural Mechanisms of sequence learning. PSYCHE, 1995, 2(12), 1995.

25. Fitts, P.M., Perceptual motor skill learning. In Categories of Human learning (ed. Melton, A. W.), Academic press, New York, 1964, pp. 243–285.

26. Jueptner, M., Stephan, K. M., Frith, C. D., Brooks, D. J., Frackowiak, R. S. J. and Passingham, R. E., Anatomy of motor learning I Frontal cortex and attention to action. Journal of Neurophysiology, 1997, 77, 1313–1324.

27. Jueptner, M., Frith, C. D., Brooks, D. J., Frackowiak, R.S.J. and Passingham, R. E., Anatomy of Motor Learning II Subcortical structures and learning by trial and error. Journal of Neurophysiology, 1997, 77, 1325-1337.

28. Sakai, K., Hikosaka, O., Miyauchi, S., Takino, R., Sasaki, Y. and Pütz, B., Transition of brain activation from frontal to parietal areas in visuomotor sequence learning. The Journal of Neuroscience, 1998, 18, 1827–1840.

29. Doya, K., What are the computations in the cerebellum, the basal ganglia, and the cerebral cortex. Neural Networks, 1999, 12, 961–974.

30. Sun, R., Introduction to sequence learning. In Sequence Learning: Paradigms, Applications and Algorithms (eds. Sun, R., Giles, C. L.), Springer-Verlag, LNAI, 2000, 1828, 1–10.

31. Sun, R. and Giles, L., Sequence learning: from prediction and recognition to sequential decision making. IEEE Intelligent Systems, 2001, 16(4), 67–70.

32. Squire, L. R. and Zola, S. M., Structure and function of declarative and nondeclarative memory systems. Proceedings of National Academy of Science USA, 1996, 93, 13515–13522.

33. Clegg, B. A., DiGirolamo, G. J. and Keele, S. W., Sequence learning. Trends in Cognitive Sciences, 1998, 2, 275–281.

34. Shin, J. C. and Ivry, R. B., Spatial and temporal sequence learning in patients with Parkinson's disease or cerebellar lesions. Journal of Cognitive Neuroscience, 2003, 15, 1232-1243.

35. Sakai, K., Hikosaka, O., Takino, R., Miyauchi, S., Nielsen, M. and Tamada, T., What and when: parallel and convergent processing in motor control. Journal of Neuroscience, 2000, 20, 2691–2700.

36. Kennereley, S. W., Sakai, K. and Rushworth, M. F. S., Organization of action sequences and role of the Pre-SMA. Journal of Neuroohysiology, 2004, 91, 978–993.

37. Bapi, R. S., Doya, K. and Harner, A. M., Evidence for effector independent and dependent representations and their differential time course of acquisition during motor sequence learning. Experimental Brain Research, 2000, 132, 149–162.

38. Bapi, R. S., Graydon, F. X. and Doya, K. Time course of learning of visual and motor sequence representations. Society for Neuroscience Annual meeting, USA, 2000.

39. Pammi, V. S. C., Miyapuram, K. P., Bapi, R. S., Samejima, K. and Doya, K., Acquisition of complex sequential skills: Behavioral and fMRI Investigation. Building the Brain, Manesar, India, 2003.

40. Pammi, V. S. C., Miyapuram, K. P., Bapi, R. S., Samejima, K. and Doya, K., The activation of orbitofrontal cortex reflects trial and error processes in a visuomotor sequence learning task. Networks and Behavior, Bangalore, India, 2003.

41. Grafton, S. T., Hazeltine, E. and Ivry, R. B., Abstract and effector-specific representations of motor sequences identified with PET. Journal of Neuroscience, 1998, 18, 9420–9428.

42. Doya, K., Complementary roles of basal ganglia and cerebellum in learning and motor control. Current Opinion in Neurobiology, 2000, 10, 732–739.

43. Pasupathy, A. and Miller, E. K., Different timecourses of learning-related activity in the prefrontal cortex and striatum, 2005, Nature, 433, 873–876.

44. Berns, G. and Sejnowski, T. J., A Computational model of how the basal ganglia produce sequences. Journal of Cognitive Neuroscience, 1998, 10, pp. 108–121.

45. Dominey, P. F., Arbib M. A. and Joseph, J. P., A model of cortico-strital plasticity for learning oculomotor associations and sequences. Journal of Cognitive Neuroscience, 1995, 7, 311–336.

46. Servan-Schreiber, D., Cleeremans, A. and McClelland, J. L., Graded state machines: The representation of temporal contingencies in simple recurrent networks. In Artificial Intelligence and Neural Networks: Steps toward principled integration (eds. Honavar, V., Uhr, L.), Academic Press, San Diego CA, 1994, pp. 241–268.

47. Suri, R.E. and Schultz, W., Dopamine-like reinforcement signal improves learning of sequential movements by neural network. Experimental Brain Research, 1998, 121, 350–354.

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

49. Sutton, R. S. and Barto, A. G., Reinforcement Learning: An Introduction, MIT Press, Cambridge MA, 1998.

Metadata

Repository Staff Only: item control page