2018
DOI: 10.1038/s41598-018-24318-x
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EEG Analytics for Early Detection of Autism Spectrum Disorder: A data-driven approach

Abstract: Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for … Show more

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Cited by 258 publications
(190 citation statements)
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References 67 publications
(71 reference statements)
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“…Before 6 months of age, children later diagnosed with autism did not seem to differ from their typically developing peers in overt social behaviours (Elsabbagh et al, 2014;Landa and Garrett-Mayer, 2006;Ozonoff et al, 2010;Rozga et al, 2011;Young et al, 2009;Zwaigenbaum et al, 2005), giving the impression that the initial development of these infants might be intact. However, recent research suggests an array of atypical signs related to, and, beyond the social domain detectable by 6 months in infants who later develop autism (e.g., oculo-motor functions, motor behaviour, visual perception, vocalizations, and their underlying neural structure and functions; Bhat et al, 2012;Bosl et al, 2018;Brisson et al, 2014;Einspieler et al, 2014;Estes et al, 2015;Iverson et al, 2019;Jones and Klin, 2013;Paul et al, 2011;Wolff et al, 2012). Notably, observable social behaviours (e.g., orienting toward or scanning of socially relevant audio and visual information) that appear similar between young infants with and without ASD may rely on disparate neural mechanisms (e.g., Blasi et al, 2015;Braukmann et al, 2018;Elsabbagh et al, 2012;Lloyd-Fox et al, 2018).…”
mentioning
confidence: 99%
“…Before 6 months of age, children later diagnosed with autism did not seem to differ from their typically developing peers in overt social behaviours (Elsabbagh et al, 2014;Landa and Garrett-Mayer, 2006;Ozonoff et al, 2010;Rozga et al, 2011;Young et al, 2009;Zwaigenbaum et al, 2005), giving the impression that the initial development of these infants might be intact. However, recent research suggests an array of atypical signs related to, and, beyond the social domain detectable by 6 months in infants who later develop autism (e.g., oculo-motor functions, motor behaviour, visual perception, vocalizations, and their underlying neural structure and functions; Bhat et al, 2012;Bosl et al, 2018;Brisson et al, 2014;Einspieler et al, 2014;Estes et al, 2015;Iverson et al, 2019;Jones and Klin, 2013;Paul et al, 2011;Wolff et al, 2012). Notably, observable social behaviours (e.g., orienting toward or scanning of socially relevant audio and visual information) that appear similar between young infants with and without ASD may rely on disparate neural mechanisms (e.g., Blasi et al, 2015;Braukmann et al, 2018;Elsabbagh et al, 2012;Lloyd-Fox et al, 2018).…”
mentioning
confidence: 99%
“…It is possible that different patterns of results would be found if we repeated this study in a different population, for example in autistic children, infants at high risk for being diagnosed with ASD (c.f. Bosl, Tager-Flusberg, & Nelson, 2018), or in autistic adults who score more highly on the RAADS-R.…”
Section: Discussionmentioning
confidence: 99%
“…Afterwards, applying bandpass low-frequency filters of 0.3Hz, a high-frequency filter of 30Hz and notch filters of 50Hz, the signals can be further utilized by the software modules. The user can adjust the notch and bandpass filters in the top menus [34,36,37]. More specific 50/60 Hz notch filters are available and options for bandpass filters of 1-50, 7-13, 15-50, 5-50, 0.30-30 Hz as well.…”
Section: Data Collection and Processingmentioning
confidence: 99%
“…In general artifacts that probably result of abnormal behavior are not excluded at this version, even though users can apply external sources [36] to remove these artifacts. While our primary goal is to use the software for art and behavioral therapy mainly in ASD patients, latest studies has clinical demonstrated that behavioral characteristics might introduce artifacts into the EEG signals which are very difficult to be identified in young ASD patients [37]. Also while latest studies concluded to the inefficient classification of ASD patients based only on EEG signal analysis [39], it seems that the calculation and study of the coherence differences between children with ASD and healthy controls could be a potential solution.…”
Section: Data Collection and Processingmentioning
confidence: 99%