Evidence for criterion shifts in visual perceptual learning: Data and implications

Perception and Psychophysics

Volumn 70, Issue 7, 2008, Pages 1248-1273

  Wenger, Michael J ^a   Copeland, Angelina M ^b   Bittner, Jennifer L ^a   Thomas, Robin D ^c  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF NEVADA   (United States)

^c MIAMI UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; EYE FIXATION; HUMAN; LEARNING; MOTIVATION; REACTION TIME; THEORETICAL MODEL; VISION;

FIXATION, OCULAR; HUMANS; LEARNING; MODELS, THEORETICAL; MOTIVATION; REACTION TIME; VISUAL PERCEPTION;

EID: 55449097021     PISSN: 00315117     EISSN: None     Source Type: Journal    
DOI: 10.3758/PP.70.7.1248     Document Type: Article

References (108)

1. ADINI, Y., & SAGI, D. (2001). Recurrent networks in human visual cortex: Psychophysical evidence. Journal of the Optical Society of America A, 18, 2228-2236.
2. ADINI, Y., SAGI, D., & TSODYKS, M. (2002). Context-enabled learning in the human visual system. Nature, 415, 790-793.
3. AHISSAR, M., & HOCHSTEIN, S. (1993). Attentional control of early perceptual learning. Proceedings of the National Academy of Sciences, 90, 5718-5722.
4. AHISSAR, M., & HOCHSTEIN, S. (1998). Perceptual learning. In V. Walsh & J. Kulikowski (Eds.), Perceptual constancy: Why things look as they do (pp. 455-498). Cambridge: Cambridge University Press.
5. AHISSAR, M., & HOCHSTEIN, S. (2002). The role of attention in learning simple visual tasks. In M. Fahle & T. Poggio (Eds.), Perceptual learning (pp. 253-272). Cambridge, MA: MIT Press, Bradford Books.
6. AHISSAR, M., & HOCHSTEIN, S. (2004). The reverse hierarchy theory of visual perceptual learning. Trends in Cognitive Sciences, 8, 457-464.
7. AMIT, D. J., & BRUNEL, N. (1995). Learning internal representations in an attractor neural network with analogue neurons. Network, 6, 359-388.
8. AMIT, D. J., & BRUNEL, N. (1997). Dynamics of a recurrent network of spiking neurons before and following learning. Network, 8, 373-404.
9. ASHBY, F. G. (2000). A stochastic version of general recognition theory. Journal of Mathematical Psychology, 44, 310-329.
10. ATKINSON, R. C., CARTERETTE, E. C., & KINCHLA, R. A. (1964). The effect of information feedback upon psychophysical judgments. Psychonomic Science, 1, 83-84.
11. BATCHELDER, W. H., & RIEFER, D. M. (1990). Multinomial processing models of source monitoring. Psychological Review, 97, 548-564.
12. BATCHELDER, W. H., & RIEFER, D. M. (1999). Theoretical and empirical review of multinomial process tree modeling. Psychonomic Bulletin & Review, 6, 57-86.
13. BISLEY, J. W., ZAKSAS, D., DROLL, J. A., & PASTERNAK, T. (2004). Activity of neurons in cortical area MT during a memory for motion task. Journal of Neurophysiology, 91, 286-300.
14. BROWN, M. W., & BASHIR, Z. I. (2002). Evidence concerning how neurons of the perirhinal cortex may effect familiarity discrimination. Philosophical Transactions of the Royal Society B, 357, 1083-1095.
15. CHASE, W. G., & ERICSSON, K. A. (1981). Skilled memory. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 141-190). Hillsdale, NJ: Erlbaum.
16. COPELAND, A. M. (2003). Multiple sources of evidence for the mechanisms of perceptual learning. Unpublished master's thesis, University of Notre Dame.
17. COPELAND, A. M., & WENGER, M. J. (2003). Investigating perceptual and decisional mechanisms for the dynamics of perceptual learning: Theory, models, and data [Abstract]. Journal of Vision, 3(9), 676a.
18. CRAIG, A. (1976). Signal recognition and the probability-matching decision rule. Perception & Psychophysics, 20, 157-162.
19. DEHAENE, S., & CHANGEUX, J.-P. (2005). Ongoing spontaneous activity controls access to consciousness: A neuronal model for inattentional blindness. PLoS Biology, 3, 910-927.
20. DEL GIUDICE, P., FUSI, S., & MATTIA, M. (2003). Modelling the formation of working memory with networks of integrate-and-fire neurons connected by plastic synapses. Journal of Physiology, 97, 659-681.
21. DI LOLLO, V., ENNS, J. T., & RENSINK, R. A. (2000). Competition for consciousness among visual events: The psychophysics of reentrant visual processes. Journal of Experimental Psychology: General, 129, 481-507.
22. DOSHER, B. A., LIU, S.-H., BLAIR, N., & LU, Z.-L. (2004). The spatial window of the perceptual template and endogenous attention. Vision Research, 44, 1257-1271.
23. DOSHER, B. A., & LU, Z.-L. (1999). Mechanisms of perceptual learning. Vision Research, 39, 3197-3221.
24. DOSHER, B. A., & LU, Z.-L. (2007). The functional form of performance improvements in perceptual learning: Learning rates and transfer. Psychological Science, 18, 531-539.
25. EDWARDS, W. (1965). Optimal strategies for seeking information: Models for statistics, choice reaction times, and human information processing. Journal of Mathematical Psychology, 2, 312-329.
26. ERICSSON, K. A., & LEHMANN, A. C. (1996). Expert and exceptional performance: Evidence of maximal adaptation to task constraints. Annual Review of Psychology, 47, 273-305.
27. FAHLE, M. (2002). Learning to perceive features below the foveal photoreceptor spacing. In M. Fahle & T. Poggio (Eds.), Perceptual learning (pp. 197-218). Cambridge, MA: MIT Press, Bradford Books.
28. FAHLE, M., & EDELMAN, S. (1993). Long-term learning in vernier acuity: Effects of stimulus orientation, range and of feedback. Vision Research, 33, 397-412.
29. FAHLE, M., & POGGIO, T. (EDS.) (2002). Perceptual learning. Cambridge, MA: MIT Press, Bradford Books.
30. FECHNER, G. T. (1966). Elements of psychophysics (H. E. Adler, Trans.). New York: Holt, Rinehart & Winston. (Original work published 1860)
31. GIBSON, E. J. (1953). Improvement in perceptual judgments as a function of controlled practice or training. Psychological Bulletin, 50, 401-431.
32. GIBSON, E. J. (1969). Principles of perceptual learning and development. New York: Appleton-Century-Crofts.
33. GIBSON, E. J., WALK, R. D., PICK, H. L., JR., & TIGHE, T. J. (1956). The effect of prolonged exposure to visual patterns on learning to discriminate similar and different patterns. Journal of Comparative & Physiological Psychology, 51, 584-587.
34. GOLD, J. [M.], BENNETT, P. J., & SEKULER, A. B. (1999). Signal but not noise changes with perceptual learning. Nature, 402, 176-178.
35. GOLD, J. M., SEKULER, A. B., & BENNETT, P. J. (2004). Characterizing perceptual learning with external noise. Cognitive Science, 28, 167-207.
36. GREEN, D. M., & SWETS, J. A. (1966). Signal detection theory and psychophysics. New York: Wiley.
37. GRENT-'T-JONG, T., & WOLDORFF, M. G. (2007). Timing and sequence of brain activity in top-down control of visual-spatial attention. PLoS Biology, 5, 114-127.
38. HARRIS, J. A., MINIUSSI, C., HARRIS, I. M., & DIAMOND, M. E. (2002). Transient storage of a tactile memory trace in primary somatosensory cortex. Journal of Neuroscience, 22, 8720-8725.
39. HATFIELD, J. L., & SODERQUIST, D. R. (1969). Practice effects and signal detection indices in an auditory vigilance task. Journal of the Acoustical Society of America, 46, 1458-1463.
40. HAWKEY, D. J. C., AMITAY, S., & MOORE, D. R. (2004). Early and rapid perceptual learning. Nature Neuroscience, 7, 1055-1056.
41. HEATHCOTE, A., BROWN, S., & MEWHORT, D. J. K. (2000). The power law repealed: The case for an exponential law of practice. Psychonomic Bulletin & Review, 7, 185-207.
42. HERZOG, M. H., & FAHLE, M. (1997). The role of feedback in learning a vernier discrimination task. Vision Research, 37, 2133-2141.
43. HERZOG, M. H., & FAHLE, M. (1998). Modeling perceptual learning: Difficulties and how they can be overcome. Biological Cybernetics, 78, 107-117.
44. HERZOG, M. H., & FAHLE, M. (1999). Effects of biased feedback on learning and deciding in a vernier discrimination task. Vision Research, 39, 4232-4243.
45. HOCHSTEIN, S., & AHISSAR, M. (2002). View from the top: Hierarchies and reverse hierarchies in the visual system. Neuron, 36, 791-804.
46. HU, X., & BATCHELDER, W. H. (1994). The statistical analysis of engineering processing tree models with the EM algorithm. Psychometrika, 59, 21-47.
47. JACOBS, D. M., & MICHAELS, C. F. (2006). Lateral interception: I. Operative optical variables, attunement, and calibration. Journal of Experimental Psychology: Human Perception & Performance, 32, 443-458.
48. KAERNBACH, C. (1990). A single-interval adjustment matrix (SIAM) procedure for unbiased adaptive testing. Journal of the Acoustical Society of America, 88, 2645-2655.
49. KLEIN, S. A. (2001). Measuring, estimating, and understanding the psychometric function: A commentary. Perception & Psychophysics, 63, 1421-1455.
50. KORNBLUM, S. (1969). Sequential determinants of information processing in serial and discrete choice reaction time. Psychological Review, 76, 113-131.
51. LAMME, V. A. F., & ROELFSEMA, P. R. (2000). The distinct modes of vision offered by feedforward and recurrent processing. Trends in Neurosciences, 23, 571-579.
52. LEEK, M. R. (2001). Adaptive procedures in psychophysical research. Perception & Psychophysics, 63, 1279-1292.
53. LEVITT, H. (1971). Transformed up-down methods in psychoacoustics. Journal of the Acoustical Society of America, 49, 467-477.
54. LI, W., PIËCH, V., & GILBERT, C. D. (2004). Perceptual learning and top-down influences in primary visual cortex. Nature Neuroscience, 7, 651-657.
55. LING, S., & CARRASCO, M. (2006). When sustained attention impairs perception. Nature Neuroscience, 9, 1243-1245.
56. LOGAN, G. D. (1988). Toward an instance theory of automatization. Psychological Review, 95, 492-527.
57. LOGAN, G. D. (1992). Shapes of reaction-time distributions and shapes of learning curves: A test of the instance theory of automaticity. Journal of Experimental Psychology: Learning, Memory, & Cognition, 18, 883-914.
58. LU, Z.-L., & DOSHER, B. A. (2008). Characterizing observers using external noise and observer models: Assessing internal representations with external noise. Psychological Review, 115, 44-82.
59. MACKIE, R. R., WYLIE, C. D., & SMITH, M. J. (1994). Countering loss of vigilance in sonar watchstanding using signal injection and performance feedback. Ergonomics, 37, 1157-1184.
60. MACMILLAN, N. A., & CREELMAN, C. D. (2005). Detection theory: A user's guide (2nd ed.). Mahwah, NJ: Erlbaum.
61. MADDOX, W. T., & BOHIL, C. J. (2003). A theoretical framework for understanding the effects of simultaneous base-rate and payoff manipulations on decision criterion learning in perceptual categorization. Journal of Experimental Psychology: Learning, Memory, & Cognition, 29, 307-320.
62. MAJOR, G., & TANK, D. (2004). Persistent neural activity: Prevalence and mechanisms. Current Opinion in Neurobiology, 14, 675-684.
63. MCCORMICK, D. A., SHU, Y., HASENSTAUB, A., SANCHES-VIVES, M., BADOUAL, M., & BAL, T. (2003). Persistent cortical activity: Mechanisms of generation and effects on neuronal excitability. Cerebral Cortex, 13, 1219-1231.
64. MCKEE, S. P., & WESTHEIMER, G. (1978). Improvement in vernier acuity with practice. Perception & Psychophysics, 24, 258-262.
65. MILGRAM, P. (1987). A spectacle-mounted liquid-crystal tachistoscope. Behavior Research Methods, Instruments, & Computers, 19, 449-456.
66. MOLLON, J. D., & DANILOVA, M. V. (1996). Three remarks on perceptual learning. Spatial Vision, 10, 51-58.
67. MURESAN, R. C., & SAVIN, C. (2007). Resonance or integration? Self-sustained dynamics and excitability of neuronal microcircuits. Journal of Neurophysiology, 97, 1911-1930.
68. NEWELL, A., & ROSENBLOOM, P. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 1-55). Hillsdale, NJ: Erlbaum.
69. NISBETT, R. E., & WILSON, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84, 231-259.
70. OLZAK, L. A., & THOMAS, J. P. (1981). Gratings: Why frequency discrimination is sometimes better than detection. Journal of the Optical Society of America, 71, 64-70.
71. PACHELLA, R. G. (1974). The interpretation of reaction time in information processing research. In B. H. Kantowitz (Ed.), Human information processing: Tutorials in performance and cognition (pp. 41-82). Hillsdale, NJ: Erlbaum.
72. PACHELLA, R. G., & FISHER, D. (1972). Hick's law and the speed-accuracy trade-off in absolute judgment. Journal of Experimental Psychology, 92, 378-384.
73. PACHELLA, R. G., & PEW, R. W. (1968). Speed-accuracy tradeoff in reaction time: Effect of discrete criterion times. Journal of Experimental Psychology, 76, 19-24.
74. PALMERI, T. J. (1999). Theories of automaticity and the power law of practice. Journal of Experimental Psychology: Learning, Memory, & Cognition, 25, 543-551.
75. PARDUCCI, A., & SANDUSKY, A. (1965). Distribution and sequence effects in judgment. Journal of Experimental Psychology, 69, 450-459.
76. PARKS, T. E., & KELLICUTT, M. H. (1968). The probability-matching decision rule in the visual discrimination of order. Perception & Psychophysics, 3, 356-360.
77. PETROV, A. A., DOSHER, B. A., & LU, Z.-L. (2005). The dynamics of perceptual learning: An incremental reweighting model. Psychological Review, 112, 715-743.
78. RANGANATH, C., COHEN, M. X., DAM, C., & D'ESPOSITO, M. (2004). Inferior temporal, prefrontal, and hippocampal contributions to visual working memory maintenance and associative memory retrieval. Journal of Neuroscience, 24, 3917-3925.
79. RIEFER, D. M., & BATCHELDER, W. H. (1988). Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339.
80. RIGAS, P., & CASTRO-ALAMANCOS, M. A. (2007). Thalamocortical up states: Differential effects of intrinsic and extrinsic cortical inputs on persistent activity. Journal of Neuroscience, 27, 4261-4272.
81. ROELFSEMA, P. R. (2005). Elemental operations in vision. Trends in Cognitive Sciences, 9, 226-233.
82. ROSENBAUM, D. A., CARLSON, R. A., & GILMORE, R. O. (2001). Acquisition of intellectual and perceptual-motor skills. Annual Review of Psychology, 52, 453-470.
83. SAGI, D., & TANNE, D. (1994). Perceptual learning: Learning to see. Current Opinion in Neurobiology, 4, 195-199.
84. SCHULMAN, A. I., & GREENBERG, G. Z. (1970). Operating characteristics and a priori probability of the signal. Perception & Psychophysics, 8, 317-320.
85. SEITZ, A. R., NANEZ, J. E., HOLLOWAY, S. R., KOYAMA, S., & WATANABE, T. (2005). Seeing what is not there shows the costs of perceptual learning. Proceedings of the National Academy of Sciences, 102, 9080-9085.
86. SEITZ, A. [R.], & WATANABE, T. (2005). A unified model for perceptual learning. Trends in Cognitive Sciences, 9, 329-334.
87. SIGMAN, M., & GILBERT, C. D. (2000). Learning to find a shape. Nature Neuroscience, 3, 264-269.
88. SIGMAN, M., PAN, H., YAN, Y., STERN, E., SILBERSWEIG, D., & GILBERT, C. D. (2005). Top-down reorganization of activity in the visual pathway after learning a shape identification task. Neuron, 46, 823-835.
89. SINHA, P., & POGGIO, T. (2002). High-level learning of early visual tasks. In M. Fahle & T. Poggio (Eds.), Perceptual learning (pp. 273-298). Cambridge, MA: MIT Press, Bradford Books.
90. STURM, W., SCHMENK, B., FIMM, B., SPECHT, K., WEIS, S., THRON, A., & WILLMES, K. (2006). Spatial attention: More than intrinsic alerting? Experimental Brain Research, 171, 16-25.
91. SWETS, J. A., & SEWALL, S. T. (1963). Invariance of signal detectability over stages of practice and levels of motivation. Journal of Experimental Psychology, 66, 120-126.
92. TANNER, T. A., JR., HALLER, R. W., & ATKINSON, R. C. (1967). Signal recognition as influenced by presentation schedules. Perception & Psychophysics, 2, 349-358.
93. TANNER, T. A., JR., RAUK, J. A., & ATKINSON, R. C. (1970). Signal recognition as influenced by information feedback. Journal of Mathematical Psychology, 7, 259-274.
94. THOMAS, J. P. (1985). Detection and identification: How are they related? Journal of the Optical Society of America A, 2, 1457-1467.
95. THOMAS, J. P., GILLE, J., & BARKER, R. A. (1982). Simultaneous visual detection and identification: Theory and data. Journal of the Optical Society of America, 72, 1642-1651.
96. THOMAS, R. D. (2006). Processing time predictions of current models of perception in the classic additive factors paradigm. Journal of Mathematical Psychology, 50, 441-455.
97. TOWNSEND, J. T., & WENGER, M. J. (1996). Evidence monitoring theory: A dynamic extension of general recognition theory and cognitive stochastic processing theory. Paper presented at the 29th Annual Meeting of the Society for Mathematical Psychology, Chapel Hill, NC.
98. TOWNSEND, J. T., & WENGER, M. J. (1999, November). Evidence monitoring theory: Foundation and experimental application. Paper presented at the 40th Annual Meeting of the Psychonomic Society, Los Angeles.
99. VOGELS, R., & ORBAN, G. A. (1994). Activity of inferior temporal neurons during orientation discrimination with successively presented gratings. Journal of Neurophysiology, 71, 1428-1451.
100. WEIBULL, W. (1951). A statistical distribution function of wide applicability. Journal of Applied Mechanics, 18, 293-297.
101. WENGER, M. J., & PAYNE, D. G. (1995). On the acquisition of mnemonic skill: Application of skilled memory theory. Journal of Experimental Psychology: Applied, 1, 194-215.
102. WENGER, M. J., & RASCHE, C. (2006). Perceptual learning in contrast detection: Presence and cost of shifts in response criteria. Psychonomic Bulletin & Review, 13, 656-661.
103. WILD, H. A., & BUSEY, T. A. (2004). Seeing faces in the noise: Stochastic activity in perceptual regions of the brain may influence the perception of ambiguous stimuli. Psychonomic Bulletin & Review, 11, 475-481.
104. YU, C., KLEIN, S. A., & LEVI, D. M. (2003). Cross- and iso-oriented surrounds modulate the contrast response function: The effect of surround contrast. Journal of Vision, 3, 527-540.
105. YU, C., KLEIN, S. A., & LEVI, D. M. (2004). Perceptual learning in contrast discrimination and the (minimal) role of context. Journal of Vision, 4, 169-182.
106. ZAR, J. H. (1999). Biostatistical analysis (4th ed.). Upper Saddle River, NJ: Prentice Hall.
107. ZENGER, B., & SAGI, D. (2002). Plasticity of low-level visual networks. In M. Fahle & T. Poggio (Eds.), Perceptual learning (pp. 177-196). Cambridge, MA: MIT Press, Bradford Books.
108. ZHANG, M., & ALLOWAY, K. D. (2004). Stimulus-induced intercolumnar synchronization of neuronal activity in rat barrel cortex: A laminar analysis. Journal of Neurophysiology, 92, 1464-1478.