Learning to represent a multi-context environment: More than detecting changes

Frontiers in Psychology

Volumn 3, Issue JUL, 2012, Pages

  Qian, Ting ^a   Jaeger, T Florian ^a,b   Aslin, Richard N ^a  

^a UNIVERSITY OF ROCHESTER   (United States)

^b University of Rochester   (United States)

Author keywords

Change detection; Contextual ambiguity; Contextual cue; Multi context environment; Representation learning

Indexed keywords

EID: 84867040191     PISSN: None     EISSN: 16641078     Source Type: Journal    
DOI: 10.3389/fpsyg.2012.00228     Document Type: Article

References (73)

1. Abad, M. J. F., Ramos-Alvarez, M. M., and Rosas, J. M. (2009). Partial reinforcement and context switch effects in human predictive learning. Q. J. Exp. Psychol. 62, 174-188.
2. Anderson, J. R. (1991). The adaptive nature of human categorization. Psychol. Rev. 98, 409-429.
3. Anderson, J. R., and Schooler, L. (1991). Reflections of the environment in memory. Psychol. Sci. 2, 396-408.
4. Behrens, T. E. J., Woolrich, M. W., Walton, M. E., and Rushworth, M. F. S. (2007). Learning the value of information in an uncertain world. Nat. Neurosci. 10, 1214-1221.
5. Bouton, M. E., and King, D. A. (1983). Contextual control of the extinction of conditioned fear: tests for the associative value of the context. J. Exp. Psychol. Anim. Behav. Process. 9, 248-265.
6. Brown, S. D., and Steyvers, M. (2009). Detecting and predicting changes. Cogn. Psychol. 58, 49-67.
7. Cho, R. Y., Nystrom, L. E., Brown, E. T., Jones, A. D., Braver, T. S., Holmes, P. J., and Cohen, J. D. (2002).
8. Mechanisms underlying dependencies of performance on stimulus history in a two-alternative forcedchoice task. Cogn. Affect. Behav. Neu- rosci. 2, 283-299.
9. Clapper, J. P., and Bower, G. H. (2002). Adaptive categorization in unsupervised learning. J. Exp. Psychol. Learn. Mem. Cogn. 28, 908-923.
10. Courville, A. C., Daw, N. D., and Touretzky, D. S. (2006). Bayesian theories of conditioning in a changing world. Trends Cogn. Sci. (Regul. Ed.) 10, 294-300.
11. Dall, S., Mcnamara, J., and Cuthill, I. (1999). Interruptions to foraging and learning in a changing environment. Anim. Behav. 57, 233-241.
12. Daw, N., and Courville, A. (2008). The pigeon as particle filter. Adv. Neural Inf. Process. Syst. 20, 369-376.
13. Ernst, M. O., and Banks, M. S. (2002). Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415, 429-433.
14. Fine, A. B., Qian, T., Jaeger, T. F., and Jacobs, R. A. (2010). "Is there syntactic adaptation in language comprehension?" in Proceedings of the 2010 Workshop on Cognitive Modeling and Computational Linguistics, ed. J. T. Hale (Stroudsburg, PA:Association for Computational Linguistics), 18-26
15. Frankenhuis, W. E., and Panchanathan, K. (2011). Individual Differences in developmental plasticity may result from stochastic sampling. Perspect. Psychol. Sci. 6, 336-347.
16. Freidin, E., and Kacelnik, A. (2011). Rational choice, context dependence, and the value of information in European starlings (Stur- nus vulgaris). Science 334, 1000-1002.
17. French, R. M. (1999). Catastrophic forgetting in connectionist networks. Trends Cogn. Sci. (Regul. Ed.) 3, 128-135.
18. Gallistel, C. R., Fairhurst, S., and Balsam, P. (2004). The learning curve: implications of a quantitative analysis. Proc. Natl. Acad. Sci. U.S.A. 101, 13124-13131.
19. Gallistel, C. R., Mark, T. A., King, A. P., and Latham, P. E. (2001). The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect. J. Exp. Psychol. Anim. Behav. Process. 27, 354-372.
20. García-Gutiérrez, A., and Rosas, J. M. (2003). Context change as the mechanism of reinstatement in causal learning. J. Exp. Psychol. Anim. Behav. Process. 29, 292-310.
21. Gebhart, A. L., Aslin, R. N., and Newport, E. L. (2009). Changing structures in midstream: learning along the statistical garden path. Cogn. Sci. 33, 1087-1116.
22. Gerken, L. (2010). Infants use rational decision criteria for choosing among models of their input. Cognition 115, 362-366.
23. Gilovich, T., Vallone, R., and Tversky, A. (1985). The hot hand in basketball: on the misperception of random sequences. Cogn. Psychol. 17, 295-314.
24. Gökaydin, D., Ma-Wyatt, A., Navarro, D., and Perfors, A. (2011). "Humans use different statistics for sequence analysis depending on the task," in Proceedings of the 33rd Annual Conference of the Cognitive Sci- ence Society, eds L. Carlson, C. Hölscher, and T. Shipley (Austin, TX: Cognitive Science Society), 543-548.
25. Green, C. S., Benson, C., Kersten, D., and Schrater, P. (2010). Alterations in choice behavior by manipulations of world model. Proc. Natl. Acad. Sci. U.S.A. 107, 16401-16406
26. Griffiths, T., Kemp, C., and Tenenbaum, J. (2008). "Bayesian models of cognition," in The Cambridge Handbook of Computational Psy- chology, ed. R. Sun (New York: Cambridge University Press), 59-100.
27. Gureckis, T. M., and Love, B. C. (2009). Learning in noise: dynamic decision-making in a variable environment. J. Math. Psychol. 53, 180-193
28. Gweon, H., Tenenbaum, J. B., and Schulz, L. E. (2010). Infants consider both the sample and the sampling process in inductive generalization. Proc. Natl. Acad. Sci. U.S.A. 107, 9066-9071.
29. Hayden, B. Y., Pearson, J. M., and Platt, M. L. (2011). Neuronal basis of sequential foraging decisions in a patchy environment. Nat. Neurosci. 14, 933-939.
30. Jaeger, T. F. (2010). Redundancy and reduction: speakers manage syntactic information density. Cogn. Psy- chol. 61, 23-62.
31. Jones, M., and Love, B. C. (2011). Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition. Behav. Brain Sci. 34, 169-188.
32. Jones, M., and Sieck, W. R. (2003). Learning myopia: an adaptive recency effect in category learning. J. Exp. Psychol. Learn. Mem. Cogn. 29, 626-640.
33. Kacelnik, A., Krebs, J. R., and Ens, B. (1987). "Foraging in a changing environment: an experiment with starlings (Sturnus vulgaris)," in Quantitative Analyses of Behavior: Foraging, Vol. VI, eds M. L. Commons, A. Kacelnik, and S. J. Shettleworth (London: Psychology Press), 63-87.
34. Kemp, C., Perfors, A., and Tenenbaum, J. B. (2007). Learning overhypotheses with hierarchical Bayesian models. Dev. Sci. 10, 307-321
35. Kemp, C., and Tenenbaum, J. B. (2008). The discovery of structural form. Proc. Natl. Acad. Sci. U.S.A. 105, 10687-10692.
36. Knill, D. C. (2007). Robust cue integration: a Bayesian model and evidence from cue-conflict studies with stereoscopic and figure cues to slant. J. Vis. 7, 5.1-24.
37. Knox, W. B., Otto, A. R., Stone, P., and Love, B. C. (2011). The nature of belief-directed exploratory choice in human decisionmaking. Front. Psychol. 2:398. doi:10.3389/fpsyg.2011.00398
38. Knudsen, E. (1998). Capacity for plasticity in the adult owl auditory system expanded by juvenile experience. Science 279, 1531-1533.
39. Kording, K. P., Tenenbaum, J. B., and Shadmehr, R. (2007). The dynamics of memory as a consequence of optimal adaptation to a changing body. Nat. Neurosci. 10, 779-786.
40. Kruschke, J. K. (1992). ALCOVE: an exemplar-based connectionist model of category learning. Psychol. Rev. 99, 22-44.
41. Lee, M. D. (2011). How cognitive modeling can benefit from hierarchical Bayesian models. J. Math. Psychol. 55, 1-7.
42. Lewandowsky, S., and Kirsner, K. (2000). Knowledge partitioning: context-dependent use of expertise. Mem. Cognit. 28, 295-305.
43. Linkenhoker, B. A., von der Ohe, C. G., and Knudsen, E. I. (2005). Anatomical traces of juvenile learning in the auditory system of adult barn owls. Nat. Neurosci. 8, 93-98.
44. Love, B. C., Medin, D. L., and Gureckis, T. M. (2004). SUSTAIN: a network model of category learning. Psychol. Rev. 111, 309-332.
45. Maloney, L. T., Dal Martello, M. F., Sahm, C., and Spillmann, L. (2005). Past trials influence perception of ambiguous motion quartets through pattern completion. Proc. Natl. Acad. Sci. U.S.A. 102, 3164-3169.
46. Marr, D. (1982). Vision. San Francisco, CA: W.H. Freeman & Co Ltd.
47. Mathys, C., Daunizeau, J., Friston, K. J., and Stephan, K. E. (2011). A bayesian foundation for individual learning under uncertainty. Front. Hum. Neurosci. 5:39. doi:10.3389/fnhum.2011.00039
48. Nassar, M. R., Wilson, R. C., Heasly, B., and Gold, J. I. (2010). An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment. J. Neurosci. 30, 12366-12378.
49. Newell, K. M., Liu, Y. T., and Mayer-Kress, G. (2001). Time scales in motor learning and development. Psychol. Rev. 108, 57-82.
50. Payzan-LeNestour, E., and Bossaerts, P. (2011). Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings. PLoS Comput. Biol. 7, e1001048. doi:10.1371/journal.pcbi.1001048
51. Pearce, J. M., Redhead, E. S., and Aydin, A. (1997). Partial reinforcement in appetitive Pavlovian conditioning with rats. Q. J. Exp. Psychol. 50B, 273-294.
52. Pearson, J. M., Hayden, B. Y., Raghavachari, S., and Platt, M.L. (2009). Neurons in posterior cingulate cortex signal exploratory decisions in a dynamic multioption choice task. Curr. Biol. 19, 1532-1537.
53. Rescorla, R., and Wagner, A. (1972). "A theory of Pavlovian conditioning: the effectiveness of reinforcement and non-reinforcement," in Classical Conditioning, Vol. 2, eds A. Black and W. Prokasy (New York: Appleton-Century-Crofts), 64-69.
54. Rosas, J. M., and Callejas-Aguilera, J. E. (2006). Context switch effects on acquisition and extinction in human predictive learning. J. Exp. Psychol. Learn. Mem. Cogn. 32, 461-474
55. Rottman, B. M., and Keil, F. C. (2012). Causal structure learning over time: observations and interventions. Cogn. Psychol. 64, 93-125.
56. Rushworth, M. F. S., and Behrens, T. E. J. (2008). Choice, uncertainty and value in prefrontal and cingulate cortex. Nat. Neurosci. 11, 389-397.
57. Sakamoto, Y., Jones, M., and Love, B. C. (2008). Putting the psychology back into psychological models: mechanistic versus rational approaches. Mem. Cognit. 36, 1057-1065.
58. Sanborn, A. N., Griffiths, T. L., and Navarro, D. J. (2010). Rational approximations to rational models: alternative algorithms for category learning. Psychol. Rev. 117, 1144-1167.
59. Shiryaev, A. N. (1978). Optimal Stopping Rules. New York: Springer-Verlag.
60. Sissons, H. T., and Miller, R. R. (2009). Spontaneous recovery of excitation and inhibition. J. Exp. Psychol. Anim. Behav. Process. 35, 419-426.
61. Stankiewicz, B. J., Legge, G. E., Mansfield, J. S., and Schlicht, E. J. (2006). Lost in virtual space: studies in human and ideal spatial navigation. J. Exp. Psychol. Hum. Percept. Per- form. 32, 688-704.
62. Summerfield, C., Behrens, T. E., and Koechlin, E. (2011). Perceptual classification in a rapidly changing environment. Neuron 71, 725-736.
63. Tarpy, R. (1982). Principles of Animal Learning and Motivation. London: Scott Foresman.
64. Thanellou, A., and Green, J. T. (2011). Spontaneous recovery but not reinstatement of the extinguished conditioned eyeblink response in the rat. Behav. Neurosci. 125, 613-625.
65. Toscano, J. C., and McMurray, B. (2010). Cue integration with categories: weighting acoustic cues in
66. Weiss, D. J., Gerfen, C., and Mitchel, A. D. (2009). Speech segmentation in a simulated bilingual environment: a challenge for statistical learning? Lang. Learn. Dev. 5, 30-49.
67. Wilder, M., Jones, M., and Mozer, M. (2010). Sequential effects reflect parallel learning of multiple environmental regularities. Adv. Neural Inf. Process. Syst. 22, 2053-2061.
68. Wilson, R. C., Nassar, M. R., and Gold, J. I. (2010). Bayesian online learning of the hazard rate in changepoint problems. Neural Comput. 22, 2452-2476.
69. Wilson, R. C., and Niv, Y. (2012). Inferring relevance in a changing world. Front. Hum. Neurosci. 5:189. doi:10.3389/fnhum.2011.00189
70. Yang, L.-X., and Lewandowsky, S. (2003). Context-gated knowledge partitioning in categorization. J. Exp. Psychol. Learn. Mem. Cogn. 29, 663-679.
71. Yi, M., and Steyvers, M. (2009). Modeling human performance in restless bandits with particle filters. J. Prob. Solv. 2, 81-102.
72. Yu, A. J. (2007). Adaptive behavior: humans act as Bayesian learners. Curr. Biol. 17, R977-R980.
73. Yu, A. J., and Cohen, J. D. (2008). Sequential effects: superstition or rational behavior? Adv. Neural Inf. Process. Syst. 21, 1873-1880.