Researchers report that compared with control mice, mouse models of autism spectrum disorders (ASD) exhibited altered arousal patterns, as measured by spontaneous pupil diameter fluctuations, which were detectable prior to symptom onset; in a study of 75 girls under age 6, a machine learning algorithm trained to identify ASD mice based on pupil fluctuations could distinguish Rett syndrome patients from typically developing controls based on heart rate fluctuations, suggesting a potential biomarker for early detection of developmental disorders.
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Article #18-20847: "Deep learning of spontaneous arousal fluctuations detects early cholinergic defects across neurodevelopmental mouse models and patients," by Pietro Artoni et al.
MEDIA CONTACT: Bethany Tripp, Boston Children's Hospital, MA; tel: 617-919-3110; e-mail: bethany.tripp@childrens.harvard.edu
Proceedings of the National Academy of Sciences