Documenta Ophthalmologica

, Volume 132, Issue 2, pp 83–99 | Cite as

Full-field electroretinogram in autism spectrum disorder

  • Paul A. Constable
  • Sebastian B. Gaigg
  • Dermot M. Bowler
  • Herbert Jägle
  • Dorothy A. Thompson
Original Research Article

Abstract

Purpose

To explore early findings that individuals with autism spectrum disorder (ASD) have reduced scotopic ERG b-wave amplitudes.

Methods

Light-adapted (LA) and dark-adapted (DA) ERGs were produced by a range of flash strengths that included and extended the ISCEV standard from two subject groups: a high-functioning ASD group N = 11 and a Control group N = 15 for DA and N = 14 for LA ERGs who were matched for mean age and range. Flash strengths ranged from DA −4.0 to 2.3 log phot cd s m−2 and LA −0.5 to 1.0 log phot cd s m−2, and Naka-Rushton curves were fitted to DA b-wave amplitude over the first growth limb (−4.0 to −1.0 log phot cd s m−2). The derived parameters (Vmax, Km and n) were compared between groups. Scotopic 15-Hz flicker ERGs (14.93 Hz) were recorded to 10 flash strengths presented in ascending order from −3.0 to 0.5 log Td s to assess the slow and fast rod pathways, respectively. LA 30-Hz flicker ERGs, oscillatory potentials (OPs) and the responses to prolonged 120-ms ON–OFF stimuli were also recorded.

Results

The ISCEV LA b-wave amplitude produced by 0.5 log phot cd s m−2 was lower in the ASD group (p < 0.001). Repeated measures ANOVA for the LA b-wave amplitude series forming the photopic hill was significantly (p = 0.01) different between groups. No group differences were observed for the distributions of the time to peaks of LA a-wave, b-wave or the photopic negative responses (phNR) (p > 0.08) to the single flash stimuli, but there was a significant difference in the distribution for the LA b-wave amplitudes (corrected p = 0.006). The prolonged 120-ms ON responses were smaller in the ASD group (corrected p = 0.003), but the OFF response amplitude (p > 0.6) and ON and OFF times to peaks (p > 0.4) were similar between groups. The LA OPs showed an earlier bifurcation of OP2 in the younger ASD participants; however, no other differences were apparent in the OPs or 30-Hz flicker waveforms. DA b-wave amplitudes fell below the control 5th centile of the controls for some individuals including four ASD participants (36 %) at the 1.5 log phot cd s m−2 flash strength and two (18 %) ASD participants at the lower −2 log phot cd s m−2 flash strength. However, across the 13 flash strengths, there were no significant group differences for b-wave amplitude’s growth (repeated measures ANOVA p = 0.83). Nor were there any significant differences between the groups for the Naka-Rushton parameters (p > 0.09). No group differences were observed in the 15-Hz scotopic flicker phase or amplitude (p > 0.1), DA ERG a-wave amplitude or time to peak (p > 26). The DA b-wave time to peak at 0.5 log phot cd s m−2 was longer in the ASD group (p = 0.04).

Conclusion

Under LA conditions, the b-wave is reduced across the ASD group, along with the ON response of the prolonged flash ERG. Some ASD individuals also show subnormal DA ERG b-wave amplitudes. These exploratory findings suggest there is altered cone-ON bipolar signalling in ASD.

Keywords

Autism spectrum disorder Electroretinogram Naka-Rushton ON pathway 15-Hz scotopic flicker 

Notes

Acknowledgments

This study was funded by the College of Optometrists, and parts of this work were presented at the 52nd ISCEV conference in Boston. The study was nominated for the Marmor prize for clinical innovation in electrophysiology at the meeting. The authors thank the anonymous reviewers for their helpful comments on this paper.

Compliance with ethical standards

Conflict of interest

All authors certify that they have no affiliations with or involvement in any organisation or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

References

  1. 1.
    Baird G, Simonoff E, Pickles A, Chandler S, Loucas T, Meldrum D et al (2006) Prevalence of disorders of the autism spectrum in a population cohort of children in South Thames: the Special Needs and Autism Project (SNAP). Lancet 368(9531):210–215. doi:10.1016/s0140-6736(06)69041-7 CrossRefPubMedGoogle Scholar
  2. 2.
    Nicholas JS, Charles JM, Carpenter LA, King LB, Jenner W, Spratt EG (2008) Prevalence and characteristics of children with autism-spectrum disorders. Ann Epidemiol 18(2):130–136CrossRefPubMedGoogle Scholar
  3. 3.
    Rattazzi A (2014) The importance of early detection and early intervention for children with autism spectrum conditions. Vertex (Buenos Aires, Argentina) 25(116):290–294Google Scholar
  4. 4.
    Lin LY (2014) Quality of life of Taiwanese adults with autism spectrum disorder. PLoS One 9(10):e109567. doi:10.1371/journal.pone.0109567 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Dillenburger K, Jordan JA, McKerr L, Keenan M (2015) The Millennium child with autism: early childhood trajectories for health, education and economic wellbeing. Dev Neurorehabil 18(1):37–46. doi:10.3109/17518423.2014.964378 CrossRefPubMedGoogle Scholar
  6. 6.
    Ecker C, Marquand A, Mourao-Miranda J, Johnston P, Daly EM, Brammer MJ et al (2010) Describing the brain in autism in five dimensions—magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J Neurosci 30(32):10612–10623. doi:10.1523/jneurosci.5413-09.2010 CrossRefPubMedGoogle Scholar
  7. 7.
    Schumann CM, Bloss CS, Barnes CC, Wideman GM, Carper RA, Akshoomoff N et al (2010) longitudinal magnetic resonance imaging study of cortical development through early childhood in autism. J Neurosci 30(12):4419–4427. doi:10.1523/jneurosci.5714-09.2010 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Wang K, Zhang H, Ma D, Bucan M, Glessner JT, Abrahams BS et al (2009) Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature 459(7246):528–533. doi:10.1038/nature07999 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    St. Pourcain B, Wang K, Glessner JT, Golding J, Steer C, Ring SM et al (2010) Association between a high-risk autism locus on 5p14 and social communication spectrum phenotypes in the general population. Am J Psychiatry 167(11):1364–1372. doi:10.1176/appi.ajp.2010.09121789 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S et al (2009) Autism genome-wide copy number variation reveals ubiquitin and neuronal genes. Nature 459(7246):569–573CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Autism Genome Project Consortium (2007) Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nat Genet 39(3):319–328. doi:10.1038/ng1985 CrossRefGoogle Scholar
  12. 12.
    Hadley D, Wu ZL, Kao C, Kini A, Mohamed-Hadley A, Thomas K et al (2014) The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism. Nat Commun 5:4074. doi:10.1038/ncomms5074 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Gerber U (2003) Metabotropic glutamate receptors in vertebrate retina. Doc Ophthalmol 106(1):83–87CrossRefPubMedGoogle Scholar
  14. 14.
    Ulrike G (2000) Distribution of GABA and glycine receptors on bipolar and ganglion cells in the mammalian retina. Microsc Res Tech 50(2):130–140CrossRefGoogle Scholar
  15. 15.
    Lavoie J, Maziade M, Hébert M (2014) The brain through the retina: the flash electroretinogram as a tool to investigate psychiatric disorders. Prog Neuropsychopharmacol Biol Psychiatry 48:129–134. doi:10.1016/j.pnpbp.2013.09.020 CrossRefPubMedGoogle Scholar
  16. 16.
    Collins A, Ma D, Whitehead P, Martin E, Wright H, Abramson R et al (2006) Investigation of autism and GABA receptor subunit genes in multiple ethnic groups. Neurogenetics 7(3):167–174CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Jamain S, Betancur C, Quach H, Philippe A, Fellous M, Giros B et al (2002) Linkage and association of the glutamate receptor 6 gene with autism. Mol Psychiatry 7(3):302–310CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    de Mariken K, Wouter GS, Roel AO, Judith H, Jan B, Barbara F et al (2009) A common variant in DRD3 receptor is associated with autism spectrum disorder. Biol Psychiatry 65(7):625–630CrossRefGoogle Scholar
  19. 19.
    Nguyen CT, Vingrys AJ, Wong VH, Bui BV (2013) Identifying cell class specific losses from serially generated electroretinogram components. BioMed Res Int 2013:796362. doi:10.1155/2013/796362 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Dhingra A, Vardi N (2012) “mGlu Receptors in the Retina”—WIREs Membrane Transport and Signaling. Wiley Interdiscip Rev Membr Transp Signal 1(5):641–653. doi:10.1002/wmts.43 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Gregory KJ, Dong EN, Meiler J, Conn PJ (2011) Allosteric modulation of metabotropic glutamate receptors: structural insights and therapeutic potential. Neuropharmacology 60(1):66–81. doi:10.1016/j.neuropharm.2010.07.007 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Hébert M, Merette C, Paccalet T, Emond C, Gagne AM, Sasseville A et al (2015) Light evoked potentials measured by electroretinogram may tap into the neurodevelopmental roots of schizophrenia. Schizophr Res 162(1–3):294–295. doi:10.1016/j.schres.2014.12.030 CrossRefPubMedGoogle Scholar
  23. 23.
    Hébert M, Gagne AM, Paradis ME, Jomphe V, Roy MA, Merette C et al (2010) Retinal response to light in young nonaffected offspring at high genetic risk of neuropsychiatric brain disorders. Biol Psychiatry 67(3):270–274. doi:10.1016/j.biopsych.2009.08.016 CrossRefPubMedGoogle Scholar
  24. 24.
    Warner R, Laugharne J, Peet M, Brown L, Rogers N (1999) Retinal function as a marker for cell membrane omega-3 fatty acid depletion in schizophrenia: a pilot study. Biol Psychiatry 45(9):1138–1142CrossRefPubMedGoogle Scholar
  25. 25.
    Balogh Z, Benedek G, Kéri S (2008) Retinal dysfunctions in schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 32(1):297–300. doi:10.1016/j.pnpbp.2007.08.024 CrossRefPubMedGoogle Scholar
  26. 26.
    Pathania M, Davenport EC, Muir J, Sheehan DF, Lopez-Domenech G, Kittler JT (2014) The autism and schizophrenia associated gene CYFIP1 is critical for the maintenance of dendritic complexity and the stabilization of mature spines. Transl Psychiatry 4:e423. doi:10.1038/tp.2014.36 CrossRefPubMedCentralGoogle Scholar
  27. 27.
    Singh SM, Castellani C, O’Reilly R (2010) Autism meets schizophrenia via cadherin pathway. Schizophr Res 116(2–3):293–294. doi:10.1016/j.schres.2009.09.031 CrossRefPubMedGoogle Scholar
  28. 28.
    Matsuo J, Kamio Y, Takahashi H, Ota M, Teraishi T, Hori H et al (2015) Autistic-like traits in adult patients with mood disorders and schizophrenia. PLoS One 10(4):e0122711. doi:10.1371/journal.pone.0122711 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Realmuto G, Purple R, Knobloch W, Ritvo ER (1989) Electroretinograms (ERGs) in four autistic probands and six first-degree relatives. Can J Psychiatry 34(5):435–439PubMedGoogle Scholar
  30. 30.
    Ritvo ER, Creel D, Realmuto G, Crandall AS, Freeman BJ, Bateman JB et al (1988) Electroretinograms in autism: a pilot study of b-wave amplitudes. Am J Psychiatry 145(2):229–232CrossRefPubMedGoogle Scholar
  31. 31.
    Shah A, Frith U (1983) An islet of ability in autistic children: a research note. J Child Psychol Psychiatry 24(4):613–620. doi:10.1111/j.1469-7610.1983.tb00137.x CrossRefPubMedGoogle Scholar
  32. 32.
    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(5):777–783CrossRefPubMedGoogle Scholar
  33. 33.
    Baldassi S, Pei F, Megna N, Recupero G, Viespoli M, Igliozzi R et al (2009) Search superiority in autism within, but not outside the crowding regime. Vis Res 49(16):2151–2156. doi:10.1016/j.visres.2009.06.007 CrossRefPubMedGoogle Scholar
  34. 34.
    Bertone A, Mottron L, Jelenic P, Faubert J (2005) Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity. Brain 128(10):2430–2441. doi:10.1093/brain/awh561 CrossRefPubMedGoogle Scholar
  35. 35.
    Constable PA, Gaigg SB, Bowler DM, Thompson DA (2012) Motion and pattern cortical potentials in adults with high-functioning autism spectrum disorder. Doc Ophthalmol 125(3):219–227. doi:10.1007/s10633-012-9349-7 CrossRefPubMedGoogle Scholar
  36. 36.
    Koldewyn K, Whitney D, Rivera SM (2010) The psychophysics of visual motion and global form processing in autism. Brain 133(2):599–610. doi:10.1093/brain/awp272 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Dakin S, Frith U (2005) Vagaries of visual perception in autism. Neuron 48(3):497–507. doi:10.1016/j.neuron.2005.10.018 CrossRefPubMedGoogle Scholar
  38. 38.
    Simmons DR, Robertson AE, McKay LS, Toal E, McAleer P, Pollick FE (2009) Vision in autism spectrum disorders. Vis Res 49(22):2705–2739. doi:10.1016/j.visres.2009.08.005 CrossRefPubMedGoogle Scholar
  39. 39.
    Bonnel A, Mottron L, Peretz I, Trudel M, Gallun E, Bonnel A-M (2003) Enhanced pitch sensitivity in individuals with autism: a signal detection analysis. J Cogn Neurosci 15(2):226–235. doi:10.1162/089892903321208169 CrossRefPubMedGoogle Scholar
  40. 40.
    Bonnel A, McAdams S, Smith B, Berthiaume C, Bertone A, Ciocca V et al (2010) Enhanced pure-tone pitch discrimination among persons with autism but not Asperger syndrome. Neuropsychologia 48(9):2465–2475. doi:10.1016/j.neuropsychologia.2010.04.020 CrossRefPubMedGoogle Scholar
  41. 41.
    Tonacci A, Billeci L, Tartarisco G, Ruta L, Muratori F, Pioggia G et al (2015) Olfaction in autism spectrum disorders: a systematic review. Child Neuropsychol. doi:10.1080/09297049.2015.1081678 PubMedGoogle Scholar
  42. 42.
    Daluwatte C, Miles JH, Sun J, Yao G (2014) Association between pupillary light reflex and sensory behaviors in children with autism spectrum disorders. Res Dev Disabil 37C:209–215Google Scholar
  43. 43.
    Milne E, Scope A, Griffiths H, Codina C, Buckley D (2013) Brief report: preliminary evidence of reduced sensitivity in the peripheral visual field of adolescents with autistic spectrum disorder. J Autism Dev Disord 43(8):1976–1982. doi:10.1007/s10803-012-1730-6 CrossRefPubMedGoogle Scholar
  44. 44.
    Lane AE, Molloy CA, Bishop SL (2014) Classification of children with autism spectrum disorder by sensory subtype: a case for sensory-based phenotypes. Autism Res 7(3):322–333. doi:10.1002/aur.1368 CrossRefPubMedGoogle Scholar
  45. 45.
    Stockman A, Sharpe LT, Ruther K, Nordby K (1995) Two signals in the human rod visual system: a model based on electrophysiological data. Vis Neurosci 12(5):951–970CrossRefPubMedGoogle Scholar
  46. 46.
    Stockman A, Sharpe LT, Zrenner E, Nordby K (1991) Slow and fast pathways in the human rod visual system: electrophysiology and psychophysics. J Opt Soc Am 8(10):1657–1665CrossRefGoogle Scholar
  47. 47.
    Sharpe LT, Fach CC, Stockman A (1993) The spectral properties of the two rod pathways. Vis Res 33(18):2705–2720CrossRefPubMedGoogle Scholar
  48. 48.
    Lord C, Rutter M, Goode S, Heemsbergen J, Jordan H, Mawhood L et al (1989) Autism diagnostic observation schedule: a standardized observation of communicative and social behavior. J Autism Dev Disord 19(2):185–212CrossRefPubMedGoogle Scholar
  49. 49.
    American Psychiatric Association (2000) Diagnostic and statistical manual of mental disorders (DSM-IV-TR). American Psychiatric Association, WashingtonGoogle Scholar
  50. 50.
    The Psychological Corporation (2000) Wechsler Adult Intelligence Scale. The Psychological Corporation, LondonGoogle Scholar
  51. 51.
    Baron-Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E (2001) The Autism-Spectrum Quotient (AQ): evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. J Autism Dev Disord 31(1):5–17CrossRefPubMedGoogle Scholar
  52. 52.
    Neveu MM, Dangour A, Allen E, Robson AG, Bird AC, Uauy R et al (2011) Electroretinogram measures in a septuagenarian population. Doc Ophthalmol 123(2):75–81. doi:10.1007/s10633-011-9282-1 CrossRefPubMedGoogle Scholar
  53. 53.
    McCulloch DL, Marmor MF, Brigell MG, Hamilton R, Holder GE, Tzekov R et al (2015) ISCEV Standard for full-field clinical electroretinography (2015 update). Doc Ophthalmol 130(1):1–12. doi:10.1007/s10633-014-9473-7 CrossRefPubMedGoogle Scholar
  54. 54.
    Scholl HP, Langrová H, Weber BH, Zrenner E, Apfelstedt-Sylla E (2001) Clinical electrophysiology of two rod pathways: normative values and clinical application. Graefes Arch Clin Exp Ophthalmol 239(2):71–80CrossRefPubMedGoogle Scholar
  55. 55.
    Meigen T, Bach M (1999) On the statistical significance of electrophysiological steady-state responses. Doc Ophthalmol 98(3):207–232CrossRefPubMedGoogle Scholar
  56. 56.
    Holopigian K, Bach M (2010) A primer on common statistical errors in clinical ophthalmology. Doc Ophthalmol 121(3):215–222. doi:10.1007/s10633-010-9249-7 CrossRefPubMedGoogle Scholar
  57. 57.
    Evans LS, Peachey NS, Marchese AL (1993) Comparison of three methods of estimating the parameters of the Naka-Rushton equation. Doc Ophthalmol 84(1):19–30CrossRefPubMedGoogle Scholar
  58. 58.
    Kim YS, Leventhal BL (2015) Genetic epidemiology and insights into interactive genetic and environmental effects in autism spectrum disorders. Biol Psychiatry 77(1):66–74CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Vardi T, Fina M, Zhang L, Dhingra A, Vardi N (2011) mGluR6 transcripts in non-neuronal tissues. J Histochem Cytochem 59(12):1076–1086. doi:10.1369/0022155411425386 CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Zielinski BA, Prigge MB, Nielsen JA, Froehlich AL, Abildskov TJ, Anderson JS et al (2014) Longitudinal changes in cortical thickness in autism and typical development. Brain 137(Pt 6):1799–1812. doi:10.1093/brain/awu083 CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Lange N, Travers BG, Bigler ED, Prigge MB, Froehlich AL, Nielsen JA et al (2014) Longitudinal volumetric brain changes in autism spectrum disorder ages 6–-35 years. Autism Res 8(1):82–93. doi:10.1002/aur.1427 CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Enoch MA, Rosser AA, Zhou Z, Mash DC, Yuan Q, Goldman D (2014) Expression of glutamatergic genes in healthy humans across 16 brain regions; altered expression in the hippocampus after chronic exposure to alcohol or cocaine. Genes Brain Behav 13(8):758–768. doi:10.1111/gbb.12179 CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Hanna MC, Calkins DJ (2007) Expression of genes encoding glutamate receptors and transporters in rod and cone bipolar cells of the primate retina determined by single-cell polymerase chain reaction. Mol Vis 13:2194–2208PubMedGoogle Scholar
  64. 64.
    Egan MF, Straub RE, Goldberg TE, Yakub I, Callicott JH, Hariri AR et al (2004) Variation in GRM3 affects cognition, prefrontal glutamate, and risk for schizophrenia. PNAS 101(34):12604–12609. doi:10.1073/pnas.0405077101 CrossRefPubMedPubMedCentralGoogle Scholar
  65. 65.
    Kawakubo Y, Suga M, Tochigi M, Yumoto M, Itoh K, Sasaki T et al (2011) Effects of metabotropic glutamate receptor 3 genotype on phonetic mismatch negativity. PLoS One 6(10):e24929. doi:10.1371/journal.pone.0024929 CrossRefPubMedPubMedCentralGoogle Scholar
  66. 66.
    Green DG, Kapousta-Bruneau NV (1999) A dissection of the electroretinogram from the isolated rat retina with microelectrodes and drugs. Vis Neurosci 16(4):727–741CrossRefPubMedGoogle Scholar
  67. 67.
    Friedburg C, Allen CP, Mason PJ, Lamb TD (2004) Contribution of cone photoreceptors and post-receptoral mechanisms to the human photopic electroretinogram. J Physiol 556(Pt 3):819–834. doi:10.1113/jphysiol.2004.061523 CrossRefPubMedPubMedCentralGoogle Scholar
  68. 68.
    Yang X-L (2004) Characterization of receptors for glutamate and GABA in retinal neurons. Prog Neurobiol 73(2):127–150CrossRefPubMedGoogle Scholar
  69. 69.
    Viswanathan S, Frishman LJ, Robson JG, Harwerth RS, Smith EL 3rd (1999) The photopic negative response of the macaque electroretinogram: reduction by experimental glaucoma. Invest Ophthalmol Vis Sci 40(6):1124–1136PubMedGoogle Scholar
  70. 70.
    Li B, Barnes GE, Holt WF (2005) The decline of the photopic negative response (PhNR) in the rat after optic nerve transection. Doc Ophthalmol 111(1):23–31. doi:10.1007/s10633-005-2629-8 CrossRefPubMedGoogle Scholar
  71. 71.
    Bush RA, Sieving PA (1994) A proximal retinal component in the primate photopic ERG a-wave. Invest Ophthalmol Vis Sci 35(2):635–645PubMedGoogle Scholar
  72. 72.
    Hamilton R, Bees MA, Chaplin CA, McCulloch DL (2007) The luminance-response function of the human photopic electroretinogram: a mathematical model. Vis Res 47(23):2968–2972CrossRefPubMedGoogle Scholar
  73. 73.
    Rufiange M, Dassa J, Dembinska O, Koenekoop RK, Little JM, Polomeno RC et al (2003) The photopic ERG luminance-response function (photopic hill): method of analysis and clinical application. Vis Res 43(12):1405–1412. doi:10.1016/S0042-6989(03)00118-4 CrossRefPubMedGoogle Scholar
  74. 74.
    Dimopoulos IS, Freund PR, Redel T, Dornstauder B, Gilmour G, Sauve Y (2014) Changes in rod and cone-driven oscillatory potentials in the aging human retina. Invest Ophthalmol Vis Sci 55(8):5058–5073. doi:10.1167/iovs.14-14219 CrossRefPubMedGoogle Scholar
  75. 75.
    Ring M, Gaigg SB, Bowler DM (2015) Object-location memory in adults with autism spectrum disorder. Autism Res 8(5):609–619. doi:10.1002/aur.1478 CrossRefPubMedGoogle Scholar
  76. 76.
    Ring M, Gaigg SB, Bowler DM (2015) Relational memory processes in adults with autism spectrum disorder. Autism Res. doi:10.1002/aur.1493 Google Scholar
  77. 77.
    Shen Y, Rampino MA, Carroll RC, Nawy S (2012) G-protein-mediated inhibition of the Trp channel TRPM1 requires the Gβγ dimer. PNAS 109(22):8752–8757. doi:10.1073/pnas.1117433109 CrossRefPubMedPubMedCentralGoogle Scholar
  78. 78.
    Skafidas E, Testa R, Zantomio D, Chana G, Everall IP, Pantelis C (2014) Predicting the diagnosis of autism spectrum disorder using gene pathway analysis. Mol Psychiatry 19(4):504–510. doi:10.1038/mp.2012.126 CrossRefPubMedPubMedCentralGoogle Scholar
  79. 79.
    Dhingra A, Jiang M, Wang TL, Lyubarsky A, Savchenko A, Bar-Yehuda T et al (2002) Light response of retinal ON bipolar cells requires a specific splice variant of GαO. J Neurosci 22(12):4878–4884PubMedGoogle Scholar
  80. 80.
    Dhingra A, Lyubarsky A, Jiang M, Pugh EN Jr, Birnbaumer L, Sterling P et al (2000) The light response of ON bipolar neurons requires GαO. J Neurosci 20(24):9053–9058PubMedGoogle Scholar
  81. 81.
    Dhingra A, Ramakrishnan H, Neinstein A, Fina ME, Xu Y, Li J et al (2012) Gβ3 is required for normal light ON responses and synaptic maintenance. J Neurosci 32(33):11343–11355. doi:10.1523/JNEUROSCI.1436-12.2012 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Optometry and Vision ScienceFlinders UniversityAdelaideAustralia
  2. 2.Autism Research GroupCity University LondonLondonUK
  3. 3.Department of OphthalmologyUniversity ClinicRegensburgGermany
  4. 4.Clinical and Academic Department of OphthalmologyGreat Ormond Street Hospital for ChildrenLondonUK

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