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Annual Review of Vision Science

Volume 8, 2022

Sensory Perception in Autism: What Can We Learn?

Abstract

Autism is a neurodevelopmental disorder of unknown etiology. Recently, there has been a growing interest in sensory processing in autism as a core phenotype. However, basic questions remain unanswered. Here, we review the major findings and models of perception in autism and point to methodological issues that have led to conflicting results. We show that popular models of perception in autism, such as the reduced prior hypothesis, cannot explain the many and varied findings. To resolve these issues, we point to the benefits of using rigorous psychophysical methods to study perception in autism. We advocate for perceptual models that provide a detailed explanation of behavior while also taking into account factors such as context, learning, and attention. Furthermore, we demonstrate the importance of tracking changes over the course of development to reveal the causal pathways and compensatory mechanisms. We finally propose a developmental perceptual narrowing account of the condition.

Keyword(s): autism, Bayesian, development, perception, perceptual illusions, perceptual narrowing, psychophysics, sensory processing
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2022-09-15
2024-04-16
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Literature Cited

  1. Adams WJ, Graf EW, Ernst MO. 2004. Experience can change the ‘light-from-above’ prior. Nat. Neurosci. 7:101057–58
     [Google Scholar]
  2. APA (Am. Psychiatric Assoc.) 2013. Diagnostic and Statistical Manual of Mental Disorders (DSM-5) Washington, DC: APA. , 5th ed..
  3. Avraam R, Binur N, Hadad BS. 2019. Typical perceptual organization in autism: perceptual grouping and spatial distortion. Autism Res 12:111623–35
     [Google Scholar]
  4. Baker CI, Olson CR, Behrmann M. 2004. Role of attention and perceptual grouping in visual statistical learning. Psychol. Sci. 15:7460–66
     [Google Scholar]
  5. Bedford R, Pellicano E, Mareschal D, Nardini M. 2016. Flexible integration of visual cues in adolescents with autism spectrum disorder. Autism Res. 9:2272–81
     [Google Scholar]
  6. Behrmann M, Thomas C, Humphreys K. 2006. Seeing it differently: visual processing in autism. Trends Cogn. Sci. 10:6258–64
     [Google Scholar]
  7. Bertone A, Mottron L, Jelenic P, Faubert J. 2005. Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity. Brain 128:102430–41
     [Google Scholar]
  8. Binur N, Hel-Or H, Hadad B-S. 2022. Individuals with autism show non-adaptive relative weighting of perceptual prior and sensory reliability. Autism https://doi.org/10.1177/13623613221074416
    [Crossref] [Google Scholar]
  9. Blakemore C, Van Sluyters RC. 1975. Innate and environmental factors in the development of the kitten's visual cortex. J. Physiol. 248:3663–716
     [Google Scholar]
  10. Blakemore SJ, Tavassoli T, Calò S, Thomas RM, Catmur C et al. 2006. Tactile sensitivity in Asperger syndrome. Brain Cogn. 61:15–13
     [Google Scholar]
  11. Bölte S, Holtmann M, Poustka F, Scheurich A, Schmidt L. 2007. Gestalt perception and local-global processing in high-functioning autism. J. Autism Dev. Disord. 37:81493–504
     [Google Scholar]
  12. Bonnel A, McAdams S, Smith B, Berthiaume C, Bertone A et al. 2010. Enhanced pure-tone pitch discrimination among persons with autism but not Asperger syndrome. Neuropsychologia 48:92465–75
     [Google Scholar]
  13. Brock J. 2012. Alternative Bayesian accounts of autistic perception: comment on Pellicano and Burr. Trends Cogn. Sci. 16:12573–74
     [Google Scholar]
  14. Brock J, Xu JY, Brooks KR. 2011. Individual differences in visual search: relationship to autistic traits, discrimination thresholds, and speed of processing. Perception 40:6739–42
     [Google Scholar]
  15. Buckingham G, Michelakakis EE, Rajendran G. 2016. The influence of prior knowledge on perception and action: relationships to autistic traits. J. Autism Dev. Disord. 46:51716–24
     [Google Scholar]
  16. Cascio C, McGlone F, Folger S, Tannan V, Baranek G et al. 2008. Tactile perception in adults with autism: a multidimensional psychophysical study. J. Autism Dev. Disord. 38:1127–37
     [Google Scholar]
  17. Cascio CJ, Foss-Feig JH, Burnette CP, Heacock JL, Cosby AA. 2012. The rubber hand illusion in children with autism spectrum disorders: delayed influence of combined tactile and visual input on proprioception. Autism 16:4406–19
     [Google Scholar]
  18. Chen Y, Norton DJ, McBain R, Gold J, Frazier JA, Coyle JT. 2012. Enhanced local processing of dynamic visual information in autism: evidence from speed discrimination. Neuropsychologia 50:5733–39
     [Google Scholar]
  19. Chouinard PA, Noulty WA, Sperandio I, Landry O. 2013. Global processing during the Müller-Lyer illusion is distinctively affected by the degree of autistic traits in the typical population. Exp. Brain Res. 230:2219–31
     [Google Scholar]
  20. Church BA, Rice CL, Dovgopoly A, Lopata CJ, Thomeer ML et al. 2015. Learning, plasticity, and atypical generalization in children with autism. Psychon. Bull. Rev. 22:51342–48
     [Google Scholar]
  21. Collins AL, Ma D, Whitehead PL, Martin ER, Wright HH et al. 2006. Investigation of autism and GABA receptor subunit genes in multiple ethnic groups. Neurogenetics 7:3167–74
     [Google Scholar]
  22. Corbett BA, Muscatello RA, Blain SD. 2016. Impact of sensory sensitivity on physiological stress response and novel peer interaction in children with and without autism spectrum disorder. Front. Neurosci. 10:278
     [Google Scholar]
  23. Croydon A, Karaminis T, Neil L, Burr D, Pellicano E. 2017. The light-from-above prior is intact in autistic children. J. Exp. Child Psychol. 161:113–25
     [Google Scholar]
  24. De Jonge MV, Kemner C, de Haan EH, Coppens JE, van Den Berg TJTP, van Engeland H. 2007. Visual information processing in high-functioning individuals with autism spectrum disorders and their parents. Neuropsychology 21:165–73
     [Google Scholar]
  25. Dekker TM, Nardini M. 2016. Risky visuomotor choices during rapid reaching in childhood. Dev. Sci. 19:3427–39
     [Google Scholar]
  26. Dickinson A, Jones M, Milne E. 2014. Oblique orientation discrimination thresholds are superior in those with a high level of autistic traits. J. Autism Dev. Disord. 44:112844–50
     [Google Scholar]
  27. Donovan I, Szpiro S, Carrasco M. 2015. Exogenous attention facilitates location transfer of perceptual learning. J. Vis. 15:1011
     [Google Scholar]
  28. Dragoi V, Turcu CM, Sur M. 2001. Stability of cortical responses and the statistics of natural scenes. Neuron 32:61181–92
     [Google Scholar]
  29. Eigsti IM, Fein DA. 2013. More is less: pitch discrimination and language delays in children with optimal outcomes from autism. Autism Res 6:6605–13
     [Google Scholar]
  30. Elsabbagh M, Johnson MH. 2010. Getting answers from babies about autism. Trends Cogn. Sci. 14:281–87
     [Google Scholar]
  31. Falter CM, Elliott MA, Bailey AJ. 2012. Enhanced visual temporal resolution in autism spectrum disorders. PLOS ONE 7:3e32774
     [Google Scholar]
  32. Feigin H, Shalom-Sperber S, Zachor DA, Zaidel A. 2021. Increased influence of prior choices on perceptual decisions in autism. eLife 10:e61595
     [Google Scholar]
  33. Foss-Feig JH, Kwakye LD, Cascio CJ, Burnette CP, Kadivar H et al. 2010. An extended multisensory temporal binding window in autism spectrum disorders. Exp. Brain Res. 203:2381–89
     [Google Scholar]
  34. Foss-Feig JH, Tadin D, Schauder KB, Cascio CJ. 2013. A substantial and unexpected enhancement of motion perception in autism. J. Neurosci. 33:198243–49
     [Google Scholar]
  35. Friston K, Schwartenbeck P, FitzGerald T, Moutoussis M, Behrens T, Dolan RJ. 2013a. The anatomy of choice: active inference and agency. Front. Hum. Neurosci. 7:598
     [Google Scholar]
  36. Friston KJ, Lawson R, Frith CD. 2013b. On hyperpriors and hypopriors: comment on Pellicano and Burr. Trends Cogn. Sci. 17:11
     [Google Scholar]
  37. Furmanski CS, Engel SA. 2000. An oblique effect in human primary visual cortex. Nat. Neurosci. 3:6535–36
     [Google Scholar]
  38. Galle SA, Courchesne V, Mottron L, Frasnelli J. 2013. Olfaction in the autism spectrum. Perception 42:3341–55
     [Google Scholar]
  39. Girshick AR, Landy MS, Simoncelli EP. 2011. Cardinal rules: Visual orientation perception reflects knowledge of environmental statistics. Nat. Neurosci. 14:7926–32
     [Google Scholar]
  40. Gliga T, Bedford R, Charman T, Johnson MH, Baron-Cohen S et al. 2015. Enhanced visual search in infancy predicts emerging autism symptoms. Curr. Biol. 25:131727–30
     [Google Scholar]
  41. Gonzalez C, Martin JM, Minshew NJ, Behrmann M. 2013. Practice makes improvement: how adults with autism out-perform others in a naturalistic visual search task. J. Autism Dev. Disord. 43:102259–68
     [Google Scholar]
  42. Gopnik A, Griffiths TL, Lucas CG. 2015. When younger learners can be better (or at least more open-minded) than older ones. Curr. Dir. Psychol. Sci. 24:287–92
     [Google Scholar]
  43. Graham NVS. 1989. Visual Pattern Analyzers Oxford, UK: Oxford Univ. Press
  44. Granovetter MC, Burlingham CS, Blauch NM, Minshew NJ, Heeger DJ, Behrmann M. 2020. Uncharacteristic task-evoked pupillary responses implicate atypical locus ceruleus activity in autism. J. Neurosci. 40:193815–26
     [Google Scholar]
  45. Hadad BS, Goldstein EK, Russo NN. 2017. Atypical perception in autism: a failure of perceptual specialization?. Autism Res 10:91510–22
     [Google Scholar]
  46. Hadad BS, Russo N, Kimchi R, Babineau V, Burack JA 2019a. Typical utilization of gestalt grouping cues in shape perception by persons with autism spectrum disorder. Perception 48: 12.1175–96
     [Google Scholar]
  47. Hadad BS, Schwartz S. 2019. Perception in autism does not adhere to Weber's law. eLife 8:e42223
     [Google Scholar]
  48. Hadad BS, Schwartz S, Binur N. 2019b. Reduced perceptual specialization in autism: evidence from the other-race face effect. J. Exp. Psychol. Gen. 148:3588–94
     [Google Scholar]
  49. Hadad BS, Ziv Y 2015. Strong bias towards analytic perception in ASD does not necessarily come at the price of impaired integration skills. J. Autism Dev. Disord 45:61499–512
     [Google Scholar]
  50. Happé F, Frith U. 2006. The weak coherence account: detail-focused cognitive style in autism spectrum disorders. J. Autism Dev. Disord. 36:15–25
     [Google Scholar]
  51. Happé FG. 1996. Studying weak central coherence at low levels: Children with autism do not succumb to visual illusions. A research note. J. Child Psychol. Psychiatry 37:7873–77
     [Google Scholar]
  52. Harris H, Israeli D, Minshew N, Bonneh Y, Heeger DJ et al. 2015. Perceptual learning in autism: over-specificity and possible remedies. Nat. Neurosci. 18:111574–76
     [Google Scholar]
  53. Hartston M, Avidan A, Hadad B. 2022. Perceptual bias in face processing in autism reveals fast updating of unstable “typical” face internal representation. Autism Res In press
    [Google Scholar]
  54. Heeger DJ, Behrmann M, Dinstein I. 2017. Vision as a beachhead. Biol. Psychiatry 81:10832–37
     [Google Scholar]
  55. Helmholtz HL. 1962. Helmholtz's Treatise on Physiological Optics New York: Dover
  56. Hoy JA, Hatton C, Hare D. 2004. Weak central coherence: a cross-domain phenomenon specific to autism?. Autism 8:3267–81
     [Google Scholar]
  57. Jamain S, Radyushkin K, Hammerschmidt K, Granon S, Boretius S et al. 2008. Reduced social interaction and ultrasonic communication in a mouse model of monogenic heritable autism. PNAS 105:51710–15
     [Google Scholar]
  58. Jarrold C, Gilchrist ID, Bender A. 2005. Embedded figures detection in autism and typical development: preliminary evidence of a double dissociation in relationships with visual search. Dev. Sci. 8:4344–51
     [Google Scholar]
  59. Jones PR, Dekker TM. 2018. The development of perceptual averaging: learning what to do, not just how to do it. Dev. Sci. 21:3e12584
     [Google Scholar]
  60. Karaminis T, Cicchini GM, Neil L, Cappagli G, Aagten-Murphy D et al. 2016. Central tendency effects in time interval reproduction in autism. Sci. Rep. 6:128570
     [Google Scholar]
  61. Karvelis P, Seitz AR, Lawrie SM, Seriès P. 2018. Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration. eLife 7:e34115
     [Google Scholar]
  62. Kéïta L, Mottron L, Bertone A. 2010. Far visual acuity is unremarkable in autism: Do we need to focus on crowding?. Autism Res 3:6333–41
     [Google Scholar]
  63. Koh HC, Milne E, Dobkins K. 2010. Spatial contrast sensitivity in adolescents with autism spectrum disorders. J. Autism Dev. Disord. 40:8978–87
     [Google Scholar]
  64. Koldewyn K, Jiang YV, Weigelt S, Kanwisher N. 2013. Global/local processing in autism: not a disability, but a disinclination. J. Autism Dev. Disord. 43:102329–40
     [Google Scholar]
  65. Körding KP, Wolpert DM. 2006. Bayesian decision theory in sensorimotor control. Trends Cogn. Sci. 10:7319–26
     [Google Scholar]
  66. Lawson RP, Mathys C, Rees G. 2017. Adults with autism overestimate the volatility of the sensory environment. Nat. Neurosci. 20:91293–99
     [Google Scholar]
  67. Lawson RP, Rees G, Friston KJ. 2014. An aberrant precision account of autism. Front. Hum. Neurosci. 8:302
     [Google Scholar]
  68. Leitner Y. 2014. The co-occurrence of autism and attention deficit hyperactivity disorder in children–What do we know?. Front. Hum. Neurosci 8:268
     [Google Scholar]
  69. Lewkowicz DJ. 2014. Early experience and multisensory perceptual narrowing. Dev. Psychobiol. 56:2292–315
     [Google Scholar]
  70. Lieder I, Adam V, Frenkel O, Jaffe-Dax S, Sahani M, Ahissar M. 2019. Perceptual bias reveals slow-updating in autism and fast-forgetting in dyslexia. Nat. Neurosci. 22:2256–64
     [Google Scholar]
  71. Lu ZL, Dosher BA. 1999. Characterizing human perceptual inefficiencies with equivalent internal noise. J. Opt. Soc. Am. A 16:3764–78
     [Google Scholar]
  72. Maloney LT, Mamassian P. 2009. Bayesian decision theory as a model of human visual perception: testing Bayesian transfer. Vis. Neurosci. 26:1147–55
     [Google Scholar]
  73. Manning C, Kilner J, Neil L, Karaminis T, Pellicano E. 2017. Children on the autism spectrum update their behaviour in response to a volatile environment. Dev. Sci. 20:5e12435
     [Google Scholar]
  74. Manning C, Tibber MS, Charman T, Dakin SC, Pellicano E. 2015. Enhanced integration of motion information in children with autism. J. Neurosci. 35:186979–86
     [Google Scholar]
  75. Marciano H, Gal E, Kimchi R, Hedley D, Goldfarb Y, Bonneh YS. 2022. Visual detection and decoding skills of aerial photography by adults with autism spectrum disorder (ASD). J. Autism Dev. Disord. 52:31346–60
     [Google Scholar]
  76. Markram H, Rinaldi T, Markram K. 2007. The intense world syndrome—an alternative hypothesis for autism. Front. Neurosci. 1:177–96
     [Google Scholar]
  77. Matsui T, Uchida M, Fujino H, Tojo Y, Hakarino K. 2022. Perception of native and non-native phonemic contrasts in children with autistic spectrum disorder: effects of speaker variability. Clin. Linguist. Phon. 36:4–5417–35
     [Google Scholar]
  78. Milne E, Scope A. 2008. Are children with autistic spectrum disorders susceptible to contour illusions?. Br. J. Dev. Psychol. 26:191–102
     [Google Scholar]
  79. Milne E, Swettenham J, Hansen P, Campbell R, Jeffries H, Plaisted K. 2002. High motion coherence thresholds in children with autism. J. Child Psychol. Psychiatry 43:2255–63
     [Google Scholar]
  80. Mitchell P, Mottron L, Soulières I, Ropar D. 2010. Susceptibility to the Shepard illusion in participants with autism: reduced top-down influences within perception?. Autism Res 3:3113–19
     [Google Scholar]
  81. Mitchell P, Ropar D. 2004. Visuo-spatial abilities in autism: a review. Infant Child Dev 13:3185–98
     [Google Scholar]
  82. Mottron L, Burack JA 2001. Enhanced perceptual functioning in the development of autism. The Development of Autism: Perspectives from Theory and Research JA Burack, T Charman, N Yirmiya, PR Zelazo 131–48 Mahwah, NJ: Lawrence Erlbaum
     [Google Scholar]
  83. Mottron L, Dawson M, Soulières I, Hubert B, Burack J. 2006. Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception. J. Autism Dev. Disord. 36:127–43
     [Google Scholar]
  84. Nardini M, Bedford R, Mareschal D. 2010. Fusion of visual cues is not mandatory in children. PNAS 107:3917041–46
     [Google Scholar]
  85. Nardini M, Dekker TM. 2018. Observer models of perceptual development. Behav. Brain Sci. 41:e238
     [Google Scholar]
  86. Nardini M, Jones P, Bedford R, Braddick O. 2008. Development of cue integration in human navigation. Curr. Biol. 18:9689–93
     [Google Scholar]
  87. O'Riordan MA, Plaisted KC, Driver J, Baron-Cohen S. 2001. Superior visual search in autism. J. Exp. Psychol. Hum. Percept. Perform. 27:3719–30
     [Google Scholar]
  88. Park WJ, Schauder KB, Zhang R, Bennetto L, Tadin D. 2017. High internal noise and poor external noise filtering characterize perception in autism spectrum disorder. Sci. Rep. 7:117584
     [Google Scholar]
  89. Paton B, Hohwy J, Enticott PG. 2012. The rubber hand illusion reveals proprioceptive and sensorimotor differences in autism spectrum disorders. J. Autism Dev. Disord. 42:91870–83
     [Google Scholar]
  90. Pellicano E. 2013. Sensory symptoms in autism: a blooming, buzzing confusion?. Child Dev. Perspect. 7:3143–48
     [Google Scholar]
  91. Pellicano E, Burr D. 2012. When the world becomes ‘too real’: a Bayesian explanation of autistic perception. Trends Cogn. Sci. 16:10504–10
     [Google Scholar]
  92. Pellicano E, Gibson L, Maybery M, Durkin K, Badcock DR. 2005. Abnormal global processing along the dorsal visual pathway in autism: a possible mechanism for weak visuospatial coherence?. Neuropsychologia 43:71044–53
     [Google Scholar]
  93. Petzschner FH, Glasauer S, Stephan KE. 2015. A Bayesian perspective on magnitude estimation. Trends Cogn. Sci. 19:5285–93
     [Google Scholar]
  94. Pirrone A, Dickinson A, Gomez R, Stafford T, Milne E. 2017. Understanding perceptual judgment in autism spectrum disorder using the drift diffusion model. Neuropsychology 31:2173–80
     [Google Scholar]
  95. Pirrone A, Wen W, Li S, Baker DH, Milne E. 2018. Autistic traits in the neurotypical population do not predict increased response conservativeness in perceptual decision making. Perception 47:10–111081–96
     [Google Scholar]
  96. Plaisted K, O'Riordan M, Baron-Cohen S. 1998. Enhanced visual search for a conjunctive target in autism: a research note. J. Child Psychol. Psychiatry 39:5777–83
     [Google Scholar]
  97. Quinn PC, Lee K, Pascalis O, Tanaka JW. 2014. Evidence for a perceptual-to-social transition in infant categorization of other-race faces. J. Vis. 14:101264
     [Google Scholar]
  98. Quinn PC, Tanaka JW, Lee K, Pascalis O, Slater AM. 2013. Are faces special to infants? An investigation of configural and featural processing for the upper and lower regions of houses in 3- to 7-month-olds. Vis. Cogn. 21:123–37
     [Google Scholar]
  99. Rahnev D, Denison RN. 2018. Suboptimality in perceptual decision making. Behav. Brain Sci. 41:e223
     [Google Scholar]
  100. Robertson CE, Baron-Cohen S. 2017. Sensory perception in autism. Nat. Rev. Neurosci. 18:11671–84
     [Google Scholar]
  101. Robertson CE, Martin A, Baker CI, Baron-Cohen S. 2012. Atypical integration of motion signals in autism spectrum conditions. PLOS ONE 7:11e48173
     [Google Scholar]
  102. Ropar D, Mitchell P. 1999. Are individuals with autism and Asperger's syndrome susceptible to visual illusions?. J. Child Psychol. Psychiatry 40:81283–93
     [Google Scholar]
  103. Ropar D, Mitchell P. 2001. Susceptibility to illusions and performance on visuospatial tasks in individuals with autism. J. Child Psychol. Psychiatry 42:4539–49
     [Google Scholar]
  104. Rosenberg A, Patterson JS, Angelaki DE. 2015. A computational perspective on autism. PNAS 112:309158–65
     [Google Scholar]
  105. Rozenkrantz L, D'Mello AM, Gabrieli JD 2021. Enhanced rationality in autism spectrum disorder. Trends Cogn. Sci. 25:8685–96
     [Google Scholar]
  106. Rubenstein JLR, Merzenich MM. 2003. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav 2:5255–67
     [Google Scholar]
  107. Sanders SJ, Ercan-Sencicek AG, Hus V, Luo R, Murtha MT et al. 2011. Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism. Neuron 70:5863–85
     [Google Scholar]
  108. Sapey-Triomphe LA, Timmermans L, Wagemans J. 2021a. Priors bias perceptual decisions in autism, but are less flexibly adjusted to the context. Autism Res 14:61134–46
     [Google Scholar]
  109. Sapey-Triomphe LA, Weilnhammer VA, Wagemans J. 2021b. Associative learning under uncertainty in adults with autism: intact learning of the cue-outcome contingency, but slower updating of priors. Autism https://doi.org/10.1177/13623613211045026
    [Crossref] [Google Scholar]
  110. Sasson NJ. 2006. The development of face processing in autism. J. Autism Dev. Disord. 36:3381–94
     [Google Scholar]
  111. Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S et al. 2020. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 180:3568–84
     [Google Scholar]
  112. Schallmo MP, Kolodny T, Kale AM, Millin R, Flevaris AV et al. 2020. Weaker neural suppression in autism. Nat. Commun. 11:12675
     [Google Scholar]
  113. Skewes JC, Gebauer L. 2016. Brief report: suboptimal auditory localization in autism spectrum disorder: support for the Bayesian account of sensory symptoms. J. Autism Dev. Disord. 46:72539–47
     [Google Scholar]
  114. Smith PL, Little DR. 2018. Small is beautiful: in defense of the small-N design. Psychon. Bull. Rev. 25:62083–101
     [Google Scholar]
  115. Sokol S, Moskowitz A, Hansen V. 1987. Electrophysiological evidence for the oblique effect in human infants. Investig. Ophthalmol. Vis. Sci. 28:4731–35
     [Google Scholar]
  116. Stocker AA, Simoncelli EP. 2006. Noise characteristics and prior expectations in human visual speed perception. Nat. Neurosci. 9:4578–85
     [Google Scholar]
  117. Sweeny TD, Wurnitsch N, Gopnik A, Whitney D. 2015. Ensemble perception of size in 4–5-year-old children. Dev. Sci. 18:4556–68
     [Google Scholar]
  118. Sysoeva OV, Davletshina MA, Orekhova EV, Galuta IA, Stroganova TA. 2016. Reduced oblique effect in children with autism spectrum disorders (ASD). Front. Neurosci. 9:512
     [Google Scholar]
  119. Szpiro SF, Carrasco M. 2015. Exogenous attention enables perceptual learning. Psychol. Sci. 26:121854–62
     [Google Scholar]
  120. Tavassoli T, Latham K, Bach M, Dakin SC, Baron-Cohen S. 2011. Psychophysical measures of visual acuity in autism spectrum conditions. Vis. Res. 51:151778–80
     [Google Scholar]
  121. Taylor JL, Seltzer MM. 2010. Changes in the autism behavioral phenotype during the transition to adulthood. J. Autism Dev. Disord. 40:121431–46
     [Google Scholar]
  122. Tversky A, Kahneman D. 1974. Judgment under uncertainty: heuristics and biases. Science 185:41571124–31
     [Google Scholar]
  123. Van der Hallen R, Evers K, Brewaeys K, Van den Noortgate W, Wagemans J. 2015. Global processing takes time: a meta-analysis on local–global visual processing in ASD. Psychol. Bull. 141:3549–73
     [Google Scholar]
  124. Vishne G, Jacoby N, Malinovitch T, Epstein T, Frenkel O, Ahissar M. 2021. Slow update of internal representations impedes synchronization in autism. Nat. Commun. 12:15439
     [Google Scholar]
  125. Walter E, Dassonville P, Bochsler TM. 2009. A specific autistic trait that modulates visuospatial illusion susceptibility. J. Autism Dev. Disord. 39:2339–49
     [Google Scholar]
  126. Wang L, Mottron L, Peng D, Berthiaume C, Dawson M. 2007. Local bias and local-to-global interference without global deficit: a robust finding in autism under various conditions of attention, exposure time, and visual angle. Cogn. Neuropsychol 24:5550–74
     [Google Scholar]
  127. Wang S, Jiang M, Duchesne XM, Laugeson EA, Kennedy DP et al. 2015. Atypical visual saliency in autism spectrum disorder quantified through model-based eye tracking. Neuron 88:3604–16
     [Google Scholar]
  128. Werker JF, Tees RC. 1999. Influences on infant speech processing: toward a new synthesis. Annu. Rev. Psychol. 50:509–35
     [Google Scholar]
  129. Yashar A, Denison RN. 2017. Feature reliability determines specificity and transfer of perceptual learning in orientation search. PLOS Comput. Biol. 13:12e1005882
     [Google Scholar]
  130. Yizhar O, Fenno LE, Davidson TJ, Mogri M, Deisseroth K. 2011. Optogenetics in neural systems. Neuron 71:19–34
     [Google Scholar]
  131. Yotsumoto Y, Watanabe T, Sasaki Y. 2008. Different dynamics of performance and brain activation in the time course of perceptual learning. Neuron 57:6827–33
     [Google Scholar]
  132. Zaidel A, Goin-Kochel RP, Angelaki DE. 2015. Self-motion perception in autism is compromised by visual noise but integrated optimally across multiple senses. PNAS 112:206461–66
     [Google Scholar]
  133. Zhang JY, Zhang GL, Xiao LQ, Klein SA, Levi DM, Yu C 2010. Rule-based learning explains visual perceptual learning and its specificity and transfer. J. Neurosci. 30:3712323–28
     [Google Scholar]
/content/journals/10.1146/annurev-vision-093020-035217
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Sensory Perception in Autism: What Can We Learn?
Annual Review of Vision Science 8, 239 (2022); https://doi.org/10.1146/annurev-vision-093020-035217
/content/journals/10.1146/annurev-vision-093020-035217
/content/journals/10.1146/annurev-vision-093020-035217
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