Discrete Wavelet Transform Analysis of the Electroretinogram in Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder

Abstract

BackgroundTo evaluate the electroretinogram waveform in autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) using a discrete wavelet transform (DWT) approach.MethodsA total of 55 ASD, 15 ADHD and 156 control individuals took part in this study. Full field light-adapted electroretinograms (ERGs) were recorded using a Troland protocol, accounting for pupil size, with five flash strengths ranging from –0.12 to 1.20 log photopic cd.s.m–2. A DWT analysis was performed using the Haar wavelet on the waveforms to examine the energy within the time windows of the a- and b-waves and the oscillatory potentials (OPs) which yielded six DWT coefficients related to these parameters. The central frequency bands were from 20–160 Hz relating to the a-wave, b-wave and OPs represented by the coefficients: a20, a40, b20, b40, op80, and op160, respectively. In addition, the b-wave amplitude and percentage energy contribution of the OPs (%OPs) in the total ERG broadband energy was evaluated.ResultsThere were significant group differences (p < 0.001) in the coefficients corresponding to energies in the b-wave (b20, b40) and OPs (op80 and op160) as well as the b-wave amplitude. Notable differences between the ADHD and control groups were found in the b20 and b40 coefficients. In contrast, the greatest differences between the ASD and control group were found in the op80 and op160 coefficients. The b-wave amplitude showed both ASD and ADHD significant group differences from the control participants, for flash strengths greater than 0.4 log photopic cd.s.m–2 (p < 0.001).ConclusionThis methodological approach may provide insights about neuronal activity in studies investigating group differences where retinal signaling may be altered through neurodevelopment or neurodegenerative conditions. However, further work will be required to determine if retinal signal analysis can offer a classification model for neurodevelopmental conditions in which there is a co-occurrence such as ASD and ADHD.

Electroretinography in adults with high‐functioning autism spectrum disorder

“…While Constable et al (2020Constable et al ( , 2022 and Lee et al (2022) focused on younger autistic individuals between 6-27 years of age, we focused on adults (mean age: 34 years). Although the former studies (Constable et al, 2020(Constable et al, , 2022Lee et al, 2022) excluded autistic participants with an IQ score below 65 or with Fragile-X or Rett syndrome, their autistic groups might have covered a wider scope of different forms of ASD compared to our study sample, which encompassed a homogeneous sample of patients with Asperger's syndrome with a higher average IQ (mean IQ = 107 (11) compared to mean IQ = 98.9 (16.5) in Constable et al's (2020) sample and mean IQ = 99.6 (18.9) in Lee et al's (2022) sample). This prompts the question whether changes in the developmental trajectories of individuals with autism or differences in the investigated ASD subtypes might have led to the diverging results.…”

“…They additionally found attenuated a‐wave amplitudes at higher flash strengths, as well as increased b‐wave peak times in children and adolescents with ASD (Constable et al, 2020). Another investigation (Constable et al, 2022) analyzed LA‐ERG responses in ASD with a discrete wavelet transform approach and not only confirmed decreased b‐wave amplitudes at high flash strengths but also found a reduced energy of the OPs in individuals with ASD, which might contribute to the observed b‐wave alterations. The OPs mainly originating in the amacrine cells are reported to be sensitive to disruption of dopamine‐ or GABA‐modulated neuronal pathways (Constable et al, 2022; Wachtmeister, 1998).…”

“…Another investigation (Constable et al, 2022) analyzed LA‐ERG responses in ASD with a discrete wavelet transform approach and not only confirmed decreased b‐wave amplitudes at high flash strengths but also found a reduced energy of the OPs in individuals with ASD, which might contribute to the observed b‐wave alterations. The OPs mainly originating in the amacrine cells are reported to be sensitive to disruption of dopamine‐ or GABA‐modulated neuronal pathways (Constable et al, 2022; Wachtmeister, 1998). A recent study described a promising machine learning model for ASD detection based on ERG data using spectral and time‐domain features which reportedly achieves a classification accuracy of 86% and sensitivity of 98% (Mohammad‐Manjur et al, 2022).…”

Visual electrophysiology and “the potential of the potentials”

“…The lower panels highlight multiple components in the waveform and potential inferences that could be made, with more advanced quantitative analyses, regarding physiological and pathophysiological processes in specific retinal neuronal groups. Several papers have used more sophisticated analyses, such as discrete wavelet transforms [70][71][72], applied for example to separately evaluate ON and OFF components in responses [70]. Frequently, novel analyses are used in conjunction with specifically designed protocols, hence many of these developments have occurred simultaneously.…”

Time–Frequency Analysis of ERG With Discrete Wavelet Transform and Matching Pursuits for Glaucoma

“… 30 , 38 A recent paper explored the use of the DWT in the photopic ERG and found differences between individuals diagnosed with autism spectrum disorder compared with control subjects. 39 …”