When it comes to ADHD and ASD, the eyes could tell it all – Neuroscience News

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

Source: University of South Australia

It’s often said that “the eyes say it all,” but regardless of their outward expression, the eyes may also be able to 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 distinct signals for attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) providing a potential biomarker for each requirement.

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 had higher overall ERG energy, while that children with ASD had less ERG energy.

Research optometrist at Flinders University, Dr. Paul Constable, says the preliminary results indicate promising results for improved diagnostics and treatments in the future.

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

“Our research aims to improve this. By exploring how retinal signals respond to light stimuli, we hope to develop more accurate and earlier diagnoses for different neurodevelopmental conditions.

“Retinal signals have specific nerves that generate them, so if we can identify those differences and map them to specific pathways that use different chemical signals that are also used in the brain, then we can show distinct differences for children with ADHD and ASD and potentially other neurodevelopmental conditions.

“This study provides preliminary evidence of neurophysiological changes that not only differentiate ADHD and ASD from typically developing children, but also evidence that they can be distinguished from each other based on ERG characteristics.”

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

Research optometrist at Flinders University, Dr. Paul Constable, says the preliminary results indicate promising results for improved diagnostics and treatments in the future. Image is in 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 condition in which children behave, communicate, interact and learn differently than most other people.

Co-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 extend to other neurological conditions.

“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 the abnormalities in retinal signals that are specific to these and other neurodevelopmental disorders, what we have observed so far shows that we are on the verge of something incredible. .

“It’s really about looking at this space; in this case, the eyes could reveal all.

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

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About this ADHD and ASD research news

Author: Annabel Mansfield
Source: University of South Australia
Contact: Annabel Mansfield – University of South Australia
Image: Image is in public domain

Original research: Free 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: To assess 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 controls participated in this study. Full-field light-adapted electroretinograms (ERGs) were recorded using a Troland protocol, accounting for pupil size, with five flash intensities ranging from -0.12 to 1.20 log photopeak cd.sm–2. A DWT analysis was performed using the Haar wavelet on the waveforms to examine the energy in the a and b wave time windows and the oscillatory potentials (OP) which yielded six related DWT coefficients to these settings. The center frequency bands were 20 to 160 Hz relative to a-wave, b-wave, and OP represented by the coefficients: a20, a40, b20, b40, op80, and op160, respectively. In addition, the b-wave amplitude and the percent energy contribution of OPs (%OP) in the total ERG broadband energy were assessed.

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

Conclusion: This methodological approach can provide insight into neuronal activity in studies investigating group differences where retinal signaling may be altered by neurodevelopment or neurodegenerative conditions. However, further work will be needed to determine if retinal signal analysis can offer a classification model for neurodevelopmental conditions in which there is co-occurrence, such as ASD and ADHD.

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