When it comes to ADHD and ASD, the eyes could reveal everything


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Summary: Measuring the electrical activity of the retina in response to light stimuli could be a biomarker for ADHD and autism, researchers report.

Source: University of South Australia

It’s often said that “the eyes tell everything,” but regardless of their outward expression, the eyes may also signal neurodevelopmental disorders like ASD and ADHD, according to new research from Flinders University and the University of South Australia.

In the first study of its kind, the researchers found that recordings from the retina could identify distinct signals for both attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), providing a potential biomarker for each condition .

Using the “electroretinogram” (ERG) – a diagnostic test that measures the electrical activity of the retina in response to a light stimulus – researchers found that children with ADHD showed higher total ERG energy, while children with ASD showed lower ERG energy showed.

Research optician at Flinders University, Dr. Paul Constable says the preliminary results point to promising results for improved diagnosis and treatment in the future.

“ASD and ADHD are the most common neurodevelopmental disorders diagnosed in childhood. However, because they often share similar characteristics, diagnosing both disorders can be lengthy and complicated,” says Dr. constable

“Our research aims to improve this. By studying how signals in the retina respond to light stimuli, we hope to develop more accurate and earlier diagnoses for various neurodevelopmental states.

“Retinal signals have specific nerves that generate them. So if we can identify these differences and localize them to specific pathways that use different chemical signals that are also used in the brain, then we can show clear differences for children with ADHD and ASD and possibly other neurodevelopmental disorders.”

“This study provides preliminary evidence of neurophysiological changes that not only distinguish ADHD and ASD from normally developing children, but also evidence that they can be distinguished from one another based on ERG properties.”

According to the World Health Organization, one in 100 children has ASD, with 5-8 percent of children being diagnosed with ADHD.

This shows an eye
Research optician at Flinders University, Dr. Paul Constable says the preliminary results point to promising results for improved diagnosis and treatment in the future. The image is in the public domain

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by excessive activity, difficulty paying attention, and difficulty controlling impulsive behaviors. Autism Spectrum Disorder (ASD) is also a neurodevelopmental disorder in which children behave, communicate, interact and learn in ways that are different from most other people.

Fellow researcher and expert in human and artificial cognition at the University of South Australia, Dr. Fernando Marmolejo-Ramos says the research has the potential to expand to other neurological conditions.

“Ultimately, we’re investigating how the eyes can help us understand the brain,” says Dr. Marmolejo Ramos.

“Although more research is needed to identify abnormalities in retinal signals specific to these and other neurodevelopmental disorders, our observations to date indicate that we are on the precipice of something amazing.

“It’s really about observing this space; Coincidentally, the eyes could reveal everything.”

This research was conducted in collaboration with McGill University, University College London and Great Ormond Street Hospital for Children.

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About this news from ADHD and ASD research

Author: Annabel Mansfeld
Source: University of South Australia
Contact: Annabel Mansfield – University of South Australia
Picture: The image is in the public domain

Original research: Open access.
“Discrete Wavelet Transform Analysis of the Electroretinogram in Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder” by Fernando Marmolejo-Ramos et al. Frontiers in Neuroscience


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

Background: Evaluation of the electroretinogram waveform in autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) using a discrete wavelet transform (DWT) approach.

Methods: A total of 55 ASD, 15 ADHD and 156 control persons took part in this study. Light-adapted full-field electroretinograms (ERGs) were recorded using a Troland protocol accounting for pupil size with five flashes ranging from −0.12 to 1.20 log photopic cd.sm–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), yielding six DWT coefficients related to these parameters. The central frequency bands were between 20 and 160 Hz with respect 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 the percentage energy contribution of the OPs (% OPs) in the total ERG broadband energy were assessed.

Results: There were significant group differences (p < 0.001) in the coefficients corresponding to the energies in the b-wave (b20, b40) and the OPs (op80 and op160) and the b-wave amplitude. Notable differences between the ADHD and control groups were found in the b20 and b40 coefficients. In contrast, the largest differences between the ASD and control groups were found in the op80 and op160 coefficients. The b-wave amplitude showed significant group differences from the control participants for flash strengths greater than 0.4 log photopic cd.sm in both ASD and ADHD–2 (p < 0.001).

Conclusion: This methodological approach can provide insights into neuronal activity in studies examining group differences in which retinal signaling may be altered by nervous system development or neurodegenerative diseases. However, more work is needed to determine whether retinal signal analysis can provide a classification model for neurodevelopmental conditions that share co-occurrences such as ASD and ADHD.

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