Skip to main content
NCBI home page
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2019 Jan 24.
Published in final edited form as: Vision Res. 2011 Jun 16;51(15):1778–1780. doi: 10.1016/j.visres.2011.06.004

Psychophysical measures of visual acuity in autism spectrum conditions

Teresa Tavassoli a,*, Keziah Latham b, Michael Bach c, Steven C Dakin d, Simon Baron-Cohen a
PMCID: PMC6345362  EMSID: EMS81094  PMID: 21704058

Abstract

Previously reported superior visual acuity (VA) in autism spectrum conditions (ASC) may have resulted from methodological settings used (Ashwin, Ashwin, Rhydderch, Howells, & Baron-Cohen, 2009). The current study re-tested whether participants with (N = 20) and without (N = 20) ASC differ on psycho-physical measures of VA. Participants’ vision was corrected before acuity measurement, minimising refractive blur. VA was assessed with an ETDRS chart as well as the Freiburg Visual Acuity and Contrast Test (FrACT). FrACT testing was undertaken at 4 m (avoiding limitations of pixel-size), using 36 trials (avoiding fatigue). Best corrected VA was significantly better than the initial habitual acuity in both groups, but adults with and without ASC did not differ on ETDRS or FrACT binocular VA. Future research should examine at which level of visual processing sensory differences emerge.

Keywords: Autism, Visual acuity, Freiburg Visual Acuity and Contrast Test

1. Introduction

Autism spectrum conditions (ASC) are characterized by difficulties in social interaction and communication, alongside unusually narrow interests and highly repetitive behaviour (A.P.A., 1994). In addition, anecdotal reports (Chamak, Bonniau, Jaunay, & Cohen, 2008; Grandin, 1996) and questionnaire studies indicate consistent perceptual differences in ASC (Kern, Grannemann, & Carmody, 2007; Kern et al., 2006; Kern, Trivedi, et al., 2007; Kientz & Dunn, 1997; Leekam, Nieto, Libby, Wing, & Gould, 2007; Tomchek & Dunn, 2007).

There is however mixed evidence as to whether adults with ASC show superior performance on “low-level” visual tasks (Bertone, Mottron, Jelenic, & Faubert 2005; Koldewyn, Whitney, & Rivera, 2006; Simmons et al., 2009; Spencer et al., 2000).

Inconsistent findings have been published regarding visual acuity (VA) in ASC. Milne, Griffiths, Buckley, and Scope (2009) used the Crowded LogMAR test and reported that children and adolescents with ASC show poorer VA compared to typically developing control participants (Milne et al., 2009). Keita, Mottron, and Bertone (2010) have reported similar distance VA in adults with ASC and without measured with Landolt-C optotypes (Keita et al., 2010). Bölte et al. (2011), while not exploring the high acuity domain, also report no difference in VA between adolescents and young adults with and without ASC. In contrast, Ashwin, Ashwin, Rhydderch, Howells, and Baron-Cohen (2009) showed markedly superior VA in adults with ASC using the Freiburg Visual Acuity and Contrast Test (FrACT) (Ashwin et al., 2009). However such “eagle-eyed visual acuity” has proved contentious and two methodological issues were raised (Bach & Dakin, 2009; Crewther & Sutherland, 2009) which inspired us to conduct the current study. First, the Ashwin et al. (2009) study used a viewing distance of 60 cm, a procedure that – given the pixel resolution of the visual display – likely elicited too few errors to allow the FrACT to precisely estimate VA. The present study addresses this issue by testing at a viewing distance of 4 m (where pixel size will not limit acuity measurement). Second, the Ashwin et al. (2009) study used 150 trials, which commentators argued may have caused group-differential fatigue and led to stimulus-unrelated “keypress” errors, which could disproportionately inflate threshold estimates given the low (near-zero) error-rates that result under short viewing distances. Superior VA in ASC could then simply reflect attentional rather than sensory group differences. To test this we again employed the FrACT, but used a reduced number of 36 trials. Finally, uncorrected refractive error may have contributed to the erroneous findings. In the present study participants were refracted prior to assessment to minimise refractive blur.

2. Materials and methods

2.1. Participants

Twenty adults with ASC (11 male, 9 female) and 22 adult controls (14 male, 8 female) with no history of psychiatric conditions took part. All ASC participants had been previously diagnosed by a qualified clinician using DSM-IV criteria (A.P.A., 1980, 1994). To screen control participants for autistic traits we used the Autism Spectrum Quotient (AQ) questionnaire (Woodbury-Smith, Robinson, & Baron-Cohen, 2005), a short questionnaire measuring autistic traits, with five subscales (social skills, attention switching, attention to detail, imagination and communication) (Baron-Cohen, Hoekstra, Knickmeyer, & Wheelwright, 2006; Baron-Cohen, Wheel-wright, Skinner, Martin, & Clubley, 2001). A cut-off AQ score of below 26 was used for the control group (Woodbury-Smith et al., 2005). Two participants in the control group scored above 26 and were therefore excluded from further analysis. In the end 20 adult participants with ASC (11 male, 9 female) were compared to 20 controls (13 male, 7 female). All participants completed the Wechsler Abbreviated Scale of Intelligence (WASI) (see Table 1).

Table 1. Descriptive characteristics of the groups.

Participant characteristics ASC group Control group
N 20 20
Sex ratio (f:m) 9:11 13:7
Mean age in years (SD) 30.4 (10.0) 30.7 (10.1)
WASI-IQ (SD) 109.2 (18.1) 112.5 (10.6)
AQ (SD) (range from 0 to 50) 36.8 (9.1) 17.2 (4.5)
Open in a new tab

Abbreviations: AQ = Autism Spectrum Quotient, ASC = Autism Spectrum Condition, f = female, m = male, N = number of participants, WASI = Wechsler Abbreviated Scale of Intelligence, IQ = Intelligence Quotient, SD = standard deviation.

2.2. Visual acuity

Visual acuity (VA) was assessed by a qualified optometrist (KL). Habitual binocular VA was initially assessed with the participant wearing their usual spectacles or contact lenses (if any) for distance vision. VA was assessed using the standard ETDRS eye-chart (Ferris & Sperduto, 1982), at a 3 m distance with VA scored on a letter by letter basis (Hazel & Elliott, 2002). Each participant was refracted and best-corrected visual acuity (BCVA) was then assessed with an alternative ETDRS chart.

VA was then measured using the FrACT (version 3.4.3, <http://michaelbach.de/fract/>) (Bach, 1996) with participants wearing the best correction as determined by refraction. A Dell Precision 690-Intel Xeon 5050 computer with an Nvidia Quadro FX3500 graphic card was used for stimulus presentation. The observer distance was set at 4 m. Threshold was determined by the “Best Probability Estimation of Sensory Threshold” (PEST) staircase routine, with threshold set to DIN/ISO corrected (67% correct) for comparison to other acuity measures. The number of trials was set to 36, with an “easy trial” every 6th item. Thirty trials correspond to the default number of trials of the FrACT. The time-out duration was set to 10 s. Auditory feedback was not used.

The Cambridge University Psychology Research Ethics Committee approved the study and all participants gave written informed consent before taking part in the study.

3. Results

3.1. Descriptive statistics

SPSS 16 was used to analyse the data. As expected, the AQ scores differed significantly between the two groups (t(37) = 8.54, p < .01). Sex ratios (Pearson Chi-Square (1) = .41, p = .51), age (p = .60) and IQ (p = .51) were not significantly different between groups. Lastly, tests of normality (Kolmogorov–Smirnov test; KS) showed that VA values were normally distributed and thus parametric tests were used (p = .20).

3.2. Visual acuity

Repeated measure multivariate tests showed that best corrected visual acuity (−0.17 ± .09 logMAR, 20/13 Snellen) was statistically significantly better than the initial habitual acuity (−0.13 ± .1 logMAR, 20/15 Snellen) (F (1, 37) = 23.33, p < .01). The difference between habitual and corrected vision did not differ between groups (F (1, 37) = 0.78, p = .38). Clinical examination revealed that one control participant had strabismic amblyopia and two control and two ASC participants had anisometropic amblyopia (amblyopia defined as >2 lines difference in best-corrected VA between eyes and a VA in the poorer eye of worse than +0.20 logMAR). All other subjects were binocularly normal and refraction was achieved in all cases.

Multivariate tests showed that best corrected ETDRS and FrACT visual acuities did not differ between the groups (F (2, 37) = .50, p = .60). There was no significant difference between ASC (−0.15 ± .07 logMAR, 20/14 Snellen) and control (−0.18 ± .1 logMAR, 20/13 Snellen) groups’ best corrected binocular ETDRS acuity (F (1) = .46, p = .49). The mean FrACT binocular acuity also did not differ between the ASC group (−0.27 ± .08 logMAR, 20/11 Snellen) and the control group (−0.28 ± .14 logMAR, 20/10 Snellen) (F (1) = .85, p = .36) = 0.27, p = .79) (see Fig. 1).

Fig. 1.

Fig. 1

Open in a new tab

The bars represent the experimentally measured visual acuity using the Freiburg Visual Acuity and Contrast Test (FrACT). Visual acuity is expressed in logMAR. The antennas are the standard error of the mean (SEM, calculated from logarithmised VA). There was no significant differences between the two groups (p > .05).

4. Discussion

We set out to resolve a debate over superior visual acuity (VA) in ASC by investigating psychophysical measures of VA in adults with and without autism spectrum conditions (ASC). Adults with and without ASC did not differ significantly in visual acuity in terms of either ETDRS or FrACT measures.

In the Ashwin et al. study (2009) the viewing distance of 60 cm was incompatible with the monitor resolution and could not allow for the accurate measurement of visual acuities due to pixel resolution limits. In the current study we used an ISO-norm compliant viewing distance of 4 m. Both groups in the present study had excellent VA, corresponding to 6/3 or 20/10 in Snellen notation. While these values appear high, they are typical if acuity is tested according to good psychophysical practice (Arditi & Cagenello, 1993), which is also prescribed by the international acuity norm EN ISO 8596.

Second, in the present experiment a qualified optometrist corrected each participant’s vision before acuity measurement. The improvement in VA by refraction, whilst statistically significant, was small and not clinically relevant as test–retest reliability with ETDRS charts is ± 0.14 logMAR (Hazel & Elliott, 2002). Refraction, while a possible confound, is unlikely to have been a major factor in explaining Ashwin et al.’s findings (Ashwin et al., 2009).

Lastly, as the present study reduced the number of trials from 150 to 36 (including the six motivation trials), it is possible that the previous study finding superior VA in ASC is related to the ASC group making fewer errors under more fatiguing test conditions. Future research could examine the role of attention.

We conclude that there is no experimental evidence for superior visual acuity in ASC. However perceptual differences in ASC are a robust phenomenon as reported anecdotally and measured by questionnaires. Thus future research should examine at which level sensory differences in ASC emerge.

Acknowledgments

We are grateful to the participants for their generous cooperation and to Bonnie Auyeung, Bhismadev Chakrabarti, Michael Lombardo, Caroline Robertson, Emma Ashwin and Chris Ashwin for valuable discussions.

Footnotes

5

Financial disclosures

T.T. was supported by the Pinsent Darwin Trust and Autistica during the period of this work. S.B.C. was supported by the MRC UK. S.C.D. was supported by the Wellcome Trust. This work was conducted in association with the NIHR CLAHRC for Cambridgeshire and Peterborough NHS Foundation Trust. The authors of this paper report no biomedical financial interests or potential conflicts of interest.

References

  1. A.P.A. DSM-III diagnostic and statistical manual of mental disorders. 3rd ed. Washington, DC: American Psychiatric Association; 1980. [Google Scholar]
  2. A.P.A. DSM-IV diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994. [Google Scholar]
  3. Arditi A, Cagenello R. On the statistical reliability of letter-chart visual acuity measurements. Investigative Ophthalmology and Visual Science. 1993;34(1):120–129. [PubMed] [Google Scholar]
  4. Ashwin E, Ashwin C, Rhydderch D, Howells J, Baron-Cohen S. Eagleeyed visual acuity: An experimental investigation of enhanced perception in autism. Biological Psychiatry. 2009;65(1):17–21. doi: 10.1016/j.biopsych.2008.06.012. [DOI] [PubMed] [Google Scholar]
  5. Bach M. The Freiburg Visual Acuity Test – automatic measurement of visual acuity. Optometry and Vision Science. 1996;73(1):49–53. doi: 10.1097/00006324-199601000-00008. [DOI] [PubMed] [Google Scholar]
  6. Bach M, Dakin SC. Regarding “Eagle-eyed visual acuity: An experimental investigation of enhanced perception in autism”. Biological Psychiatry. 2009;66(10):e19–20. doi: 10.1016/j.biopsych.2009.02.035. author reply e23–14. [DOI] [PubMed] [Google Scholar]
  7. Baron-Cohen S, Hoekstra RA, Knickmeyer R, Wheelwright S. The Autism-Spectrum Quotient (AQ) – Adolescent version. Journal of Autism & Developmental Disorders. 2006;36:343–350. doi: 10.1007/s10803-006-0073-6. [DOI] [PubMed] [Google Scholar]
  8. Baron-Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E. The Autism Spectrum Quotient (AQ): Evidence from Asperger syndrome/high functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders. 2001;31:5–17. doi: 10.1023/a:1005653411471. [DOI] [PubMed] [Google Scholar]
  9. Bertone A, Mottron L, Jelenic P, Faubert J. Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity. Brain. 2005;128:2430–2441. doi: 10.1093/brain/awh561. [DOI] [PubMed] [Google Scholar]
  10. Bölte S, Schlitt S, Gapp V, Hainz D, Schirman S, Poustka F, et al. A close eye on the eagle-eyed visual acuity hypothesis of autism. Journal of Autism and Developmental Disorders. 2011 doi: 10.1007/s10803-011-1300-3. [Epub ahead of print] [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chamak B, Bonniau B, Jaunay E, Cohen D. What can we learn about autism from autistic persons? Psychotherapy and Psychosomatics. 2008;77(5):271–279. doi: 10.1159/000140086. [DOI] [PubMed] [Google Scholar]
  12. Crewther DP, Sutherland A. The more he looked inside, the more piglet wasn’t there: Is autism really blessed with visual hyperacuity? Biological Psychiatry. 2009;66(10):e21–22. doi: 10.1016/j.biopsych.2009.02.036. author reply e23–24. [DOI] [PubMed] [Google Scholar]
  13. Ferris FL, 3rd, Sperduto RD. Standardized illumination for visual acuity testing in clinical research. American Journal of Ophthalmology. 1982;94(1):97–98. doi: 10.1016/0002-9394(82)90198-2. [DOI] [PubMed] [Google Scholar]
  14. Grandin T. Thinking in pictures. Vancouver, WA USA: Vintage Books; 1996. [Google Scholar]
  15. Hazel CA, Elliott DB. The dependency of logMAR visual acuity measurements on chart design and scoring rule. Optometry and Vision Science. 2002;79(12):788–792. doi: 10.1097/00006324-200212000-00011. [DOI] [PubMed] [Google Scholar]
  16. Keita L, Mottron L, Bertone A. Far visual acuity is unremarkable in autism: Do we need to focus on crowding? Autism Research. 2010;3(6):333–341. doi: 10.1002/aur.164. [DOI] [PubMed] [Google Scholar]
  17. Kern G, Grannemann, Trivedi, Carmody, Andrews Examining Sensory Quadrants in Autism Research in Autism Spectrum Disorders. 2007:185–193. [Google Scholar]
  18. Kern JK, Trivedi MH, Garver CR, Grannemann BD, Andrews AA, Savla JS, et al. The pattern of sensory processing abnormalities in autism. Autism. 2006;10(5):480–494. doi: 10.1177/1362361306066564. [DOI] [PubMed] [Google Scholar]
  19. Kern JK, Trivedi MH, Grannemann BD, Garver CR, Johnson DG, Andrews AA, et al. Sensory correlations in autism. Autism. 2007;11(2):123–134. doi: 10.1177/1362361307075702. [DOI] [PubMed] [Google Scholar]
  20. Kientz MA, Dunn W. A comparison of the performance of children with and without autism on the sensory profile. American Journal of Occupational Therapy. 1997;51(7):530–537. doi: 10.5014/ajot.51.7.530. [DOI] [PubMed] [Google Scholar]
  21. Koldewyn K, Whitney D, Rivera SM. The psychophysics of visual motion and global form processing in autism. Brain. 2006;133(Pt 2):599–610. doi: 10.1093/brain/awp272. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Leekam SR, Nieto C, Libby SJ, Wing L, Gould J. Describing the sensory abnormalities of children and adults with autism. Journal of Autism and Developmental Disorders. 2007;37(5):894–910. doi: 10.1007/s10803-006-0218-7. [DOI] [PubMed] [Google Scholar]
  23. Milne E, Griffiths H, Buckley D, Scope A. Vision in children and adolescents with autistic spectrum disorder: Evidence for reduced convergence. Journal of Autism and Developmental Disorders. 2009;39(7):965–975. doi: 10.1007/s10803-009-0705-8. [DOI] [PubMed] [Google Scholar]
  24. Simmons DR, Robertson AE, McKay LS, Toal E, McAleer P, Pollick FE. Vision in autism spectrum disorders. Vision Research. 2009;49(22):2705–2739. doi: 10.1016/j.visres.2009.08.005. [DOI] [PubMed] [Google Scholar]
  25. Spencer J, O’Brien J, Riggs K, Braddick O, Atkinson J, Wattam-Bell J. Motion processing in autism: Evidence for a dorsal stream deficiency. Cognitive Neuroscience & Neuropsychology. 2000;11:2765–2767. doi: 10.1097/00001756-200008210-00031. [DOI] [PubMed] [Google Scholar]
  26. Tomchek SD, Dunn W. Sensory processing in children with and without autism: A comparative study using the short sensory profile. American Journal of Occupational Therapy. 2007;61(2):190–200. doi: 10.5014/ajot.61.2.190. [DOI] [PubMed] [Google Scholar]
  27. Woodbury-Smith M, Robinson J, Baron-Cohen S. Screening adults for Asperger Syndrome using the AQ: Diagnostic validity in clinical practice. Journal of Autism and Developmental Disorders. 2005;35:331–335. doi: 10.1007/s10803-005-3300-7. [DOI] [PubMed] [Google Scholar]

RESOURCES