Supplement 1. References for all articles included in the meta-analysis, including 5 articles that overlap 4 other source articles.

1-126

1. Aldaqre I, Paulus M, Sodian B. Referential gaze and word learning in adults with autism. Autism.

2015;19(8):944-955.

2. Amso D, Haas S, Tenenbaum E, Markant J, Sheinkopf SJ. Bottom-up attention orienting in young

children with autism. J Autism Dev Disord. 2014;44(3):664-673.

3. Anderson A. Visual scanning and pupillary responses in young children with autism spectrum

disorder. J Clin Exp Neuropsychol. 2006;28:1238-1256.

4. Au-Yeung SK, Kaakinen JK, Benson V. Cognitive perspective-taking during scene perception in

autism spectrum disorder: evidence from eye movements. Autism Res. 2014;7(1):84-93.

5. Au-Yeung SK, Kaakinen JK, Liversedge SP, Benson V. Processing of written irony in autism

spectrum disorder: an eye-movement study. Autism Res. 2015;8(6):749-760.

6. Bal E, Harden E, Lamb D, Van Hecke AV, Denver JW, Porges SW. Emotion recognition in children

with autism spectrum disorders: relations to eye gaze and autonomic state. J Autism Dev Disord.

2010;40(3):358-370.

7. Bedford R, Elsabbagh M, Gliga T, et al. Precursors to social and communication difficulties in

infants at-risk for autism: gaze following and attentional engagement. J Autism Dev Disord.

2012;42(10):2208-2218.

8. Bekele E, Crittendon J, Zheng Z, et al. Assessing the utility of a virtual environment for enhancing

facial affect recognition in adolescents with autism. J Autism Dev Disord. 2014;44(7):1641-1650.

9. Benjamin DP, Mastergeorge AM, McDuffie AS, Kover ST, Hagerman RJ, Abbeduto L. Effects of

labeling and pointing on object gaze in boys with fragile X syndrome: an eye-tracking study. Res

Dev Disabil. 2014;35(11):2658-2672.

10. Benson V, Piper J, Fletcher-Watson S. Aytpical saccadic scanning in autistic spectrum disorder.

Neuropsychologia. 2009;47:1178-1182.

11. Benson V, Castelhano MS, Au-Yeung SK, Rayner K. Eye movements reveal no immediate "WOW"

("which one's weird") effect in autism spectrum disorder. Q J Exp Psychol (Hove).

2012;65(6):1139-1150.

12. Benson V, Castelhano MS, Howard PL, Latif N, Rayner K. Looking, seeing and believing in autism:

Eye movements reveal how subtle cognitive processing differences impact in the social domain.

Autism Res. 2016;9(8):879-887.

13. Bird G, Press C, Richardson DC. The role of alexithymia in reduced eye-fixation in Autism

Spectrum Conditions. J Autism Dev Disord. 2011;41(11):1556-1564.

14. Birmingham E, Cerf M, Adolphs R. Comparing social attention in autism and amygdala lesions:

effects of stimulus and task condition. Soc Neurosci. 2011;6(5-6):420-435.

15. Boraston ZL, Corden B, Miles LK, Skuse DH, Blakemore SJ. Brief report: perception of genuine

and posed smiles by individuals with autism. J Autism Dev Disord. 2008;38(3):574-580.

16. Bradshaw J, Shic F, Chawarska K. Brief report: face-specific recognition deficits in young children

with autism spectrum disorders. J Autism Dev Disord. 2011;41(10):1429-1435.

17. Cassidy S, Ropar D, Mitchell P, Chapman P. Can adults with autism spectrum disorders infer

what happened to someone from their emotional response? Autism Res. 2014;7(1):112-123.

18. Cassidy S, Mitchell P, Chapman P, Ropar D. Processing of spontaneous emotional responses in

adolescents and adults with autism spectrum disorders: effect of stimulus type. Autism Res.

2015;8(5):534-544.

19. Chawarska K, Klin A, Paul R, Macari S, Volkmar F. A prospective study of toddlers with ASD:

short-term diagnostic and cognitive outcomes. J Child Psychol Psychiatry. 2009;50:1235-1245.

20. Chawarska K, Macari S, Shic F. Context modulates attention to social scenes in toddlers with

autism. J Child Psychol Psychiatry. 2012;53:903-913.

21. Chawarska K, Macari S, Shic F. Decreased spontaneous attention to social scenes in 6-month-old

infants later diagnosed with autism spectrum disorders. Biol Psychiatry. 2013;74:195-203.

22. Chevallier C, Parish-Morris J, McVey A, et al. Measuring social attention and motivation in autism

spectrum disorder using eye-tracking: stimulus type matters. Autism Res. 2015;8:620-8.

23. Dalton KM, Nacewicz BM, Alexander AL, Davidson RJ. Gaze-fixation, brain activation, and

amygdala volume in unaffected siblings of individuals with autism. Biol Psychiatry. 2007;61:512-20.

24. Dalton KM, Holsen L, Abbeduto L, Davidson RJ. Brain function and gaze fixation during facial-

emotion processing in fragile X and autism. Autism Res. 2008;1:231-239.

25. de Wit TCJ, Falck-Ytter T, von Hofsten C. Young children with autism spectrum disorder look

differently at positive versus negative emotional faces. Res Autism Spectr Disord. 2008;2:651-9.

26. Dundas EM, Best CA, Minshew NJ, Strauss MS. A lack of left visual field bias when individuals

with autism process faces. J Autism Dev Disord. 2012;42:1104-1111.

27. Elsabbagh M, Gliga T, Pickles A, et al. The development of face orienting mechanisms in infants

at-risk for autism. Behav Brain Res. 2013;251:147-154.

28. Falck-Ytter T, Fernell E, Gillberg C, von Hofsten C. Face scanning distinguishes social from

communication impairments in autism. Dev Sci. 2010;13:864-875.

29. Falck-Ytter T, Fernell E, Hedvall AL, von Hofsten C, Gillberg C. Gaze performance in children with

autism spectrum disorder when observing communicative actions. J Autism Dev Disord.

2012;42:2236-2245.

30. Falck-Ytter T, Rehnberg E, Bolte S. Lack of visual orienting to biological motion and audiovisual

synchrony in 3-year-olds with autism. PLoS One. 2013;8(7):e68816.

31. Falck-Ytter T, Thorup E, Bolte S. Brief report: Lack of processing bias for the objects other people

attend to in 3-year-olds with autism. J Autism Dev Disord. 2015;45:1897-1904.

32. Falck-Ytter T, Carlstrom C, Johansson M. Eye contact modulates cognitive processing differently

in children with autism. Child Dev. 2015;86:37-47.

33. Fletcher-Watson S, Leekam SR, Benson V, Frank MC, Findlay JM. Eye-movements reveal

attention to social information in autism spectrum disorder. Neuropsychologia. 2009;47:248-57.

34. Freeth M, Chapman P, Ropar D, Mitchell P. Do gaze cues in complex scenes capture and direct

the attention of high functioning adolescents with ASD? Evidence from eye-tracking. J Autism

Dev Disord. 2010;40:534-547.

35. Freeth M, Foulsham T, Chapman P. The influence of visual saliency on fixation patterns in

individuals with Autism Spectrum Disorders. Neuropsychologia. 2011;49:156-160.

36. Fujisawa TX, Tanaka S, Saito DN, Kosaka H, Tomoda A. Visual attention for social information and

salivary oxytocin levels in preschool children with autism spectrum disorders: an eye-tracking

study. Front Neurosci. 2014;8:295.

37. Gastgeb HZ, Wilkinson DA, Minshew NJ, Strauss MS. Can individuals with autism abstract

prototypes of natural faces? J Autism Dev Disord. 2011;41:1609-1618.

38. Gharib A, Mier D, Adolphs R, Shimojo S. Eyetracking of social preference choices reveals normal

but faster processing in autism. Neuropsychologia. 2015;72:70-79.

39. Groen WB, Rommelse N, de Wit T, et al. Visual scanning in very young children with autism and

their unaffected parents. Autism Res Treat. 2012;2012:748467.

40. Grossman RB, Steinhart E, Mitchell T, McIlvane W. "Look who's talking!" Gaze Patterns for

Implicit and Explicit Audio-Visual Speech Synchrony Detection in Children With High-Functioning

Autism. Autism Res. 2015;8:307-316.

41. Grynszpan O, Nadel J, Martin JC, et al. Self-monitoring of gaze in high functioning autism. J

Autism Dev Disord. 2012;42:1642-1650.

42. Guillon Q, Afzali MH, Roge B, Baduel S, Kruck J, Hadjikhani N. The Importance of Networking in

Autism Gaze Analysis. PLoS One. 2015;10(10):e0141191.

43. Han B, Tijus C, Le Barillier F, Nadel J. Morphing technique reveals intact perception of object

motion and distrubed perception of emotional expressions by low-functioning adolescents with

autism spectrum disorder. Res Dev Disabil. 2015;47:393-404.

44. Hanley M, McPhillips M, Mulhern G, Riby DM. Spontaneous attention to faces in Asperger

syndrome using ecologically valid static stimuli. Autism. 2013;17:754-761.

45. Hanley M, Riby DM, Carty C, Melaugh McAteer A, Kennedy A, McPhillips M. The use of eye-

tracking to explore social difficulties in cognitively able students with autism spectrum disorder:

A pilot investigation. Autism. 2015;19:868-873.

46. Hedley D, Young R, Brewer N. Using eye movements as an index of implicit face recognition in

autism spectrum disorder. Autism Res. 2012;5:363-379.

47. Hedley D, Brewer N, Young R. The effect of inversion on face recognition in adults with autism

spectrum disorder. J Autism Dev Disord. 2015;45:1368-1379.

48. Hernandez N, Metzger A, Magne R, et al. Exploration of core features of a human face by

healthy and autistic adults analyzed by visual scanning. Neuropsychologia. 2009;47:1004-1012.

49. Hosozawa M, Tanaka K, Shimizu T, Nakano T, Kitazawa S. How children with specific language

impairment view social situations: an eye tracking study. Pediatrics. 2012;129(6):e1453-1460.

50. Irwin JR, Brancazio L. Seeing to hear? Patterns of gaze to speaking faces in children with autism

spectrum disorders. Front Psychol. 2014;5:397.

51. Johnels JA, Gillberg C, Falck-Ytter T, Miniscalco C. Face-viewing patterns in young children with

autism spectrum disorders. J Speech Lang Hear Res. 2014;57:2246-2252.

52. Jones W, Carr K, Klin A. Absence of preferential looking to the eyes of approaching adults

predicts level of social disability in 2-year-old toddlers with autism spectrum disorder. Arch Gen

Psychiatry. 2008;65:946-954.

53. Jones W, Klin A. Attention to eyes is present but in decline in 2-6-month-old infants later

diagnosed with autism. Nature. 2013;504:427-431.

54. Joseph RM, Keehn B, Connolly C, Wolfe JM, Horowitz TS. Why is visual search superior in autism

spectrum disorder? Dev Sci. 2009;12:1083-1096.

55. Kaldy Z, Kraper C, Carter AS, Blaser E. Toddlers with Autism Spectrum Disorder are more

successful at visual search than typically developing toddlers. Dev Sci. 2011;14:980-988.

56. Keehn B, Joseph RM. Impaired prioritization of novel onset stimuli in autism spectrum disorder. J

Child Psychol Psychiatry. 2008;49:1296-1303.

57. Keehn B, Brenner LA, Ramos AI, Lincoln AJ, Marshall SP, Muller RA. Brief report: eye-movement

patterns during an embedded figures test in children with ASD. J Autism Dev Disord. 2009;39:383-7.

58. Kirchner JC, Hatri A, Heekeren HR, Dziobek I. Autistic symptomatology, face processing abilities,

and eye fixation patterns. J Autism Dev Disord. 2011;41:158-167.

59. Klin A, Jones W, Schultz R, Volkmar F, Cohen D. Visual fixation patterns during viewing of

naturalistic social situations as predictors of social competence in individuals with autism. Arch

Gen Psychiatry. 2002;59:809-816.

60. Klin A, Lin DJ, Gorrindo P, Ramsay G, Jones W. Two-year-olds with autism orient to non-social

contingencies rather than biological motion. Nature. 2009;459:257-261.

61. Kuhn G, Kourkoulou A, Leekam SR. How magic changes our expectations about autism. Psychol

Sci. 2010;21:1487-1493.

62. Loth E, Gomez JC, Happe F. When seeing depends on knowing: adults with Autism Spectrum

Conditions show diminished top-down processes in the visual perception of degraded faces but

not degraded objects. Neuropsychologia. 2010;48:1227-1236.

63. Loth E, Gomez JC, Happe F. Do high-functioning people with autism spectrum disorder

spontaneously use event knowledge to selectively attend to and remember context-relevant

aspects in scenes? J Autism Dev Disord. 2011;41:945-961.

64. Marsh LE, Pearson A, Ropar D, Hamilton AF. Predictive gaze during observation of irrational

actions in adults with autism spectrum conditions. J Autism Dev Disord. 2015;45:245-261.

65. McPartland JC, Webb SJ, Keehn B, Dawson G. Patterns of visual attention to faces and objects in

autism spectrum disorder. J Autism Dev Disord. 2011;41:148-157.

66. Mercadante MT, Macedo EC, Baptista PM, Paula CS, Schwartzman JS. Saccadic movements using

eye-tracking technology in individuals with autism spectrum disorders: pilot study. Arq

Neuropsiquiatr. 2006;64:559-562.

67. Muszkat M, de Mello CB, Munoz Pde O, et al. Face Scanning in Autism Spectrum Disorder and

Attention Deficit/Hyperactivity Disorder: Human Versus Dog Face Scanning. Front Psychiatry.

2015;6:150.

68. Nadig A, Lee I, Singh L, Bosshart K, Ozonoff S. How does the topic of conversation affect verbal

exchange and eye gaze? A comparison between typical development and high-functioning

autism. Neuropsychologia. 2010;48:2730-2739.

69. Nakano T, Tanaka K, Endo Y, et al. Atypical gaze patterns in children and adults with autism

spectrum disorders dissociated from developmental changes in gaze behaviour. Proc Biol Sci.

2010;277:2935-2943.

70. Neumann D, Spezio ML, Piven J, Adolphs R. Looking you in the mouth: abnormal gaze in autism

resulting from impaired top-down modulation of visual attention. Soc Cogn Affect Neurosci.

2006;1:194-202.

71. Norbury CF, Brock J, Cragg L, Einav S, Griffiths H, Nation K. Eye-movement patterns are

associated with communicative competence in autistic spectrum disorders. J Child Psychol

Psychiatry. 2009;50:834-842.

72. Noris B, Nadel J, Barker M, Hadjikhani N, Billard A. Investigating gaze of children with ASD in

naturalistic settings. PLoS One. 2012;7(9):e44144.

73. Nuske HJ, Vivanti G, Dissanayake C. Reactivity to fearful expressions of familiar and unfamiliar

people in children with autism: an eye-tracking pupillometry study. J Neurodev Disord.

2014;6:14.

74. Nuske HJ, Vivanti G, Dissanayake C. No evidence of emotional dysregulation or aversion to

mutual gaze in preschoolers with autism spectrum disorder: An eye-tracking pupillometry study.

J Autism Dev Disord. 2015;45:3433-3445.

75. Parish-Morris J, Chevallier C, Tonge N, Letzen J, Pandey J, Schultz RT. Visual attention to dynamic

faces and objects is linked to face processing skills: a combined study of children with autism

and controls. Front Psychol. 2013;4:185.

76. Pelphrey KA, Sasson NJ, Reznick JS, Paul G, Goldman BD, Piven J. Visual scanning of faces in

autism. J Autism Dev Disord. 2002;32:249-261.

77. Pierce K, Conant D, Hazin R, Stoner R, Desmond J. Preference for geometric patterns early in life

as a risk factor for autism. Arch Gen Psychiatry. 2011;68:101-109.

78. Pierce K, Marinero S, Hazin R, McKenna B, Barnes CC, Malige A. Eye tracking reveals abnormal

visual preference for geometric images as an early biomarker of an autism spectrum disorder

subtype associated with increased symptom severity. Biol Psychiatry. 2016;79:657-666.

79. Riby DM, Hancock PJ. Viewing it differently: social scene perception in Williams syndrome and

autism. Neuropsychologia. 2008;46:2855-2860.

80. Riby D, Hancock PJ. Looking at movies and cartoons: eye-tracking evidence from Williams

syndrome and autism. J Intellect Disabil Res. 2009;53:169-181.

81. Riby DM, Hancock PJ. Do faces capture the attention of individuals with Williams syndrome or

autism? Evidence from tracking eye movements. J Autism Dev Disord. 2009;39:421-431.

82. Riby DM, Hancock PJ, Jones N, Hanley M. Spontaneous and cued gaze-following in autism and

Williams syndrome. J Neurodev Disord. 2013;5:13.

83. Rice K, Moriuchi JM, Jones W, Klin A. Parsing heterogeneity in autism spectrum disorders: visual

scanning of dynamic social scenes in school-aged children. J Am Acad Child Adolesc Psychiatry.

2012;51:238-248.

84. Rutherford MD, Towns AM. Scan path differences and similarities during emotion perception in

those with and without autism spectrum disorders. J Autism Dev Disord. 2008;38:1371-1381.

85. Rutherford MD, Walsh JA, Lee V. Brief Report: Infants Developing with ASD Show a Unique

Developmental Pattern of Facial Feature Scanning. J Autism Dev Disord. 2015;45:2618-2623.

86. Saalasti S, Katsyri J, Tiippana K, Laine-Hernandez M, von Wendt L, Sams M. Audiovisual speech

perception and eye gaze behavior of adults with asperger syndrome. J Autism Dev Disord.

2012;42:1606-1615.

87. Santos A, Chaminade T, Da Fonseca D, Silva C, Rosset D, Deruelle C. Just another social scene:

evidence for decreased attention to negative social scenes in high-functioning autism. J Autism

Dev Disord. 2012;42:1790-1798.

88. Sasson N, Tsuchiya N, Hurley R, et al. Orienting to social stimuli differentiates social cognitive

impairment in autism and schizophrenia. Neuropsychologia. 2007;45:2580-2588.

89. Sasson NJ, Turner-Brown LM, Holtzclaw TN, Lam KS, Bodfish JW. Children with autism

demonstrate circumscribed attention during passive viewing of complex social and nonsocial

picture arrays. Autism Res. 2008;1:31-42.

90. Sasson NJ, Elison JT, Turner-Brown LM, Dichter GS, Bodfish JW. Brief report: Circumscribed

attention in young children with autism. J Autism Dev Disord. 2011;41:242-247.

91. Sasson NJ, Touchstone EW. Visual attention to competing social and object images by preschool

children with autism spectrum disorder. J Autism Dev Disord. 2014;44:584-592.

92. Sasson NJ, Pinkham AE, Weittenhiller LP, Faso DJ, Simpson C. Context Effects on Facial Affect

Recognition in Schizophrenia and Autism: Behavioral and Eye-Tracking Evidence. Schizophr Bull.

2016;42:675-683.

93. Schwartzman JS, Velloso Rde L, D'Antino ME, Santos S. The eye-tracking of social stimuli in

patients with Rett syndrome and autism spectrum disorders: a pilot study. Arq Neuropsiquiatr.

2015;73:402-407.

94. Senju A, Southgate V, Miura Y, et al. Absence of spontaneous action anticipation by false belief

attribution in children with autism spectrum disorder. Dev Psychopathol. 2010;22:353-360.

95. Shi L, Zhou Y, Ou J, et al. Different visual preference patterns in response to simple and complex

dynamic social stimuli in preschool-aged children with autism spectrum disorders. PLoS One.

2015;10:e0122280.

96. Shic F, Chawarska K, Bradshaw J, Scassellati B. Autism, eye-tracking, entropy. 2008 7th IEEE

International Conference on Development and Learning. 2008:73-78.

97. Shic F, Bradshaw J, Klin A, Scassellati B, Chawarska K. Limited activity monitoring in toddlers with

autism spectrum disorder. Brain Res. 2011;1380:246-254.

98. Shic F, Macari S, Chawarska K. Speech disturbs face scanning in 6-month-old infants who

develop autism spectrum disorder. Biol Psychiatry. 2014;75:231-237.

99. Snow J, Ingeholm JE, Levy IF, et al. Impaired visual scanning and memory for faces in high-

functioning autism spectrum disorders: it's not just the eyes. J Int Neuropsychol Soc.

2011;17:1021-1029.

100. Speer LL, Cook AE, McMahon WM, Clark E. Face processing in children with autism: effects of

stimulus contents and type. Autism. 2007;11:265-277.

101. Spezio ML, Adolphs R, Hurley RS, Piven J. Abnormal use of facial information in high-functioning

autism. J Autism Dev Disord. 2007;37:929-939.

102. Stagg SD, Linnell KJ, Heaton P. Investigating eye movement patterns, language, and social ability

in children with autism spectrum disorder. Dev Psychopathol. 2014;26:529-537.

103. Sterling L, Dawson G, Webb S, et al. The role of face familiarity in eye tracking of faces by

individuals with autism spectrum disorders. J Autism Dev Disord. 2008;38:1666-1675.

104. Tenenbaum E, Amso D, Abar B, Sheinkopf SJ. Attention and word learning in autistic, language

delayed, and typically developing children. Frontiers in Psychology. 2014;5:1-9.

105. Trembath D, Vivanti G, Iacono T, Dissanayake C. Accurate or assumed: visual learning in children

with ASD. J Autism Dev Disord. 2015;45:3276-3287.

106. Trepagnier C, Sebrechts MM, Peterson R. Atypical face gaze in autism. Cyberpsychol Behav.

2002;5:213-217.

107. van der Geest JN, Kemner C, Camfferman G, Verbaten MN, van Engeland H. Looking at images

with human figures: comparison between autistic and normal children. J Autism Dev Disord.

2002;32:69-75.

108. van der Geest JN, Kemner C, Verbaten MN, van Engeland H. Gaze behavior of children with

pervasive developmental disorder toward human faces: a fixation time study. J Child Psychol

Psychiatry. 2002;43:669-678.

109. Van Herwegen J, Smith TJ, Dimitriou D. Exploring different explanations for performance on a

theory of mind task in Williams syndrome and autism using eye movements. Res Dev Disabil.

2015;45-46:202-209.

110. Vivanti G, Nadig A, Ozonoff S, Rogers SJ. What do children with autism attend to during imitation

tasks? J Exp Child Psychol. 2008;101(3):186-205.

111. Vivanti G, McCormick C, Young GS, et al. Intact and impaired mechanisms of action

understanding in autism. Dev Psychol. 2011;47(3):841-856.

112. Vivanti G, Dissanayake C. Propensity to imitate in autism is not modulated by the model's gaze

direction: an eye-tracking study. Autism Res. 2014;7(3):392-399.

113. Vivanti G, Trembath D, Dissanayake C. Atypical monitoring and responsiveness to goal-directed

gaze in autism spectrum disorder. Experimental Brain Research. 2014;232(2):695-701.

114. Wagner JB, Hirsch SB, Vogel-Farley VK, Redcay E, Nelson CA. Eye-tracking, autonomic, and

electrophysiological correlates of emotional face processing in adolescents with autism

spectrum disorder. J Autism Dev Disord. 2013;43(1):188-199.

115. Wang S, Jiang M, Duchesne XM, et al. Atypical Visual Saliency in Autism Spectrum Disorder

Quantified through Model-Based Eye Tracking. Neuron. 2015;88(3):604-616.

116. Wass SV, Jones EJ, Gliga T, et al. Shorter spontaneous fixation durations in infants with later

emerging autism. Sci Rep. 2015;5:8284.

117. White SW, Maddox BB, Panneton RK. Fear of negative evaluation influences eye gaze in

adolescents with autism spectrum disorder: A pilot study. J Autism Dev Disord. 2015;45:3446-57.

118. Wild KS, Poliakoff E, Jerrison A, Gowen E. Goal-directed and goal-less imitation in autism

spectrum disorder. J Autism Dev Disord. 2012;42(8):1739-1749.

119. Wilson CE, Brock J, Palermo R. Attention to social stimuli and facial identity recognition skills in

autism spectrum disorder. J Intellect Disabil Res. 2010;54(12):1104-1115.

120. Wilson CE, Palermo R, Brock J. Visual scan paths and recognition of facial identity in autism

spectrum disorder and typical development. PLoS One. 2012;7(5):e37681.

121. Yi L, Liu Y, Li Y, Fan Y, Huang D, Gao D. Visual Scanning Patterns during the Dimensional Change

Card Sorting Task in Children with Autism Spectrum Disorder. Autism Res Treat.

2012;2012:123053.

122. Yi L, Fan Y, Quinn PC, et al. Abnormality in face scanning by children with autism spectrum

disorder is limited to the eye region: evidence from multi-method analyses of eye tracking data.

J Vis. 2013;13(10).

123. Yi L, Feng C, Quinn PC, et al. Do individuals with and without autism spectrum disorder scan

faces differently? A new multi-method look at an existing controversy. Autism Res. 2014;7:72-83.

124. Yi L, Quinn PC, Feng C, Li J, Ding H, Lee K. Do individuals with autism spectrum disorder process

own- and other-race faces differently? Vision Res. 2015;107:124-132.

125. Zamzow RM, Christ SE, Saklayen SS, et al. Effect of propranolol on facial scanning in autism

spectrum disorder: a preliminary investigation. J Clin Exp Neuropsychol. 2014;36:431-445.

126. Zwickel J, White SJ, Coniston D, Senju A, Frith U. Exploring the building blocks of social cognition:

spontaneous agency perception and visual perspective taking in autism. Soc Cogn Affect

Neurosci. 2011;6:564-571.

Note: Reference #96 incorrectly reported standard errors as standard deviations. The erratum referenced below alludes to this problem. The correct effect sizes were calculated and included in the present meta-analysis.

Chita-Tegmark M. Review Journal of Autism and Developmental Disorders (2016) 3: 400. doi:10.1007/s40489-016-0089-6.

Table S1. Compliance With Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines for the Conduct of Meta-Analyses

Guideline PRISMA # Location Addressed in the Present StudyDescriptive title 1 TitleAbstract 2 Abstract

IntroductionRationale 3 pgs. 3-4Hypothesis/Objectives 4 pg. 4-5

MethodsProtocol and registration 5 N/AEligibility criteria 6 pg. 5-6Information sources 7 pg. 5-6Search strategy 8 pg. 5-6Study selection 9 pgs. 5-6 and Figure 1Data collection processes 10 pg. 6-7Data items 11 pg. 6-7Risk of bias in individual studies 12 Design and Reporting Quality Index, pg. 7Summary measures 13 pg. 8, Hedge’s gSynthesis of results 14 pgs. 8-9Risk of bias across studies 15 pgs. 10, rank correlation testAdditional analyses 16 pg. 10

ResultsStudy selection 17 Figure 1Study characteristics 18 Tables S2 and S4Risk of bias within studies 19 pgs. 12Results of individual studies 20 Available by requestSynthesis of results 21 pg. 10-11, Tables 1 and 2, Figures 2-3Risk of bias across studies 22 pg. 12, Figure S3Additional analyses 23 pg. 11-12, Figures S1 and S2, Table S4

DiscussionSummary of evidence 24 pgs. 13-16Limitations 25 pg. 16Conclusions 26 pgs. 17

FundingFunding 27 Author disclosures

Note. Search criteria and inclusion/exclusion criteria were a priori specified by first author. However, study protocol was not formally drafted or registered.

Supplement 2. Ordinal Codes for Sampling Rate and Points of Calibration.

Sampling Rate

4 = >120Hz

3 = 120Hz

2 = 60 to <120Hz

1 <60Hz

Points of Calibration

3= 6 or greater points

2= 5 points

1 = <5 points

Note: Validation of calibration accuracy was not reported for the vast majority of studies and, therefore, points of calibration were used as a proxy variable for calibration accuracy. However, it should be noted that lower numbers of calibration points are often used in calibrating younger children and this would not necessarily indicate lower calibration accuracy.

Supplement 3. Definitions of Stimulus Feature Coding

Audio-Visual = sound presented with visual stimuli.

Dynamic = any movement in the stimulus.

Face Only = the stimulus included only a face (human, animated, or avatar) or an upper torso with the face regions dominating the presentation.

Human = any human figure present in the stimulus. The human figure had to include at least a face. Body parts only (e.g., a human hand) were not counted as a human figure.

Interactive = any static or dynamic image involving at least two human or animated figures that are posed in a possible state of interacting (e.g., looking at one another, in close proximity, body oriented to each other, or conducting actions that imply interaction).

Number of Stimuli = the number of stimulus presentations included in the calculation of gaze measures to the region of interest.

Directive = the participant viewing the stimulus was given a verbal or visual direction beyond simply looking at the screen. Most often this was a directive to remember something or to track specific objects.

Supplement 4. Examples of Social and Nonsocial Regions of Interest (ROIs)

Social ROIs were defined as those regions coded within a study where the expectation was that gaze would be directed for a substantial proportion of the viewing time. Examples included human and animated character faces and face regions, objects that were designated by a human actor (e.g., joint attention paradigms). Faces and face regions were always considered social ROIs even if the face was not the primary person in the scene. In one study by Sasson (2007), faces were presented within social scenes, but the face was digitally removed from the scene. In this case, the face ROI was designated as nonsocial because the expectation was that individuals would attend to other aspects of the scene after identifying that the face was missing. Other body ROIs (e.g., torso/neck, shirt, pants/legs, etc.) were always considered nonsocial. In stimuli presenting nature scenes (e.g., mountains, waterfalls, etc.) where the ROI was the entire scene, the ROI was designated as social because the participant’s expectation was to look at the scene. Several studies presented human faces or human interactions versus digital geometric images in a side-by-side fashion. For these stimuli, the side with the face or human interaction was designated as social and the side with digital geometric images was designated as nonsocial.

The image below is from our recent study and provides an example of how social versus nonsocial ROIs are designated. This study was published in 2016 and therefore was not included in this meta-analysis but provides a visual example of the general coding scheme. In this image, the two human faces, the hand gesture, and the trash can were coded as social ROIs, while the picture, plate, and body regions (not designated) were designated as nonsocial ROIs.

It is also important to note that nonsocial ROIs were not simply the inverse of social ROIs for most stimuli. Rather, effects for nonsocial and social ROIs tended to be modestly correlated within studies, and in our own work, the correlation is typically negative but quite small r|<.10|. It is theoretically possible that anything not coded as a social ROI could be considered a nonsocial ROI. However, studies tended to select specific ROIs that did not represent all of the remaining regions.

Taxonomy of Social Versus Nonsocial ROIs

Social

Eyes

Whole face

Upper face

Lower face

Face ratio (upper/lower)

Mouth

Nose

Non-body (designated as target by task or human figure within stimuli)

Nonsocial

Other face (ears, hair, beard)

Other body (torso/neck, shirt, pants/legs)

An anonymous reviewer pointed out that in at least some cases (e.g., the natural scenes described above), this may not represent a socially important region, but rather simply where individuals were expected to look. We maintain the social vs. nonsocial distinction for simplicity and because it likely describes most instances, while acknowledging this as true for at least some ROIs.

Supplement 5. Variables Contributing to the Design and Reporting Quality Index Scoring

1. Age matched?2. Autism sex reported?3. Control sex reported?4. Sex matched?5. Diagnostic system reported?6. ADI-R used?7. ADOS used?8. Autism IQ reported?9. Control IQ reported?10. IQ matched?11. Sampling rate specified?12. Points of calibration specified?

Total Possible: 12

Note: ADI-R=Autism Diagnostic Interview-Revised; ADOS=Autism Diagnostic Observation Schedule.

The design and reporting quality index mixes the quality of reporting (e.g., IQ reported for the autism group?) as well as aspects important for study quality (e.g., were ages matched?). Post hoc analyses separating variables emphasizing reporting versus variables emphasizing design quality indicated significant effects for both aspects of the index (design quality b=-.05, SE=.03, z=2.08, p=.038; reporting quality b=-.09, SE=.03, z=3.62, p<.001).

Item-total correlations between the design and reporting quality variables and the total score ranged from r=.06-.69 with the largest item-total correlations being for autism and control IQs being reported (r=.62 and .69), and the lowest correlations being for sampling rate and points of calibration being reported (r=.06 and r=.15).

Per a reviewer suggestion, eye tracker manufacturer was also coded (Tobii, SMI, Eyelink, ISCAN, and other). Post hoc analysis including this variable with other methodological factors identified nominally significantly larger effect sizes for the ISCAN tracker (b=.30, SE=.14, z=2.27, p=.023) relative to other tracker manufacturers. Future studies may attempt to identify the source of this apparent difference, but the above results do not suggest that the effect sizes reported in the literature are artificially inflated due to one type of eye tracker manufacturer being differentially represented.

Per a reviewer suggestion, we also examined the interaction between eye tracking measure (e.g., fixation count, fixation duration, etc.) and social (vs. nonsocial) ROI type. None of the interactions were significant (largest b=-.08, SE=.11, z=-0.76, p=.448).

Table S2. Summary of Participant Characteristics Across All Studies.

Autism Healthy Controls DD Controlsn (mean n per study) 2,199 (17.8) 2,148 (20.0) 416 (19.8)Mean age (SD, range) 14.8 (10.6, 4 months – 40 years) 14.5 (10.8, 4 months – 40 years) 7.6 (10.3, 6 months – 35 years)Mean sex % (SD, range) 84.0% (12.1%, 46%-100%) 74.4% (20.0%, 0%-100%) 70.8% (19.0%, 20%-100%)Mean IQ in SS (SD, range)a 94.7 (18.1, 44-120) 108.2 (8.3, 72-124) 87.5 (12.1, 58-102)IQ difference (SD, range) - +12.1 (15.2, -12 to +60) +5.7 (8.0, -9 to +17)Note. DD=Developmental disability controls; SS=Standard Score (M=100, SD=15). a23 studies had IQ levels SS<80 and 6 of these studies were published in 2011 or earlier.

Table S3. Counts of Modifier Variables Across All Studies.

Design and Reporting Quality Index Yes NoAge Matched? 840 315Autism Sex Reported? 1049 106Control Sex Reported? 1025 130Sex Matched? 695 366Diagnostic System Reported? 818 237ADI-R Used? 546 609ADOS Used? 708 447Autism IQ Reported? 942 213Control IQ Reported? 852 303IQ Matched? 528 400Sample Rate Specified? 991 64Points of Calibration Specified? 796 359Stimulus Modifiers Yes NoAudio-Visual (vs. Visual only) 280 875Human 958 197Dynamic (vs. Static) 453 702Face Only 479 676Interactive 263 892Directive 365 790Region-of-Interest Modifiers Yes NoSocial (vs. Nonsocial) 860 295Body Regions

Eyes 181 974Whole Face 192 963Upper Face 9 1146Lower Face 9 1146Face Ratio (Upper/Lower) 23 1132Mouth 150 1005Nose 36 1119Other Body 39 1116

Non-Body 469 686Other Face 47 1108

Note: ADI-R=Autism Diagnostic Interview-Revised; ADOS=Autism Diagnostic Observation Schedule.

Table S4. Summary of Study Sample Characteristics.

UniqueSample #

Ref # First Author Year NestedEffects

Control Type

Autism Age(in years)

Autism Sex(%)

AutismIQ

(SS)

ROI Type Method QualityIndex

(out of 12)1 1 Aldagre 2015 15 Healthy 36.9 60 119.1 Both 72 2 Amso 2014 1 Healthy 3.5 60 68.8 Social 73 3 Anderson 2006 8 Both 4.1 89 76.0 Social 84 4 Au-Yeung 2014 16 Healthy 29.8 83 111.0 Both 95 5 Au-Yueng 2015 4 Healthy 36.0 100 116.8 Both 86 6 Bal 2010 18 Healthy 10.3 94 104.1 Both 97 7 Bedford 2012 12 Both .6 - 97.8 Both 88 8 Bekele 2014 6 Healthy 14.7 - 116.5 Both 69 9 Benjamin 2014 4 Healthy 6.9 100 69.3 Social 7

10 10 Benson 2009 12 Healthy 19.0 - 88.0 Both 611 11 Benson 2012 2 Healthy 29.5 71 110.2 Social 712 12 Benson 2016 4 Healthy 31.3 83 113.0 Social 1013 13 Bird 2011 2 Healthy 40.5 77 115.0 Social 714 14 Birmingham 2011 7 Healthy 31.6 89 108.8 Both 1015 15 Boraston 2008 4 Healthy 34.6 82 120.0 Social 816 16 Bradshaw 2011 9 Healthy 3.3 90 79.0 Social 917 17 Cassidy 2014 4 Healthy 36.4 63 117.1 Social 1018 18 Cassidy 2015 8 Healthy 17.3 88 92.2 Social 919 19 Chawarska 2009 12 Healthy 2.2 84 85.0 Both 1020 20 Chawarska 2012 32 Both 1.8 85 77.0 Social 821 21 Chawarska 2013 15 Both 6.5 64 92.0 Social 922 22 Chevallier 2015 6 Healthy 12.2 93 95.1 Both 1023 23 Dalton 2007 3 Healthy 14.4 67 110.0 Social 824 24 Dalton 2008 3 Healthy 15.9 100 87.2 Social 625 25 De Wit 2008 3 Healthy 5.2 85 - Social 626 26 Dundas 2012 2 Healthy 18.9 90 109.0 Social 927 27 Elsabbagh 2013 12 Both .6 65 92.1 Social 1128 28 Falck-Ytter 2010 2 Healthy 5.2 80 55.0 Social 9

29 29 Falck-Ytter 2012 7 Healthy 6.2 - 79.0 Both 530 30 Falck-Ytter 2013 2 Healthy 3.4 80 55.0 Social 931 31 Falck-Ytter 2015 4 Both 3.6 77 62.5 Both 1032 32 Falck-Ytter 2015 2 Healthy 6.7 90 104.0 Social 933 33 Fletcher-Watson 2009 20 Healthy 18.8 83 91.3 Both 834 34 Freeth 2010 15 Healthy 13.8 88 97.0 Both 1035 35 Freeth 2011 8 Healthy 14.9 88 101.3 Both 936 36 Fujisawa 2014 12 Healthy 4.8 84 77.7 Both 737 37 Gastgeb 2011 6 Healthy 22.9 100 108.7 Social 938 38 Gharib 2015 15 Healthy 35.4 75 113.1 Social 1039 39 Groen 2012 24 Healthy 3.1 70 - Social 740 40 Grossman 2015 30 Healthy 11.8 93 104.0 Both 1141 41 Grynszpan 2012 2 Healthy 20.2 92 90.5 Both 642 42 Guillon 2015 5 Healthy 3.4 80 82.6 Both 1043 43 Han 2015 4 Healthy 19.5 100 44.0 Social 944 44 Hanley 2013 36 Healthy 20.5 - - Both 645 45 Hanley 2015 5 Healthy 26.0 63 111.0 Both 1046 46 Hedley 2012 15 Healthy 28.1 65 107.7 Social 947 47 Hedley 2015 4 Healthy 28.9 62 106.6 Both 1048 48 Hernandez 2009 36 Healthy 24.1 100 101.2 Both 749 49 Hosozawa 2012 10 Both 4.9 84 63.0 Social 650 50 Irwin 2014 6 Healthy 10.2 80 92.1 Both 1051 51 Johnels 2014 3 Healthy 4.4 91 - Both 652 52 Jones 2008 8 Both 2.3 73 78.0 Both 1053 53 Jones 2013 4 Healthy 1.0 100 97.3 Both 1054 54 Joseph 2009 2 Healthy 14.6 81 107.0 Social 1055 55 Kaldy 2011 2 Healthy 2.5 82 60.1 Both 656 56 Keehn 2008 3 Healthy 14.1 86 109.0 Both 1157 57 Keehn 2009 4 Healthy 12.9 - 109.0 Both 858 58 Kirchner 2011 6 Healthy 31.9 75 112.6 Social 1159 59 Klin 2002 4 Healthy 15.4 100 101.3 Both 1160 60 Klin 2009 4 Both 2.2 - 90.0 Social 661 61 Kuhn 2010 5 Healthy 19.0 80 101.3 Social 11

62 62 Loth 2010 11 Healthy 25.6 79 98.3 Both 963 63 Loth 2011 2 Healthy 27.5 85 108.0 Both 864 64 Marsh 2015 5 Healthy 22.0 95 94.7 Both 865 65 McPartland 2011 20 Healthy 14.5 87 115.1 Social 1166 66 Mercadante 2006 2 Healthy 15.9 100 - Social 567 67 Muszkat 2015 12 Both 11.6 87 - Social 568 68 Nadig 2010 1 Healthy 11.4 83 106.5 Social 969 69 Nakano 2010a 4 Healthy 29.5 67 104.0 Social 670 69 Nakano 2010b 4 Healthy 4.9 84 60.2 Social 671 70 Neumann 2006 6 Healthy 23.0 100 104.0 Social 1172 71 Norbury 2009 8 Healthy 14.9 100 96.6 Both 1073 72 Noris 2012 2 Healthy 5.3 90 - Social 574 73, 74 Nuske 2014/2015 3 Healthy 4.1 83 68.5 Social 975 75 Parish-Morris 2013 2 Healthy 11.3 88 111.6 Social 1176 76 Pelphrey 2002 19 Healthy 25.2 100 100.8 Social 877 77 Pierce 2011 2 Both 2.2 81 78.4 Non-Social 1178 78 Pierce 2016 3 Both 2.3 76 77.0 Non-Social 879 79, 80, 81 Riby 2008/2009 45 Healthy 12.3 75 - Both 580 82 Riby 2013 10 Healthy 11.3 81 - Both 581 83 Rice 2012 5 Healthy 10.0 81 112.0 Both 1082 84 Rutherford 2008 2 Healthy 25.8 100 91.8 Social 783 85 Rutherford 2015 8 Healthy .3 80 - Social 684 86 Saalasti 2012 16 Healthy 33.0 78 107.0 Both 1085 87 Santos 2012 2 Healthy 18.4 87 102.3 Social 1086 88 Sasson 2007 12 Both 23.0 100 107.8 Both 1187 89 Sasson 2008 16 Healthy 9.6 93 99.5 Both 1088 90 Sasson 2011 16 Healthy 3.6 89 - Both 789 91 Sasson 2014 6 Healthy 3.8 93 73.6 Both 1090 92 Sasson 2015 6 Both 23.4 86 101.5 Social 991 93 Schwartzman 2015 4 Healthy 8.5 100 - Both 192 94 Senju 2010 1 Healthy 7.8 92 79.7 Social 793 95 Shi 2015 16 Healthy 5.1 92 55.8 Both 1094 96 Shic 2008 8 Healthy 2.1 - - Both 3

95 97 Shic 2011 14 Both 1.7 79 89.9 Both 996 98 Shic 2014 12 Both .5 67 92.0 Both 997 99 Snow 2011 10 Healthy 16.0 96 111.5 Both 1198 100 Speer 2007 24 Healthy 13.6 100 104.5 Both 1199 101 Spezio 2007 12 Healthy 23.0 100 107.0 Both 11

100 102 Stagg 2014 8 Healthy 9.6 - 106.0 Social 6101 103 Sterling 2008 30 Healthy 23.5 94 107.1 Social 11102 104 Tenenbaum 2014 14 Both 3.6 62 69.8 Both 9103 105 Trembath 2015 8 Both 4.0 88 65.2 Social 9104 106 Trepagnier 2002 4 Healthy 18.4 80 - Social 5105 107, 108 van der Geest 2002 46 Healthy 10.6 100 95.1 Both 11106 109 Van Herwegen 2015 4 Healthy 7.1 92 - Social 6107 110 Vivanti 2008 4 Healthy 11.3 89 107.0 Social 11108 111 Vivanti 2011 13 Healthy 13.0 89 112.0 Social 11109 112, 113 Vivanti 2014 8 DD 4.0 88 72.0 Social 9110 114 Wagner 2013 12 Healthy 17.0 100 111.2 Social 10111 115 Wang 2015 9 Healthy 31.0 85 107.5 Both 11112 116 Wass 2015 24 Healthy .7 47 90.0 Both 10113 117 White 2015 2 Healthy 14.9 53 - Social 8114 118 Wild 2012 2 Healthy 30.6 69 120.0 Both 8115 119 Wilson 2010 8 Healthy 10.1 69 92.0 Social 9116 120 Wilson 2012 5 Healthy 10.2 64 93.6 Both 11117 121 Yi 2012 12 Healthy 6.6 94 47.3 Both 8118 122 Yi 2013 10 Healthy 7.9 85 77.2 Social 9119 123 Yi 2014 10 Both 20.8 74 - Both 7120 124 Yi 2015 20 Both 20.7 71 - Social 8121 125 Zamzow 2014 3 Healthy 18.3 75 103.5 Social 10122 126 Zwickel 2011 9 Healthy 37.0 60 117.0 Both 6

Note: Several references were online published in PubMed in 2015, but the final reference reflects the print publication in 2016.aNot reported. bROI type = social regions-of-interest, nonsocial regions-of-interest, or both types of regions-of-interest. cControl type: Healthy=Healthy Controls, DD=Developmental Disability. dMethod quality could vary across effect sizes but never varied more than +/-1 point within a study.

Figure S1. Effects of age (A) and IQ level (B) on effect size magnitude.

Figure S2. Profile likelihood plots for meta-regression estimates of level 1 (between study) and level 2 (within study) variance, both indicating clear parameter estimation.

Figure S3. Residual plots before (A) and after (B) removing outliers.

Table S5. Multivariate Meta-Regression Estimates of the Effects of Stimulus and Region-of-Interest (ROI) Moderators Including Points of Calibration.

Simultaneous Moderator Model (k=796)b SE Z p 95% CI

Intercept -0.06 .20 -0.30 .763 -.45 to .33Method FactorsPublication Year (centered at 2011) -0.01 .01 -0.96 .339 -.03 to .01Design and Reporting Quality Index (centered at 8.63) -0.08 .02 -4.52 <.001 -.12 to -.05DD Controls (vs. Healthy) -0.11 .06 -1.80 .072 -.22 to -.01Points of Calibration 0.13 .04 2.93 .003 .04 to .22Stimulus FactorsAudio-Visual (vs. Visual only) 0.07 .09 0.80 .424 -.11 to .26Human 0.01 .09 0.17 .875 -.15 to .18Dynamic (vs. Static) 0.20 .22 0.90 .367 -.24 to .64Face -0.02 .07 -0.32 .750 -.16 to .11Interactive -0.23 .18 -1.30 .193 -.58 to .12Directive -0.02 .05 -0.45 .656 -.13 to .08Dynamic X Interactive -0.17 .33 -0.54 .593 -.81 to .46Dynamic X Human Present -0.11 .24 -0.46 .648 -.57 to .35Human X Interactive 0.46 .18 2.49 .013 .10 to .82Dynamic X Interactive X Human -0.04 .34 -0.10 .921 -.70 to .63Regions-of-InterestSocial (vs. Non-Social) -0.13 .06 -2.30 .021 -.24 to -.02Body Regions (vs. Other Face)

Eyes 0.13 .11 1.20 .231 -.08 to .34Whole Face 0.28 .11 2.51 .012 .06 to .49Upper Face -0.22 .18 -1.21 .228 -.58 to .14Lower Face 0.11 .18 0.61 .542 -.25 to .47Face Ratio (Upper/Lower) -0.33 .17 -1.91 .056 -.66 to .01Mouth -0.07 .11 -0.65 .513 -.30 to .15Nose -0.28 .14 -2.04 .041 -.55 to -.01Body -0.14 .12 -1.11 .267 -.38 to .11Non-Body 0.04 .10 0.35 .726 -.16 to .23

Note. Bold designates factors significant at p<.05. “Other Face” regions included areas of the face that were not coded as eyes, mouth, nose, or any of the other aggregate face regions (e.g., upper face, lower face, whole face, etc.). The “Other Face” region-of-interest was chosen as the comparison because preliminary analyses indicated that this region had an average effect size that fell at the middle of the distribution of effect sizes for the body regions. Face ratio refers to regions-of-interest where an upper face region was compared to a lower face region. Most frequently, this comparison involved an eyes-to- mouth comparison. DD=Developmental Disability controls.