Manual and automated assessments of general movements in neonates are associated with early autism risk at 18 months

General movements (GMs) refer to infants’ spontaneous motor activities before the emergence of voluntary motor activity. Abnormal GMs in neonates have been regarded as a marker of poor neurodevelopmental outcomes, with preliminary findings in autism. To examine the relation between abnormal GMs in neonates and autism risk, videos of neonates (n = 76) extracted from a Japanese birth cohort were retrospectively exploited. A manual assessment of GMs was completed using the General Movement Assessment Optimality Score (GMOS-R) rated by professionals blinded from all clinical information. An automated assessment of several features of neonates’ motor activity was also conducted using videos of neonates. Outcome measures were the M-CHAT score at 18 months to document autistic risk status and the Strengths and Difficulties Questionnaire (SDQ) at four years to measure non-autistic general psychopathology. The GMOS-R total score and subscores significantly predicted the autistic risk status according to M-CHAT, but not any SDQ scales or the Total Difficulties score. In the manual assessment of GM, “Global poorness of motion” was the most informative feature in predicting ASD risk. The classification performance systematically increased with the addition of automatically extracted features, as indicated by the Loglikelihood tests. In contrast, the DeLong tests for comparison of AUC failed to reach statistical significance. Such improvement came mainly from incorporating information about the imbalance in motion strength between the upper and lower limbs, and was more marked for awake babies. This finding confirms the relevance of considering abnormal motor patterns in neonates as an early marker of autistic risk.

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Publication Details

Journal
Scientific Reports
Published
2026-01-19
DOI
https://doi.org/10.1038/s41598-025-34525-y
Primary Topic
Autism Spectrum Disorder Research
Type
article
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article

Manual and automated assessments of general movements in neonates are associated with early autism risk at 18 months

Hirokazu Doi, Giulio Bertamini, Midori Yamamoto, Muriel Chauvet et al.
Scientific Reports
Autism Spectrum Disorder Research
article

Manual and automated assessments of general movements in neonates are associated with early autism risk at 18 months

Hirokazu Doi, Giulio Bertamini, Midori Yamamoto, Muriel Chauvet, X. Benarous, Akira Furui, T. Tsuji, Koji Shimatani, Catherine Saint Georges, Kenichi Sakurai, Hugues Pellerin, Pessia Grywac, Maeva Da Cunha, Marie-Christine Laznik, Isabelle Habgarth, Chisato Mori, Salvatore Maria Anzalone, David Cohen, Annik Beaulieu, Orna Lev-Enacab
article en

Abstract

General movements (GMs) refer to infants’ spontaneous motor activities before the emergence of voluntary motor activity. Abnormal GMs in neonates have been regarded as a marker of poor neurodevelopmental outcomes, with preliminary findings in autism. To examine the relation between abnormal GMs in neonates and autism risk, videos of neonates (n = 76) extracted from a Japanese birth cohort were retrospectively exploited. A manual assessment of GMs was completed using the General Movement Assessment Optimality Score (GMOS-R) rated by professionals blinded from all clinical information. An automated assessment of several features of neonates’ motor activity was also conducted using videos of neonates. Outcome measures were the M-CHAT score at 18 months to document autistic risk status and the Strengths and Difficulties Questionnaire (SDQ) at four years to measure non-autistic general psychopathology. The GMOS-R total score and subscores significantly predicted the autistic risk status according to M-CHAT, but not any SDQ scales or the Total Difficulties score. In the manual assessment of GM, “Global poorness of motion” was the most informative feature in predicting ASD risk. The classification performance systematically increased with the addition of automatically extracted features, as indicated by the Loglikelihood tests. In contrast, the DeLong tests for comparison of AUC failed to reach statistical significance. Such improvement came mainly from incorporating information about the imbalance in motion strength between the upper and lower limbs, and was more marked for awake babies. This finding confirms the relevance of considering abnormal motor patterns in neonates as an early marker of autistic risk.

Scientific ReportsVol. 16(1)
Hiroshima University (JP), Prefectural University of Hiroshima (JP), Centre National de la Recherche Scientifique (FR), Inserm (FR), Chiba University (JP), Universidade de São Paulo (BR), Université Paris Cité (FR), Sorbonne Université (FR), Sorbonne Paris Cité (FR), Assistance Publique – Hôpitaux de Paris (FR), Laboratoire Cognitions Humaine et Artificielle (FR), Pitié-Salpêtrière Hospital (FR), Institut Pierre Louis d‘Épidémiologie et de Santé Publique (FR), Institut Systèmes Intelligents et de Robotique (FR), Nagasaki University (JP), Université Paris 8 (FR), Nagaoka University of Technology (JP), University of Haifa (IL)
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Autism Spectrum Disorder Research
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