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When it comes to ADHD and ASD, the eyes can reveal it all – Neuroscience News

Overview: Measuring the electrical activity of the retina in response to a light stimulus 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 whatever their outward appearance, the eyes can also signal neurodevelopmental disorders such as ASD and ADHD, according to new research from Flinders University and the University of South Australia.

In the first study of its kind, researchers found that retinal recordings could identify different 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 overall ERG energy, while children with ASD had less ERG energy. showed energy.

Research optometrist at Flinders University, Dr. Paul Constable, says the preliminary findings show promising results for better diagnoses and treatments in the future.

“ASD and ADHD are the most common neurodevelopmental disorders diagnosed in childhood. But because they often share similar traits, making diagnoses for both conditions can be long and complicated,” says Dr. Constable.

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

“Retinal signals have specific nerves that generate them, so if we can identify these differences and locate 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 potentially other neurological disorders.”

“This study provides preliminary evidence for neurophysiological changes that not only distinguish ADHD and ASD from normally developing children, but also evidence that they can be distinguished from each other based on ERG features.”

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

Research optometrist at Flinders University, Dr. Paul Constable, says the preliminary findings show promising results for better diagnoses and treatments in the future. Image is in the public domain

Attention deficit hyperactivity disorder (ADHD) is a neurological disorder characterized by being overly active, having difficulty paying attention, and having difficulty controlling impulsive behavior. Autism spectrum disorder (ASD) is also a neurological disorder in which children behave, interact, communicate, and learn in ways that are different from most other people.

Co-investigator and expert in human and artificial cognition at the University of South Australia, Dr Fernando Marmolejo-Ramos, says the research has potential to extend into other neurological disorders.

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

“While further research is needed to establish abnormalities in retinal signals specific to these and other neurodevelopmental disorders, what we have observed so far shows that we are on the precipice of something astonishing.

“It’s really a matter of looking at this space; when it happens, the eyes can reveal everything.”

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

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About this research news on ADHD and ASD

Author: Annabel Mansfield
Source: University of South Australia
Contact: Annabel Mansfield – University of South Australia
Image: 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 Disorderby Fernando Marmolejo-Ramos et al. Frontiers in Neuroscience


Abstract

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

Background: Evaluating 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 subjects with ASD, 15 ADHD and 156 control subjects participated in this study. Light-adapted electroretinograms (ERGs) were recorded using a Troland protocol, taking pupil size into account, with five flash intensities 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 oscillating potentials (OPs), yielding six DWT coefficients associated with these parameters. The central frequency bands were from 20-160 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 percent energy contribution of the OPs (%OPs) in the total ERG broadband energy were evaluated.

Results: There 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 amplitude of the b-wave. 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 the control group were found in the op80 and op160 coefficients. The amplitude of the b-wave showed significant group differences with both ASD and ADHD relative to the control participants, for flash intensities greater than 0.4 log photopic cd.sm–2p < 0.001).

Conclusion: This methodological approach may provide insights into neuronal activity in group differences studies where retinal signaling may be altered by neurodevelopment or neurodegenerative disorders. However, further research will be needed to determine whether retinal signal analysis can provide a classification model for neurodevelopmental disorders that are co-occurring, such as ASD and ADHD.

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