Interest paradigm for early identification of autism spectrum disorder: an analysis from electroencephalography combined with eye tracking

Front Neurosci. 2024 Nov 27:18:1502045. doi: 10.3389/fnins.2024.1502045. eCollection 2024.

Abstract

Introduction: Early identification of Autism Spectrum Disorder (ASD) is critical for effective intervention. Restricted interests (RIs), a subset of repetitive behaviors, are a prominent but underutilized domain for early ASD diagnosis. This study aimed to identify objective biomarkers for ASD by integrating electroencephalography (EEG) and eye-tracking (ET) to analyze toddlers' visual attention and cortical responses to RI versus neutral interest (NI) objects.

Methods: The study involved 59 toddlers aged 2-4 years, including 32 with ASD and 27 non-ASD controls. Participants underwent a 24-object passive viewing paradigm, featuring RI (e.g., transportation items) and NI objects (e.g., balloons). ET metrics (fixation time and pupil size) and EEG time-frequency (TF) power in theta (4-8 Hz) and alpha (8-13 Hz) bands were analyzed. Statistical methods included logistic regression models to assess the predictive potential of combined EEG and ET biomarkers.

Results: Toddlers with ASD exhibited significantly increased fixation times and pupil sizes for RI objects compared to NI objects, alongside distinct EEG patterns with elevated theta and reduced alpha power in occipital regions during RI stimuli. The multimodal logistic regression model, incorporating EEG and ET metrics, achieved an area under the curve (AUC) of 0.75, demonstrating robust predictive capability for ASD.

Discussion: This novel integration of ET and EEG metrics highlights the potential of RIs as diagnostic markers for ASD. The observed neural and attentional distinctions underscore the utility of multimodal biomarkers for early diagnosis and personalized intervention strategies. Future work should validate findings across broader age ranges and diverse populations.

Keywords: autism spectrum disorder (ASD); biomarker; early diagnosis; electroencephalography (EEG); eye-tracking (ET); interest paradigm.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Financial support for this research was provided by the General Projects of Shenzhen Science and Technology Program, China (Grant number JCYJ20210324131211031); Shenzhen Maternity and Child Healthcare Hospital (Grant number FYA2022018); the Massachusetts General Hospital (Grant number 233263) and Shenzhen Sanming project (Grant number SZSM201512009).