The structure of integral dimensions: Contrasting topological and cartesian representations

Journal of Experimental Psychology: Human Perception and Performance

Volumn 39, Issue 1, 2013, Pages 111-132

  Jones, Matt ^a   Goldstone, Robert L ^b  

^a UNIVERSITY OF COLORADO   (United States)

^b INDIANA UNIVERSITY   (United States)

Author keywords

Cartesian representation; Integral dimensions; Perceptual representation; Topological representation; Unsupervised learning

Indexed keywords

ARTICLE; ATTENTION; COLOR VISION; DEPTH PERCEPTION; DISCRIMINATION LEARNING; HUMAN; PATTERN RECOGNITION; PERCEPTIVE DISCRIMINATION; PHOTOSTIMULATION; PSYCHOLOGICAL MODEL; TASK PERFORMANCE;

ATTENTION; COLOR PERCEPTION; DISCRIMINATION (PSYCHOLOGY); DISCRIMINATION LEARNING; HUMANS; MODELS, PSYCHOLOGICAL; PATTERN RECOGNITION, VISUAL; PHOTIC STIMULATION; SPACE PERCEPTION; TASK PERFORMANCE AND ANALYSIS;

MLCS; MLOWN;

EID: 84880450033     PISSN: 00961523     EISSN: None     Source Type: Journal    
DOI: 10.1037/a0029059     Document Type: Article

References (73)

1. Anderson, J. R. (1991). The adaptive nature of human categorization. Psychological Review, 98, 409-429. doi:10.1037/0033-295X.98.3.409
2. Ashby, F. G., & Lee, W. W. (1991). Predicting similarity and categorization from identification. Journal of Experimental Psychology: General, 120, 150-172. doi:10.1037/0096-3445.120.2.150
3. Ashby, F. G., & Maddox, W. T. (1993). Relations between prototype, exemplar, and decision bound models of categorization. Journal of Mathematical Psychology, 37, 372-400. doi:10.1006/jmps.1993.1023
4. Ashby, F. G., & Maddox, W. T. (1994). A response time theory of separability and integrality in speeded classification. Journal of Mathematical Psychology, 38, 423-466. doi:10.1006/jmps.1994.1032
5. Ashby, F. G., & Maddox, W. T. (2005). Human category learning. Annual Review of Psychology, 56, 149 -178. doi:10.1146/annurev .psych.56.091103.070217
6. Ashby, F. G., Queller, S., & Berretty, P. M. (1999). On the dominance of unidimensional rules in unsupervised categorization. Perception & Psychophysics, 61, 1178-1199. doi:10.3758/BF03207622
7. Ashby, F. G., & Townsend, J. T. (1986). Varieties of perceptual independence. Psychological Review, 93, 154 -179. doi:10.1037/0033- 295X.93.2.154
8. Attneave, F. (1950). Dimensions of similarity. American Journal of Psychology, 63, 516-556. doi:10.2307/1418869
9. Austerweil, J. L., & Griffiths, T. L. (2010). Learning hypothesis spaces and dimensions through concept learning. In Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 73-78). Hillsdale, NJ: Erlbaum.
10. Ballesteros, S. (1989). Some determinants of perceived structure: Effects of stimulus tasks. In B. E. Shepp & S. Ballesteros (Eds.), Object perception: Structure and process (pp. 235-266). Hillsdale, NJ: Erlbaum.
11. Barlow, H. B., & Foldiak, P. (1989). Adaptation and decorrelation in the cortex. In R. Durbin, C. Miall, & G. Mitchison (Eds.), The computing neuron (pp. 454-472). New York, NY: Addison Wesley.
12. Bell, A., & Sejnowski, T. (1997). The "independent components" of natural scenes are edge filters. Vision Research, 37, 3327-3338. doi: 10.1016/S0042-6989(97)00121-1
13. Brainard, D. H. (1989). Calibration of a computer controlled color monitor. Color Research and Application, 14, 23-34. doi:10.1002/col.5080140107
14. Bredon G. E. (1995). Topology and geometry. New York, NY: Springer-Verlag.
15. Bukach, C., Gauthier, I., & Tarr, M. J. (2006). Beyond faces and modularity: The power of an expertise framework. Trends in Cognitive Sciences, 10, 159-166. doi:10.1016/j.tics.2006.02.004
16. Burton, A. M., Jenkins, R., Hancock, P. J. B., & White, D. (2005). Robust representations for face recognition: The power of averages. Cognitive Psychology, 51, 256-284. doi:10.1016/j.cogpsych.2005.06.003
17. Canini, K. R., Shashkov, M. M., & Griffiths, T. L. (2010). Modeling transfer learning in human categorization with the hierarchical Dirichlet process. In J. Furnkranz & T. Joachims (Eds.), Proceedings of the 27th International Conference on Machine Learning (pp. 151-158). Madison, WI: Omnipress.
18. Carroll, J. D., & Chang, J. J. (1972, March). IDOSCAL (individual differences in orientation scaling): A generalization of iNDSCAL allowing miosyncratic reference systems as well as analytic approximation to INDSCAL. Paper presented at the meeting of the Psychometric Society, Princeton, NJ.
19. Dailey, M. N., Cottrell, G. W., Padgett, C., & Adolphs, R. (2002). EMPATH: A neural network that perceives and categorizes facial expressions. Journal of Cognitive Neuroscience, 14, 1158-1173. doi: 10.1162/089892902760807177
20. de Beeck, H. O., Wagemans, J., & Vogels, R. (2003). The effect of category learning on the representation of shape: Dimensions can be biased, but not differentiated. Journal of Experimental Psychology: General, 132, 491-511. doi:10.1037/0096-3445.132.4.491
21. Foard, C. F., & Kemler, D. G. (1984). Holistic and analytic model of processing: The multiple determinants of perceptual analysis. Journal of Experimental Psychology: General, 113, 94-111. doi:10.1037/0096- 3445.113.1.94
22. Furl, N., Phillips, P. J., & O'Toole, A. J. (2002). Face recognition algorithms and the other-race effect: Computational mechanisms for a developmental contact hypothesis. Cognitive Science, 26, 797-815. doi: 10.1207/s15516709cog2606_4
23. Garner, W. R. (1974). The processing of information and structure. New York, NY: Wiley.
24. Garner W. R., & Felfoldy, G. L. (1970). Integrality of stimulus dimensions in various types of information processing. Cognitive Psychology, 1, 225-241. doi:10.1016/0010-0285(70)90016-2
25. Goldstone, R. L. (1994a). An efficient method for obtaining similarity data. Behavior Research Methods, Instruments, & Computers, 26, 381-386. doi:10.3758/BF03204653
26. Goldstone, R. L. (1994b). Influences of categorization on perceptual discrimination. Journal of Experimental Psychology: General, 123, 178- 200. doi:10.1037/0096-3445.123.2.178
27. Goldstone, R. L. (1998). Perceptual learning. Annual Review of Psychology, 49, 585-612. doi:10.1146/annurev.psych.49.1.585
28. Goldstone, R. L. (2003). Learning to perceive while perceiving to learn. In R. Kimchi, M. Behrmann, & C. Olson (Eds.), Perceptual organization in vision: Behavioral and neural perspectives (pp. 233-280). Mahwah, NJ: Erlbaum.
29. Goldstone, R. L., & Steyvers, M. (2001). The sensitization and differentiation of dimensions during category learning. Journal of Experimental Psychology: General, 130, 116-139. doi:10.1037/0096-3445.130.1.116
30. Grau, J. W., & Kemler Nelson, D. G. (1988). The distinction between integral and separable dimensions: Evidence for the integrality of pitch and loudness. Journal of Experimental Psychology: General, 117, 347- 370. doi:10.1037/0096-3445.117.4.347
31. Griffiths, T. L., Canini, K. R., Sanborn, A. N., & Navarro, D. J. (2007). Unifying rational models of categorization via the hierarchical Dirichlet process. In Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society (pp. 323-328). Hillsdale, NJ: Erlbaum.
32. Grill-Spector, K., Knouf, N., & Kanwisher, N. (2004). The fusiform face area subserves face perception, not generic within-category identification. Nature Neuroscience, 7, 555-562. doi:10.1038/nn1224
33. Gureckis, T. M., & Goldstone, R. L. (2008). The effect of the internal structure of categories on perception. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 843-848). Austin, TX: Cognitive Science Society.
34. Handel, S., & Imai, S. (1972). The free classification of analyzable and unanalyzable stimuli. Perception & Psychophysics, 12, 108-116.
35. Hinson, J. M., Cannon, C. B., & Tennison, L. R. (1998). Range effects and dimensional organization in visual discrimination. Behavioural Processes, 43, 275-287. doi:10.1016/S0376-6357(98)00021-7
36. Hyman, R., & Well, A. (1967). Judgments of similarity and spatial models. Perception & Psychophysics, 2, 233-248.
37. Hyman, R., & Well, A. (1968). Perceptual separability and spatial models. Perception & Psychophysics, 3, 161-165.
38. Intrator, N., & Gold, J. I. (1993). Three-dimensional object recognition using an unsupervised BCM network. Neural Computation, 5, 61-74. doi:10.1162/neco.1993.5.1.61
39. Ishihara, S. (1967). Tests of colour-blindness (38 plate collection). Tokyo, Japan: Shuppan.
40. Jolliffe, I. T. (2002). Principal components analysis. New York, NY: Springer.
41. Jones, M., Maddox, W. T., & Love, B. C. (2005). Stimulus generalization in category learning. Proceedings of the 27th Annual Meeting of the Cognitive Science Society, 1066-1071.
42. Kalish, C. W., Rogers, T. T., Lang, L., & Zhu, X. (2011). Can semisupervised learning explain incorrect beliefs about categories? Cognition, 120, 106-118.
43. Kemler Nelson D. G. (1993). Processing integral dimensions: The whole view. Journal of Experimental Psychology: Human Perception and Performance, 19, 1105-1113. doi:10.1037/0096-1523.19.5.1105
44. Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29, 1-27. doi:10.1007/BF02289565
45. Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211-240. doi: 10.1037/0033-295X.104.2.211
46. Lockhead, G. R. (1972). Processing dimensional stimuli: A note. Psychological Review, 79, 410-419. doi:10.1037/h0033129
47. Love, B. C., Medin, D. L., & Gureckis, T. M. (2004). SUSTAIN: A network model of category learning. Psychological Review, 111, 309- 332. doi:10.1037/0033-295X.111.2.309
48. Melara, R. D., & Marks, L. E. (1990). Perceptual primacy of dimensions: Support for a model of dimensional interaction. Journal of Experimental Psychology: Human Perception and Performance, 16, 398-414. doi: 10.1037/0096-1523.16.2.398
49. Melara, R. D., Marks, L. E., & Lesko, K. E. (1992). Optional processes in similarity judgments. Perception & Psychophysics, 51, 123-133. doi: 10.3758/BF03212237
50. Melara, R. D., Marks, L. E., & Potts, B. C. (1993a). Early-holistic processing or dimensional similarity? Journal of Experimental Psychology: Human Perception and Performance, 19, 1114-1120. doi:10.1037/0096-1523.19.5.1114
51. Melara, R. D., Marks, L. E., & Potts, B. C. (1993b). Primacy of dimensions in color perception. Journal of Experimental Psychology: Human Perception and Performance, 19, 1082-1104. doi:10.1037/0096- 1523.19.5.1082
52. Newhall, S. M., Nickerson, D., & Judd, D. B. (1943). Final report of the O.S.A. subcommittee on spacing of the Munsell colors. Journal of the Optical Society of America, 33, 385-418. doi:10.1364/JOSA.33.000385
53. Nickerson, D. (1936). The specification of color tolerances. Textile Research Journal, 6, 505-514. doi:10.1177/004051753600601202
54. Nosofsky, R. M. (1986). Attention, similarity, and the identification- categorization relationship. Journal of Experimental Psychology: General, 115, 39-61. doi:10.1037/0096-3445.115.1.39
55. Nosofsky, R. M. (1992). Similarity scaling and cognitive process models. Annual Review of Psychology, 43, 25-53. doi:10.1146/annurev .ps.43.020192.000325
56. Pevtzow, R., & Goldstone, R. L. (1994). Categorization and the parsing of objects. In Proceedings of the 16th Annual Conference of the Cognitive Science Society (pp. 717-722). Hillsdale, NJ: Erlbaum.
57. Pothos, E. M., & Close, J. (2008). One or two dimensions in spontaneous classification: A simplicity approach. Cognition, 107, 581-602. doi: 10.1016/j.cognition.2007.11.007
58. Schyns, P. G., Goldstone, R. L., & Thibaut, J. (1998). Development of features in object concepts. Behavioral and Brain Sciences, 21, 1-17. doi:10.1017/S0140525X98000107
59. Shepard, R. N. (1962). The analysis of proximities: Multidimensional scaling with an unknown distance function. Part I. Psychometrika, 27, 125-140. doi:10.1007/BF02289630
60. Shepard, R. N. (1964). Attention and the metric structure of the stimulus space. Journal of Mathematical Psychology, 1, 54-87. doi:10.1016/ 0022-2496(64)90017-3
61. Simoncelli, E. P., & Olshausen, B. A. (2001). Natural image statistics and neural representation. Annual Review of Neuroscience, 24, 1193-1216. doi:10.1146/annurev.neuro.24.1.1193
62. Smith, J. D., & Minda, J. P. (1998). Prototypes in the mist: The early epochs of category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 1411-1436. doi:10.1037/0278-7393.24.6.1411
63. Smith, L. B., & Kemler, D. G. (1978). Levels of experienced dimensionality in children and adults. Cognitive Psychology, 10, 502-532. doi: 10.1016/0010-0285(78)90009-9
64. Steyvers, M. (1999). Morphing techniques for generating and manipulating face images. Behavior Research Methods, Instruments, & Computers, 31, 359-369. doi:10.3758/BF03207733
65. Sutherland, N., & Mackintosh, N. (1971). Mechanisms of animal discrimination learning. New York, NY: Academic Press.
66. Torgerson, W. S. (1951). A theoretical and empirical investigation of multidimensional scaling (Unpublished doctoral dissertation). Princeton University, Princeton, NJ.
67. Torgerson, W. S. (1958). Theory and methods of scaling. New York, NY: Wiley.
68. Toscano, J. C., & McMurray, B. (2010). Cue integration with categories: Weighting acoustic cues in speech using unsupervised learning and distributional statistics. Cognitive Science, 34, 434-464. doi:10.1111/ j.1551-6709.2009.01077.x
69. Travis, D. (1991). Effective color displays: Theory and practice. London, England: Academic Press.
70. Tucker, L. R. (1972). Relations between multidimensional scaling and three-mode factor analysis. Psychometrika, 37, 3-27. doi:10.1007/BF02291410
71. Turk, M., & Pentland, A. (1991). Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3, 71-86. doi:10.1162/jocn.1991.3.1.71
72. Valentin, D., Abdi, H., & Edelman, B. (1997). What represents a face: A computational approach for the integration of physiological and psychological data. Perception, 26, 1271-1288. doi:10.1068/p261271
73. Zhu, X., Rogers, T. T., Qian, R., & Kalish, C. (2007). Humans perform semi-supervised classification too. In R. C. Holte & A. Howe (Eds.), Proceedings of AAAI 2007 (pp. 864-869). Menlo Park: AAAI Press.