Stratification and Predictive Biomarkers in Autism and Other Neurodevelopmental Disorders: Advancing EEG and Eye-Tracking Approaches to Optimize Intervention Strategies
Autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs) are characterized by substantial heterogeneity in etiology, symptomatology, developmental course, and treatment response. This heterogeneity poses significant challenges for clinical practice and research, particularly in the design and evaluation of effective early interventions. Attempts to stratify children diagnosed with these conditions have been primarily based on behavioral criteria, but clinical subtyping operates without reference to the underlying neurobiological mechanisms and has limited predictive value of the forthcoming developmental path. To advance tailored interventions in ASD and other NDDs, there is a growing emphasis on the discovery and validation of biomarkers that can objectively identify clinically meaningful subgroups and predict intervention response.
Identifying reliable stratification and predictive biomarkers is thus essential for improving clinical trial design, tailoring interventions, and optimizing precision medicine approaches. This Research Topic will highlight innovative research using electroencephalography (EEG) and eye-tracking (ET) as scalable, non-invasive, and developmentally sensitive tools for: • characterizing heterogeneity and stratification within autistic and neurodiverse individuals • identifying predictive biomarkers for intervention response and prognosis • bridging neural, cognitive, and behavioral levels of analysis • advancing early detection and personalized treatment approaches.
Both modalities offer sensitive windows into neurocognitive processing, social communication, and attentional dynamics, making them well-suited for the identification of predictive and stratification biomarkers across the first years of life. Studies generating empirical evidence on whether baseline stratification using EEG and ET metrics can reliably predict individual developmental trajectories and intervention outcomes will be given priority.
Submissions may address, but are not limited to, the following areas: • new EEG and ET paradigms for biomarker discovery in ASD/NDDs • stratification approaches to reduce heterogeneity in clinical and intervention trials • predictive modeling of intervention response and developmental outcomes • longitudinal EEG/ET across early development • integration of multimodal biomarkers (e.g., EEG, ET, digital phenotyping, behavioral measures) • translational (from animal to human models) and clinical frameworks linking biomarkers to personalized interventions.
Submissions of various article types are welcomed, including Original Research, Reviews, Systematic Reviews, Methods, and Perspectives.
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