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Annual Review of Vision Science

Volume 2, 2016

Perceptual Learning: Use-Dependent Cortical Plasticity

Abstract

Our perceptual abilities significantly improve with practice. This phenomenon, known as perceptual learning, offers an ideal window for understanding use-dependent changes in the adult brain. Different experimental approaches have revealed a diversity of behavioral and cortical changes associated with perceptual learning, and different interpretations have been given with respect to the cortical loci and neural processes responsible for the learning. Accumulated evidence has begun to put together a coherent picture of the neural substrates underlying perceptual learning. The emerging view is that perceptual learning results from a complex interplay between bottom-up and top-down processes, causing a global reorganization across cortical areas specialized for sensory processing, engaged in top-down attentional control, and involved in perceptual decision making. Future studies should focus on the interactions among cortical areas for a better understanding of the general rules and mechanisms underlying various forms of skill learning.

Keyword(s): cortical plasticity, learning specificity, learning transfer, perceptual learning, top-down influence, visual cortex
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2016-10-14
2024-05-07
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Literature Cited

  1. Abe H, McManus JNJ, Ramalingam N, Li W, Marik SA. et al. 2015. Adult cortical plasticity studied with chronically implanted electrode arrays. J. Neurosci. 35:2778–90 [Google Scholar]
  2. Adab HZ, Popivanov ID, Vanduffel W, Vogels R. 2014. Perceptual learning of simple stimuli modifies stimulus representations in posterior inferior temporal cortex. J. Cogn. Neurosci. 26:2187–200 [Google Scholar]
  3. Adab HZ, Vogels R. 2011. Practicing coarse orientation discrimination improves orientation signals in macaque cortical area V4. Curr. Biol. 21:1661–66 [Google Scholar]
  4. Ahissar M, Hochstein S. 1993. Attentional control of early perceptual learning. PNAS 90:5718–22 [Google Scholar]
  5. Ahissar M, Hochstein S. 1996. Learning pop-out detection: specificities to stimulus characteristics. Vis. Res. 36:3487–500 [Google Scholar]
  6. Ahissar M, Hochstein S. 1997. Task difficulty and the specificity of perceptual learning. Nature 387:401–6 [Google Scholar]
  7. Amitay S, Irwin A, Moore DR. 2006. Discrimination learning induced by training with identical stimuli. Nat. Neurosci. 9:1446–48 [Google Scholar]
  8. Averbeck BB, Latham PE, Pouget A. 2006. Neural correlations, population coding and computation. Nat. Rev. Neurosci. 7:358–66 [Google Scholar]
  9. Baker CI, Peli E, Knouf N, Kanwisher NG. 2005. Reorganization of visual processing in macular degeneration. J. Neurosci. 25:614–18 [Google Scholar]
  10. Ball K, Sekuler R. 1982. A specific and enduring improvement in visual motion discrimination. Science 218:697–98 [Google Scholar]
  11. Ball K, Sekuler R. 1987. Direction-specific improvement in motion discrimination. Vis. Res. 27:953–65 [Google Scholar]
  12. Baruni JK, Lau B, Salzman CD. 2015. Reward expectation differentially modulates attentional behavior and activity in visual area V4. Nat. Neurosci. 18:1656–63 [Google Scholar]
  13. Bejjanki VR, Beck JM, Lu Z-L, Pouget A. 2011. Perceptual learning as improved probabilistic inference in early sensory areas. Nat. Neurosci. 14:642–48 [Google Scholar]
  14. Bejjanki VR, Zhang R, Li R, Pouget A, Green CS. et al. 2014. Action video game play facilitates the development of better perceptual templates. PNAS 111:16961–66 [Google Scholar]
  15. Berardi N, Fiorentini A. 1987. Interhemispheric transfer of visual information in humans: spatial characteristics. J. Physiol. 384:633–47 [Google Scholar]
  16. Beste C, Dinse HR. 2013. Learning without training. Curr. Biol. 23:R489–99 [Google Scholar]
  17. Bi T, Chen J, Zhou T, He Y, Fang F. 2014. Function and structure of human left fusiform cortex are closely associated with perceptual learning of faces. Curr. Biol. 24:222–27 [Google Scholar]
  18. Blakemore C, Cooper GF. 1970. Development of the brain depends on the visual environment. Nature 228:477–78 [Google Scholar]
  19. Brown M, Irvine DRF, Park VN. 2004. Perceptual learning on an auditory frequency discrimination task by cats: association with changes in primary auditory cortex. Cereb. Cortex 14:952–65 [Google Scholar]
  20. Chang DHF, Mevorach C, Kourtzi Z, Welchman AE. 2014. Training transfers the limits on perception from parietal to ventral cortex. Curr. Biol. 24:2445–50 [Google Scholar]
  21. Chen M, Yan Y, Gong X, Gilbert CD, Liang H, Li W. 2014. Incremental integration of global contours through interplay between visual cortical areas. Neuron 82:682–94 [Google Scholar]
  22. Chen N, Bi T, Zhou T, Li S, Liu Z, Fang F. 2015. Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning. NeuroImage 115:17–29 [Google Scholar]
  23. Chen N, Cai P, Zhou T, Thompson B, Fang F. 2016. Perceptual learning modifies the functional specializations of visual cortical areas. PNAS 113:5724–29 [Google Scholar]
  24. Choi H, Watanabe T. 2012. Perceptual learning solely induced by feedback. Vis. Res. 61:77–82 [Google Scholar]
  25. Chowdhury SA, DeAngelis GC. 2008. Fine discrimination training alters the causal contribution of macaque area MT to depth perception. Neuron 60:367–77 [Google Scholar]
  26. Crist RE, Kapadia MK, Westheimer G, Gilbert CD. 1997. Perceptual learning of spatial localization: specificity for orientation, position, and context. J. Neurophysiol. 78:2889–94 [Google Scholar]
  27. Crist RE, Li W, Gilbert CD. 2001. Learning to see: experience and attention in primary visual cortex. Nat. Neurosci. 4:519–25 [Google Scholar]
  28. De Weerd P, Reithler J, van de Ven V, Been M, Jacobs C, Sack AT. 2012. Posttraining transcranial magnetic stimulation of striate cortex disrupts consolidation early in visual skill learning. J. Neurosci. 32:1981–88 [Google Scholar]
  29. Dilks DD, Serences JT, Rosenau BJ, Yantis S, McCloskey M. 2007. Human adult cortical reorganization and consequent visual distortion. J. Neurosci. 27:9585–94 [Google Scholar]
  30. Dosher BA, Lu Z-L. 1998. Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting. PNAS 95:13988–93 [Google Scholar]
  31. Fahle M, Daum I. 2002. Perceptual learning in amnesia. Neuropsychologia 40:1167–72 [Google Scholar]
  32. Fahle M, Edelman S, Poggio T. 1995. Fast perceptual learning in hyperacuity. Vis. Res. 35:3003–13 [Google Scholar]
  33. Fiorentini A, Berardi N. 1980. Perceptual learning specific for orientation and spatial frequency. Nature 287:43–44 [Google Scholar]
  34. Fiorentini A, Berardi N. 1981. Learning in grating waveform discrimination: specificity for orientation and spatial frequency. Vis. Res. 21:1149–58 [Google Scholar]
  35. Fritz J, Elhilali M, Shamma S. 2005. Active listening: task-dependent plasticity of spectrotemporal receptive fields in primary auditory cortex. Hear. Res. 206:159–76 [Google Scholar]
  36. Furmanski CS, Schluppeck D, Engel SA. 2004. Learning strengthens the response of primary visual cortex to simple patterns. Curr. Biol. 14:573–78 [Google Scholar]
  37. Ghose GM, Yang T, Maunsell JHR. 2002. Physiological correlates of perceptual learning in monkey V1 and V2. J. Neurophysiol. 87:1867–88 [Google Scholar]
  38. Gilbert CD, Wiesel TN. 1992. Receptive field dynamics in adult primary visual cortex. Nature 356:150–52 [Google Scholar]
  39. Goujon A, Didierjean A, Thorpe S. 2015. Investigating implicit statistical learning mechanisms through contextual cueing. Trends Cogn. Sci. 19:524–33 [Google Scholar]
  40. Green CS, Bavelier D. 2015. Action video game training for cognitive enhancement. Curr. Opin. Behav. Sci. 4:103–8 [Google Scholar]
  41. Grzeczkowski L, Tartaglia EM, Mast FW, Herzog MH. 2015. Linking perceptual learning with identical stimuli to imagery perceptual learning. J. Vis. 15:1013 [Google Scholar]
  42. Gu Y, Liu S, Fetsch CR, Yang Y, Fok S. et al. 2011. Perceptual learning reduces interneuronal correlations in macaque visual cortex. Neuron 71:750–61 [Google Scholar]
  43. Han YK, Köver H, Insanally MN, Semerdjian JH, Bao S. 2007. Early experience impairs perceptual discrimination. Nat. Neurosci. 10:1191–97 [Google Scholar]
  44. Herzog MH, Fahle M. 1997. The role of feedback in learning a vernier discrimination task. Vis. Res. 37:2133–41 [Google Scholar]
  45. Hua T, Bao P, Huang C-B, Wang Z, Xu J. et al. 2010. Perceptual learning improves contrast sensitivity of V1 neurons in cats. Curr. Biol. 20:887–94 [Google Scholar]
  46. Hubel DH, Wiesel TN. 1959. Receptive fields of single neurones in the cat's striate cortex. J. Physiol. 148:574–91 [Google Scholar]
  47. Hubel DH, Wiesel TN. 1970. Period of susceptibility to physiological effects of unilateral eye closure in kittens. J. Physiol. 206:419–36 [Google Scholar]
  48. Hung S-C, Seitz AR. 2014. Prolonged training at threshold promotes robust retinotopic specificity in perceptual learning. J. Neurosci. 34:8423–31 [Google Scholar]
  49. Jehee JFM, Ling S, Swisher JD, van Bergen RS, Tong F. 2012. Perceptual learning selectively refines orientation representations in early visual cortex. J. Neurosci. 32:16747–53 [Google Scholar]
  50. Jeter PE, Dosher BA, Liu S-H, Lu Z-L. 2010. Specificity of perceptual learning increases with increased training. Vis. Res. 50:1928–40 [Google Scholar]
  51. Jeter PE, Dosher BA, Petrov A, Lu Z-L. 2009. Task precision at transfer determines specificity of perceptual learning. J. Vis. 9:31 [Google Scholar]
  52. Kaas JH, Krubitzer LA, Chino YM, Langston AL, Polley EH, Blair N. 1990. Reorganization of retinotopic cortical maps in adult mammals after lesions of the retina. Science 248:229–31 [Google Scholar]
  53. Kahnt T, Grueschow M, Speck O, Haynes J-D. 2011. Perceptual learning and decision-making in human medial frontal cortex. Neuron 70:549–59 [Google Scholar]
  54. Karni A, Sagi D. 1991. Where practice makes perfect in texture discrimination: evidence for primary visual cortex plasticity. PNAS 88:4966–70 [Google Scholar]
  55. Kim Y-H, Kang D-W, Kim D, Kim H-J, Sasaki Y, Watanabe T. 2015. Real-time strategy video game experience and visual perceptual learning. J. Neurosci. 35:10485–92 [Google Scholar]
  56. Kobatake E, Wang G, Tanaka K. 1998. Effects of shape-discrimination training on the selectivity of inferotemporal cells in adult monkeys. J. Neurophysiol. 80:324–30 [Google Scholar]
  57. Kourtzi Z, Betts LR, Sarkheil P, Welchman AE. 2005. Distributed neural plasticity for shape learning in the human visual cortex. PLOS Biol. 3:1317–27 [Google Scholar]
  58. Kuai S-G, Levi D, Kourtzi Z. 2013. Learning optimizes decision templates in the human visual cortex. Curr. Biol. 23:1799–804 [Google Scholar]
  59. Law C-T, Gold JI. 2008. Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area. Nat. Neurosci. 11:505–13 [Google Scholar]
  60. Law C-T, Gold JI. 2009. Reinforcement learning can account for associative and perceptual learning on a visual-decision task. Nat. Neurosci. 12:655–63 [Google Scholar]
  61. Lewis CM, Baldassarre A, Committeri G, Romani GL, Corbetta M. 2009. Learning sculpts the spontaneous activity of the resting human brain. PNAS 106:17558–63 [Google Scholar]
  62. Li W, Piëch V, Gilbert CD. 2004. Perceptual learning and top-down influences in primary visual cortex. Nat. Neurosci. 7:651–57 [Google Scholar]
  63. Li W, Piëch V, Gilbert CD. 2006. Contour saliency in primary visual cortex. Neuron 50:951–62 [Google Scholar]
  64. Li W, Piëch V, Gilbert CD. 2008. Learning to link visual contours. Neuron 57:442–51 [Google Scholar]
  65. Liu Z, Weinshall D. 2000. Mechanisms of generalization in perceptual learning. Vis. Res. 40:97–109 [Google Scholar]
  66. Logothetis NK, Pauls J, Poggio T. 1995. Shape representation in the inferior temporal cortex of monkeys. Curr. Biol. 5:552–63 [Google Scholar]
  67. Makino H, Komiyama T. 2015. Learning enhances the relative impact of top-down processing in the visual cortex. Nat. Neurosci. 18:1116–22 [Google Scholar]
  68. McManus JNJ, Li W, Gilbert CD. 2011. Adaptive shape processing in primary visual cortex. PNAS 108:9739–46 [Google Scholar]
  69. Messinger A, Squire LR, Zola SM, Albright TD. 2005. Neural correlates of knowledge: stable representation of stimulus associations across variations in behavioral performance. Neuron 48:359–71 [Google Scholar]
  70. Miyashita Y. 1993. Inferior temporal cortex: where visual perception meets memory. Annu. Rev. Neurosci. 16:245–63 [Google Scholar]
  71. Miyashita Y. 2004. Cognitive memory: cellular and network machineries and their top-down control. Science 306:435–40 [Google Scholar]
  72. Moldakarimov S, Bazhenov M, Sejnowski TJ. 2014. Top-down inputs enhance orientation selectivity in neurons of the primary visual cortex during perceptual learning. PLOS Comput. Biol. 10:e1003770 [Google Scholar]
  73. Molina-Luna K, Hertler B, Buitrago MM, Luft AR. 2008. Motor learning transiently changes cortical somatotopy. NeuroImage 40:1748–54 [Google Scholar]
  74. Mukai I, Kim D, Fukunaga M, Japee S, Marrett S, Ungerleider LG. 2007. Activations in visual and attention-related areas predict and correlate with the degree of perceptual learning. J. Neurosci. 27:11401–11 [Google Scholar]
  75. Op de Beeck HP, Baker CI, DiCarlo JJ, Kanwisher NG. 2006. Discrimination training alters object representations in human extrastriate cortex. J. Neurosci. 26:13025–36 [Google Scholar]
  76. Otto TU, Öğmen H, Herzog MH. 2010. Perceptual learning in a nonretinotopic frame of reference. Psychol. Sci. 21:1058–63 [Google Scholar]
  77. Petrov AA, Dosher BA, Lu Z-L. 2005. The dynamics of perceptual learning: an incremental reweighting model. Psychol. Rev. 112:715–43 [Google Scholar]
  78. Piëch V, Li W, Reeke GN, Gilbert CD. 2013. Network model of top-down influences on local gain and contextual interactions in visual cortex. PNAS 110:E4108–17 [Google Scholar]
  79. Poggio T, Fahle M, Edelman S. 1992. Fast perceptual learning in visual hyperacuity. Science 256:1018–21 [Google Scholar]
  80. Polley DB, Steinberg EE, Merzenich MM. 2006. Perceptual learning directs auditory cortical map reorganization through top-down influences. J. Neurosci. 26:4970–82 [Google Scholar]
  81. Poort J, Khan AG, Pachitariu M, Nemri A, Orsolic I. et al. 2015. Learning enhances sensory and multiple non-sensory representations in primary visual cortex. Neuron 86:1478–90 [Google Scholar]
  82. Raiguel S, Vogels R, Mysore SG, Orban GA. 2006. Learning to see the difference specifically alters the most informative V4 neurons. J. Neurosci. 26:6589–602 [Google Scholar]
  83. Rainer G, Lee H, Logothetis NK. 2004. The effect of learning on the function of monkey extrastriate visual cortex. PLOS Biol. 2:275–83 [Google Scholar]
  84. Ramachandran VS, Braddick O. 1973. Orientation-specific learning in stereopsis. Perception 2:371–76 [Google Scholar]
  85. Recanzone GH, Merzenich MM, Jenkins WM. 1992a. Frequency discrimination training engaging a restricted skin surface results in an emergence of a cutaneous response zone in cortical area 3a. J. Neurophysiol. 67:1057–70 [Google Scholar]
  86. Recanzone GH, Merzenich MM, Jenkins WM, Grajski KA, Dinse HR. 1992b. Topographic reorganization of the hand representation in cortical area 3b of owl monkeys trained in a frequency-discrimination task. J. Neurophysiol. 67:1031–56 [Google Scholar]
  87. Recanzone GH, Schreiner CE, Merzenich MM. 1993. Plasticity in the frequency representation of primary auditory cortex following discrimination training in adult owl monkeys. J. Neurosci. 13:87–103 [Google Scholar]
  88. Reed A, Riley J, Carraway R, Carrasco A, Perez C. et al. 2011. Cortical map plasticity improves learning but is not necessary for improved performance. Neuron 70:121–31 [Google Scholar]
  89. Roelfsema PR, van Ooyen A, Watanabe T. 2010. Perceptual learning rules based on reinforcers and attention. Trends Cogn. Sci. 14:64–71 [Google Scholar]
  90. Saffell T, Matthews N. 2003. Task-specific perceptual learning on speed and direction discrimination. Vis. Res. 43:1365–74 [Google Scholar]
  91. Sagi D. 2011. Perceptual learning in Vision Research. Vis. Res. 51:1552–66 [Google Scholar]
  92. Schiltz C, Bodart JM, Dubois S, Dejardin S, Michel C. et al. 1999. Neuronal mechanisms of perceptual learning: changes in human brain activity with training in orientation discrimination. NeuroImage 9:46–62 [Google Scholar]
  93. Schoups A, Vogels R, Orban GA. 1995. Human perceptual learning in identifying the oblique orientation: retinotopy, orientation specificity and monocularity. J. Physiol. 483:797–810 [Google Scholar]
  94. Schoups A, Vogels R, Qian N, Orban G. 2001. Practising orientation identification improves orientation coding in V1 neurons. Nature 412:549–53 [Google Scholar]
  95. Schwartz S, Maquet P, Frith C. 2002. Neural correlates of perceptual learning: a functional MRI study of visual texture discrimination. PNAS 99:17137–42 [Google Scholar]
  96. Seitz AR, Kim D, Watanabe T. 2009. Rewards evoke learning of unconsciously processed visual stimuli in adult humans. Neuron 61:700–7 [Google Scholar]
  97. Series P, Latham PE, Pouget A. 2004. Tuning curve sharpening for orientation selectivity: coding efficiency and the impact of correlations. Nat. Neurosci. 7:1129–35 [Google Scholar]
  98. Shibata K, Watanabe T, Sasaki Y, Kawato M. 2011. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science 334:1413–15 [Google Scholar]
  99. Shiu L-P, Pashler H. 1992. Improvement in line orientation discrimination is retinally local but dependent on cognitive set. Percept. Psychophys. 52:582–88 [Google Scholar]
  100. Sigman M, Gilbert CD. 2000. Learning to find a shape. Nat. Neurosci. 3:264–69 [Google Scholar]
  101. Sigman M, Pan H, Yang Y, Stern E, Silbersweig D, Gilbert CD. 2005. Top-down reorganization of activity in the visual pathway after learning a shape identification task. Neuron 46:823–35 [Google Scholar]
  102. Song Y, Hu S, Li X, Li W, Liu J. 2010. The role of top-down task context in learning to perceive objects. J. Neurosci. 30:9869–76 [Google Scholar]
  103. Spillmann L, Dresp-Langley B, Tseng C-H. 2015. Beyond the classical receptive field: the effect of contextual stimuli. J. Vis. 15:97 [Google Scholar]
  104. Squire LR. 2009. The legacy of patient H.M. for neuroscience. Neuron 61:6–9 [Google Scholar]
  105. Squire LR, Stark CEL, Clark RE. 2004. The medial temporal lobe. Annu. Rev. Neurosci. 27:279–306 [Google Scholar]
  106. Squire LR, Zola SM. 1996. Structure and function of declarative and nondeclarative memory systems. PNAS 93:13515–22 [Google Scholar]
  107. Stănişor L, van der Togt C, Pennartz CMA, Roelfsema PR. 2013. A unified selection signal for attention and reward in primary visual cortex. PNAS 110:9136–41 [Google Scholar]
  108. Szwed M, Dehaene S, Kleinschmidt A, Eger E, Valabrègue R. et al. 2011. Specialization for written words over objects in the visual cortex. NeuroImage 56:330–44 [Google Scholar]
  109. Takeda M, Koyano KW, Hirabayashi T, Adachi Y, Miyashita Y. 2015. Top-down regulation of laminar circuit via inter-area signal for successful object memory recall in monkey temporal cortex. Neuron 86:840–52 [Google Scholar]
  110. Tartaglia EM, Bamert L, Herzog MH, Mast FW. 2012. Perceptual learning of motion discrimination by mental imagery. J. Vis. 12:614 [Google Scholar]
  111. Tartaglia EM, Bamert L, Mast FW, Herzog MH. 2009. Human perceptual learning by mental imagery. Curr. Biol. 19:2081–85 [Google Scholar]
  112. Thorndike EL, Woodworth RS. 1901a. The influence of improvement in one mental function upon the efficiency of other functions. (I). Psychol. Rev. 8:247–61 [Google Scholar]
  113. Thorndike EL, Woodworth RS. 1901b. The influence of improvement in one mental function upon the efficiency of other functions. II. The estimation of magnitudes. Psychol. Rev. 8:384–95 [Google Scholar]
  114. Turk-Browne NB, Scholl BJ, Chun MM, Johnson MK. 2009. Neural evidence of statistical learning: efficient detection of visual regularities without awareness. J. Cogn. Neurosci. 21:1934–45 [Google Scholar]
  115. Vaina LM, Belliveau JW, des Roziers EB, Zeffiro TA. 1998. Neural systems underlying learning and representation of global motion. PNAS 95:12657–62 [Google Scholar]
  116. Vidnyánszky Z, Sohn W. 2005. Learning to suppress task-irrelevant visual stimuli with attention. Vis. Res. 45:677–85 [Google Scholar]
  117. Vogels R, Orban GA. 1985. The effect of practice on the oblique effect in line orientation judgments. Vis. Res. 25:1679–87 [Google Scholar]
  118. Wang F, Huang J, Lv Y, Ma X, Yang B. et al. 2016. Predicting perceptual learning from higher-order cortical processing. NeuroImage 124:682–92 [Google Scholar]
  119. Wang R, Wang J, Zhang J-Y, Xie X-Y, Yang Y-X. et al. 2016. Perceptual learning at a conceptual level. J. Neurosci. 36:2238–46 [Google Scholar]
  120. Wang R, Zhang J-Y, Klein SA, Levi DM, Yu C. 2012. Task relevancy and demand modulate double-training enabled transfer of perceptual learning. Vis. Res. 61:33–38 [Google Scholar]
  121. Wang R, Zhang J-Y, Klein SA, Levi DM, Yu C. 2014. Vernier perceptual learning transfers to completely untrained retinal locations after double training: a “piggybacking” effect. J. Vis. 14:1312 [Google Scholar]
  122. Watanabe T, Nanez JE, Sasaki Y. 2001. Perceptual learning without perception. Nature 413:844–48 [Google Scholar]
  123. Watanabe T, Sasaki Y. 2015. Perceptual learning: toward a comprehensive theory. Annu. Rev. Psychol. 66:197–221 [Google Scholar]
  124. Weinberger NM. 1995. Dynamic regulation of receptive fields and maps in the adult sensory cortex. Annu. Rev. Neurosci. 18:129–58 [Google Scholar]
  125. Westheimer G, Truong TT. 1988. Target crowding in foveal and peripheral stereoacuity. Am. J. Optom. Physiol. Opt. 65:395–99 [Google Scholar]
  126. Wiesel TN, Hubel DH. 1963. Single-cell responses in striate cortex of kittens deprived of vision in one eye. J. Neurophysiol. 26:1003–17 [Google Scholar]
  127. Xiao L-Q, Zhang J-Y, Wang R, Klein SA, Levi DM, Yu C. 2008. Complete transfer of perceptual learning across retinal locations enabled by double training. Curr. Biol. 18:1922–26 [Google Scholar]
  128. Xue G, Dong Q, Chen C, Lu Z, Mumford JA, Poldrack RA. 2010. Greater neural pattern similarity across repetitions is associated with better memory. Science 330:97–101 [Google Scholar]
  129. Yamahachi H, Marik SA, McManus JNJ, Denk W, Gilbert CD. 2009. Rapid axonal sprouting and pruning accompany functional reorganization in primary visual cortex. Neuron 64:719–29 [Google Scholar]
  130. Yan Y, Rasch MJ, Chen M, Xiang X, Huang M. et al. 2014. Perceptual training continuously refines neuronal population codes in primary visual cortex. Nat. Neurosci. 17:1380–87 [Google Scholar]
  131. Yang T, Maunsell JHR. 2004. The effect of perceptual learning on neuronal responses in monkey visual area V4. J. Neurosci. 24:1617–26 [Google Scholar]
  132. Yotsumoto Y, Watanabe T, Sasaki Y. 2008. Different dynamics of performance and brain activation in the time course of perceptual learning. Neuron 57:827–33 [Google Scholar]
  133. Yu C, Klein SA, Levi DM. 2004. Perceptual learning in contrast discrimination and the (minimal) role of context. J. Vis. 4:3169–82 [Google Scholar]
  134. Zhang E, Li W. 2010. Perceptual learning beyond retinotopic reference frame. PNAS 107:15969–74 [Google Scholar]
  135. Zhang E, Zhang G-L, Li W. 2013. Spatiotopic perceptual learning mediated by retinotopic processing and attentional remapping. Eur. J. Neurosci. 38:3758–67 [Google Scholar]
  136. Zhang G-L, Li H, Song Y, Yu C. 2015. ERP C1 is top-down modulated by orientation perceptual learning. J. Vis. 15:108 [Google Scholar]
  137. Zhang J-Y, Zhang G-L, Xiao L-Q, Klein SA, Levi DM, Yu C. 2010. Rule-based learning explains visual perceptual learning and its specificity and transfer. J. Neurosci. 30:12323–28 [Google Scholar]
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Perceptual Learning: Use-Dependent Cortical Plasticity
Annual Review of Vision Science 2, 109 (2016); https://doi.org/10.1146/annurev-vision-111815-114351
/content/journals/10.1146/annurev-vision-111815-114351
/content/journals/10.1146/annurev-vision-111815-114351
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