Skip to main content Skip to navigation

Conversations with a Neuron, Volume 3

Diagnosing Autism Spectrum Disorder: There’s an App for that!

Researchers study the potential to use a digital app on a phone as a screening tool to assist in the diagnosis of Autism Spectrum Disorder (ASD).

Author: Edward Hernandez

Download: [ PDF ]

Neurophysiology

Introduction

In a recent study published in JAMA Pediatrics, researchers sought to investigate whether an app on a phone or tablet could be used to screen children with ASD1. Researchers found that there is a potential for the app to detect a common characteristic among autism in children. This is important as this digital app may increase access to ASD screening that can result in early diagnosis. 

Background

ASD is a developmental disorder that affects behavior, alters cognition, and creates difficulties in communication and social skills2. ASD varies by person, some require more help than others, and there many different types of ASD. There are many risk factors for ASD including environmental, genetic, and immunological risks2,3

Diagnosing ASD is difficult due to there not being any medical tests to formally diagnose the disorder. Instead, doctors must look at the symptoms presented by the patient, while monitoring and evaluating the child’s development to diagnose them with ASD2,4. One diagnostic criterion and symptom presented by ASD is atypical eye gaze7. Early attention to social information influences an infant’s learning of social interactions. The human brain contains neural circuits which help focus gaze on social information such as faces, eyes, voices, and expressions6. In children with ASD neurodevelopment, engagement with social information is decreased and they spend more time focused elsewhere7. In this study, researchers investigated whether an app on a phone or tablet could be used to track the gaze of ASD to potentially use it to help screen patients for ASD.

Methods 

The study recruited a total of 993 toddlers aged 16-38 months average being 21 months. The researchers began by giving parents an ASD self-screening checklist known as the Modified Checklist for Toddlers, Revised with Follow Up during their children's clinical visit. Children with scores on the checklist that raised concern for risk of ASD were referred for evaluation. A total of 40 participants were diagnosed with ASD.  During the clinical visits, children would also be shown videos on an iPhone or iPad for about 10 minutes. The videos on the iPhone included a woman spinning a pinwheel and a man blowing bubbles with a bubble gun. The videos on the iPad included a woman spinning a top, a man blowing bubbles with a wand, and a video of two women in a park talking to each other. The women in the park video were set up so one woman was on each side of the screen. The other videos were set up so that the person performing the action was on one side of the screen and the toy was on the other side of the screen. In the videos, there was another toy set up on a shelf on the top corner of the screen where the toy side was. There were also videos shown on both devices that included bubbles flowing down on the screen with a gurgling sound and a video where a puppy face appeared and disappeared on either side of the screen. These videos were used as a control. The gaze of the children was tracked using the iPhone’s or iPad’s front facing camera and an algorithm for face detection and recognition1.

Figure 1: An example of how a video would set up. The spinning top would be on the right side of the screen along with the other toy on the shelf on the top corner. The person would be on the other side of the screen.
Figure 1. An example of how a video would be set up. The spinning top would be on the right side of the screen along with the other toy on the shelf on the top corner. The person would be on the other side of the screen.

Results

For the videos with the toy and a person, the researchers found that the children that were diagnosed with ASD group spent significantly more time focusing on the side of the screen where the toys were compared to the typical development group. In the video with the women talking at the park, the gaze of typically developing children was found to coordinate with the flow of the conversation; the gaze of the ASD children was not correlated with the flow of the speech and showed a more variable pattern. In the video with gurgling sound and bubbles on the screen, there were no significant differences between the ASD and typical development group. In the video with the puppy face, the gaze of both groups shifted as it appeared on either side of the screen. The results demonstrate the ASD symptom of atypical eye gaze, where those with ASD have decreased engagement with social information. The results suggest that the app has the potential to be used to measure eye gaze and detect early symptoms of ASD related to social attention. 

Discussion

The findings and potential use of this tool are significant as most people have phones and could easily use this app to identify ASD symptoms early on in their child’s life. ASD can be diagnosed in children as young as 18 months or sometimes even younger, however, in the US many aren’t diagnosed until the age of 4 or sometimes even much older8,9. Additionally, White children are diagnosed with ASD at higher rates than Black or Hispanic children. The ratio of ASD diagnosis between White and Balck children is 1.1 and between White and Hispanic children it is 1.2. This may be as a result of socioeconomic factors that lead to a lack of access to ASD evaluation and services. However, these ratios have decreased in recent years. As technology has continued to advance, it also becomes more inexpensive. Using an app, which most people can access and use, to detect and screen for ASD symptoms will greatly increase access and allow for earlier diagnosis of ASD. Early diagnosis of ASD is significant in the treatment of it, as it can result in earlier interventions when the brain is at a critical point of development. Early intervention can improve function and attenuate the symptoms of ASD11,12.

 

[+] References

1.

Chang, Z., Di Martino, J., Aiello, R., Baker, J., Carpenter, K., Compton, S., Davis, N., Eichner, B., Espinosa, S., Flowers, J., Franz, L., Harris, A., Howard, J., Perochon, S., Perrin, E., Krishnappa Babu, P., Spanos, M., Sullivan, C., Walter, B., Kollins, S., Dawson, G., & Sapiro, G. (2021). Computational Methods to Measure Patterns of Gaze in Toddlers With Autism Spectrum Disorder. JAMA Pediatrics, 175(7).

2.

National Institute of Mental Health. (2021) Autism Spectrum Disorder. https://www.nimh.nih.gov/health/topics/autism-spectrum-disorders-asd/index.shtml.

3.

Amaral D. G. (2017). Examining the Causes of Autism. Cerebrum : the Dana forum on brain science, 2017, cer-01-17.

4.

Hyman SL, Levey SE, Myers SM, Council on Children with Disabilities, Section on Developmental and Behavioral Pediatrics. Identification, Evaluation, and Management of Children With Autism Spectrum Disorder. Peditarics. 2020 Jan;145(1).

5.

Adolphs, R. (2003) Cognitive neuroscience of human social behaviour. Nat Rev Neurosci 4, 165–178 https://doi.org/10.1038/nrn1056.

6.

Reynolds, G. D., & Roth, K. C. (2018). The Development of Attentional Biases for Faces in Infancy: A Developmental Systems Perspective. Frontiers in Psychology, 9. doi:10.3389/fpsyg.2018.00222.

7.

Chawarska, K., Macari, S., & Shic, F. (2013). Decreased Spontaneous Attention to Social Scenes in 6-Month-Old Infants Later Diagnosed with Autism Spectrum Disorders. Biological Psychiatry, 74(3), 195–203. doi:10.1016/j.biopsych.2012.11.022.

8.

Christensen, Deborah L et al. “Prevalence and Characteristics of Autism Spectrum Disorder Among 4-Year-Old Children in the Autism and Developmental Disabilities Monitoring Network.” Journal of developmental and behavioral pediatrics : JDBP vol. 37,1 (2016): 1-8. doi:10.1097/DBP.0000000000000235.

9.

Ozonoff, S., Young, G. S., Landa, R. J., Brian, J., Bryson, S., Charman, T., Chawarska, K., Macari, S. L., Messinger, D., Stone, W. L., Zwaigenbaum, L., & Iosif, A. M. (2015). Diagnostic stability in young children at risk for autism spectrum disorder: a baby siblings research consortium study. Journal of child psychology and psychiatry, and allied disciplines, 56(9), 988–998. https://doi.org/10.1111/jcpp.12421.

10.

Center for Disease Control. (2020) Autism Spectrum Disorder: Spotlight On: Racial and Ethnic Differences in Children Identified with Autism Spectrum Disorder. https://www.cdc.gov/ncbddd/autism/addm-community-report/differences-in-children.html.

11.

Sara Jane Webb, Emily J. H. Jones, Jean Kelly & Geraldine Dawson (2014) The motivation for very early intervention for infants at high risk for autism spectrum disorders, International Journal of Speech-Language Pathology, 16:1, 36-42, DOI: 10.3109/17549507.2013.861018.

12.

Landa R. J. (2018). Efficacy of early interventions for infants and young children with, and at risk for, autism spectrum disorders. International review of psychiatry (Abingdon, England), 30(1), 25–39. https://doi.org/10.1080/09540261.2018.1432574.

[+] Other Work By Edward Hernandez

A new target for depression treatment?

Neuroanatomy

It was found that overexpression of Regulator of G Protein Signaling 8 (RGS8) protein is linked to resistance of depression. This could lead to a new drug target for treatment of depression.