On the relation between decision rules and perceptual representation in multidimensional perceptual categorization

Perception and Psychophysics

Volumn 62, Issue 5, 2000, Pages 984-997

  Maddox, W Todd ^a   Bogdanov, Sergei V ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ATTENTION; DECISION MAKING; DISCRIMINATION LEARNING; FEMALE; HUMAN; MALE; ORIENTATION; PATTERN RECOGNITION; PSYCHOPHYSICS;

ATTENTION; DECISION MAKING; DISCRIMINATION LEARNING; FEMALE; HUMANS; MALE; ORIENTATION; PATTERN RECOGNITION, VISUAL; PSYCHOPHYSICS;

EID: 0034221430     PISSN: 00315117     EISSN: None     Source Type: Journal    
DOI: 10.3758/BF03212083     Document Type: Article

References (64)

1. AKAIKE, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723.
2. ALCOCK, J. (1989). Animal behavior: An evolutionary approach (4th ed.). Sunderland, MA: Sinauer.
3. ALFONSO-REESE, L. A. (1996). Dynamics of category learning. Unpublished doctoral dissertation, University of California, Santa Barbara.
4. ALFONSO-REESE, L. A. (1997). On the dangers of ignoring noise in high-level perception experiments (Technical report). Bloomington: Indiana University.
5. ASHBY, F. G. (1988). Estimating the parameters of multidimensional signal detection theory from simultaneous ratings on separate stimulus components. Perception & Psychophysics, 44, 195-204.
6. ASHBY, F. G. (1992a). Multidimensional models of categorization. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition (pp. 449-484). Hillsdale, NJ: Erlbaum.
7. ASHBY, F. G. (1992b). Multivariate probability distributions. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition (pp. 1-34). Hillsdale, NJ: Erlbaum.
8. ASHBY, F. G., ALFONSO-REESE, L. A., TURKEN, A. U., & WALDRON, E. M. (1998). A neuropsychological theory of multiple systems in category learning. Psychological Review, 105, 442-481.
9. ASHBY, F. G., & GOTT, R. E. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory, & Cognition, 14, 33-53.
10. ASHBY, F. G., & LEE, W, W. (1991). Predicting similarity and categorization from identification. Journal of Experimental Psychology: General, 120, 150-172.
11. ASHBY, F. G., & MADDOX, W. T. (1990). Integrating information from separable psychological dimensions. Journal of Experimental Psychology: Human Perception & Performance, 16, 598-612.
12. ASHBY, F. G., & MADDOX, W. T. (1991). A response time theory of perceptual independence. In J. P. Doignon & J. C. Falmagne (Eds.), Mathematical psychology: Current developments (pp. 389-414). New York: Springer-Verlag.
13. ASHBY, F. G., & MADDOX, W. T. (1992). Complex decision rules in categorization: Contrasting novice and experienced performance. Journal of Experimental Psychology: Human Perception & Performance, 18, 50-71.
14. ASHBY, F. G., & MADDOX, W. T. (1993). Relations between prototype, exemplar, and decision bound models of categorization. Journal of Mathematical Psychology, 37, 372-400.
15. ASHBY, F. G., & MADDOX, W. T. (1994). A response time theory of perceptual separability and perceptual integrality in speeded classification. Journal of Mathematical Psychology, 33, 423-466.
16. ASHBY, F. G., & MADDOX, W. T. (1998). Stimulus categorization. In M. H. Birnbaum (Ed.), Measurement, judgment, and decision making: Handbook of perception and cognition (pp. 251-301). San Diego: Academic Press.
17. ASHBY, F. G., & PERRIN, N. A. (1988). Toward a unified theory of similarity and recognition. Psychological Review, 95, 124-150.
18. ASHBY, F. G., & TOWNSEND, J. T. (1986). Varieties of perceptual independence. Psychological Review, 93, 154-179.
19. BADDELEY, A. (1995). Working memory. In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 755-764). Cambridge, MA: MIT Press.
20. BRAINARD, D. H. (1997). Psychophysics software for use with MAT-LAB. Spatial Vision, 10, 433-436.
21. BREHMER, B. (1987). Note on subject's hypothesis in multiple-cue probability learning. Organizational Behavior & Human Decision Processes, 40, 323-329.
22. DESIMONE, R., & DUNCAN, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193-222.
23. DESIMONE, R., & UNGERLEIDER, L. G. (1989). Neural mechanisms of visual processing in monkeys. In I. Boller & J. Grafman (Eds.), Handbook of neuropsychology (Vol. 2, pp. 267-299). Amsterdam: Elsevier.
24. GARNER, W. R. (1974). The processing of information and structure. New York: Wiley.
25. GARNER, W. R., & FELFOLDY, G. L. (1970). Integrality of stimulus dimensions in various types of information processing. Cognitive Psychology, 1, 225-241.
26. GEISLER, W. S. (1989). Sequential ideal-observer analysis of visual discriminations. Psychological Review, 96, 267-341.
27. GEISLER, W. S., & ALBRECHT, D. G. (1997). Visual cortex neurons in monkeys and cats: Detection, discrimination, and identification. Visual Neuroscience, 14, 897-919.
28. GEISLER, W. S. & CHOU, K. (1996). Separation of low-level and high-level factors in complex tasks: Visual search. Psychological Review, 102, 356-378.
29. GOLDMAN-RAKIC, P. S. (1995). Toward a circuit model of working memory and the guidance of voluntary motor action. In J. C. Houk, J. L. Davis, & D. G. Beiser (Eds.), Models of information processing in the basal ganglia (pp. 131-148). Cambridge, MA: MIT Press, Bradford Books.
30. GOLDSTONE, R. (1994). Influences of categorization on perceptual discrimination. Journal of Experimental Psychology: General, 123, 178-200.
31. GREEN, D. M., & SWETS, J. A. (1967). Signal detection theory and psychophysics. New York: Wiley.
32. HAMMOND, K. R., & SUMMERS, D. A. (1972). Cognitive control. Psychological Review, 79, 58-67.
33. KADLEC, H., & HICKS, C. L. (1998). Invariance of perceptual spaces and perceptual separability of stimulus dimensions. Journal of Experimental Psychology: Human Perception & Performance, 24, 80-104.
34. 1 in vowels in isolation and before oral and nasal consonants: A detection-theoretic application of the Garner paradigm. Journal of the Acoustical Society of America, 97, 1261-1285.
35. KINGSTON, J., MACMILLAN, N. A., DICKEY, I. W., THORBURN, R., & BARTELS, C. (1997). Integrality in the perception of tongue root position and voice quality in vowels. Journal of the Acoustical Society of America, 101, 1696-1709.
36. LABERGE, D. (1995). Computational and anatomical models of selective attention in object identification. In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 649-664). Cambridge, MA: MIT Press.
37. LABERGE, D. (1997). Attention, awareness, and the triangular circuit. Consciousness & Cognition, 6, 149-181.
38. MACMILLAN, N. A., & KINGSTON, J. (1995). Integrality, correspondence, and configurality represent different degrees of perceptual interaction, not different types. In C. A. Possamai (Ed.), Fechner Day '95 (pp. 243-248). Cassis, France: International Society for Psychophysics.
39. MACMILLAN, N. A., & ORNSTEIN, A. S. (1998). The mean-integral representation of rectangles. Perception & Psychophysics, 60, 250-262.
40. MADDOX, W. T. (1992). Perceptual and decisional separability. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition (pp. 147-180). Hillsdale, NJ: Erlbaum.
41. MADDOX, W. T. (1999). On the dangers of averaging across observers when comparing decision bound and generalized context models of categorization. Perception & Psychophysics, 61, 354-374.
42. MADDOX, W. T., & ASHBY, F. G. (1993). Comparing decision bound and exemplar models of categorization. Perception & Psychophysics, 53, 49-70.
43. MADDOX, W. T., & ASHBY, F. G. (1996). Perceptual separability, decisional separability, and the identification - speeded classification relationship. Journal of Experimental Psychology: Human Perception & Performance, 22, 795-817.
44. MADDOX, W. T., & ASHBY, F. G. (1998). Selective attention and the formation of linear decision boundaries: Comment on McKinley and Nosofsky (1996). Journal of Experimental Psychology: Human Perception & Performance, 24, 301-321.
45. MADDOX, W. T., ASHBY, F. G., & GOTTLOB, L. R. (1998). Response time distributions in multidimensional perceptual categorization. Perception & Psychophysics, 60, 620-637.
46. MADDOX, W. T., ASHBY, F. G., & WALDRON, E. M. (1999). On the functional independence of perceptual and executive attention in perceptual categorization. Manuscript submitted for publication.
47. MADDOX, W. T., & BOHIL, C. J. (1998).Overestimation of base-rate differences in complex perceptual categories. Perception & Psychophysics, 60, 575-592.
48. MARDIA, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrita, 57, 519-530.
49. MARDIA, K. V. (1974). Applications of some measures of multivariate skewness and kurtosis for testing normality and robustness studies. Sankhya: Series B, 36, 115-128.
50. MEDIN, D. L., & SCHAFFER, M. M. (1978). Context theory of classification learning. Psychological Review, 85, 207-238.
51. MEDIN, D. L., & SCHWANENFLUGEL, P. J. (1981). Linear separability in classification learning. Journal of Experimental Psychology: Human Learning & Memory, 1, 335-368.
52. MELLERS, B. A. (1980). Configurality in multiple probabilistic cues. American Journal of Psychology, 93, 429-443.
53. MORAN, J., & DESIMONE, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229, 782-784.
54. NOSOFSKY, R. M. (1986). Attention, similarity, and the identification -categorization relationship. Journal of Experimental Psychology: General, 115, 39-57.
55. NOSOFSKY, R. M. (1998). Selective attention and the formation of linear decision boundaries: Reply to Maddox and Ashby (1998). Journal of Experimental Psychology: Human Perception & Performance, 24, 322-339.
56. OLSHAUSEN, B. A., ANDERSON, C. H., & VAN ESSEN, D. C. (1993). A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information. Journal of Neuroscience, 13, 4700-4719.
57. PERRIN, N. A., & ASHBY, F. G. (1991). A test of perceptual independence with dissimilarity data. Applied Psychological Measurement, 15, 79-93.
58. POSNER, M. I., & PETERSEN, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25-42.
59. SHEPARD, R. N. (1964). Attention and the metric structure of the stimulus space. Journal of Mathematical Psychology, 1, 54-87.
60. SPITZER, H., DESIMONE, R., & MORAN, J. (1988). Increased attention enhances both behavioral and neuronal performance. Science, 240, 338-340.
61. TAKANE, Y., & SHIBAYAMA, T. (1992). Structures in stimulus identification data. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition (pp. 335-362). Hillsdale, NJ: Erlbaum.
62. THOMAS, R. D. (1995). Gaussian general recognition theory and perceptual independence. Psychological Review, 102, 192-200.
63. WICKENS, T. D. (1982). Models for behavior: Stochastic processes in psychology. San Francisco: Freeman.
64. WICKENS, T. D., & OLZAK, L. A. (1992). Three views of association in concurrent detection ratings. In F. G. Ashby (Ed.), Multidimensional models of perception and cognition (pp. 229-252). Hillsdale, NJ: Erlbaum.