New Ways to Predict Autism Spectrum Disorders
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Developmental Neuroscience".
Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 198
Special Issue Editors
Interests: multi-sensory perception; autism; predictive coding; attention; developmental disorders
Special Issue Information
Dear Colleagues,
Autism spectrum disorder (ASD) is a highly heritable, heterogeneous neurodevelopmental disorder characterized by impaired social interaction and communication, as well as restricted, repetitive behavior presenting in early childhood. Therapeutic interventions are most effective if started early in life; however, diagnosis often remains delayed, partly because the diagnosis of ASD is based on identifying atypical behaviors that may not emerge until the disorder is well established.
It would signal great progress to find biomarkers that can help to identify children at risk during the pre-symptomatic period, assist with early diagnosis, stratify patients into subgroups, and predict therapeutic responses tailored for each different subtype of patient. The main aim of this Special Issue of Brain Sciences is to provide a collection of studies providing the most recent results in the field of research on promising biomarkers for ASD.
Authors are invited to submit cutting-edge research and reviews that present potential biomarkers related to the detection and identification of ASD, including studies on the following: neuroimaging and electrophysiologic, physical, and behavioral characteristics (adaptive behaviors, sensory profiles, language, cognitive). In particular, we aim to present biomarkers in autism research that may have a significant effect on therapeutic responses.
Dr. Marco Turi
Dr. Themis Karaminis
Guest Editor
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Keywords
- autism
- screening and risk factor
- early diagnosis
- biomarkers
- therapeutic outcome
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