Behavior and interaction imaging at 9 months of age predict autism/intellectual disability in high-risk infants with West syndrome.
Lisa OussGiuseppe PalestraCatherine Saint-GeorgesMarluce Leitgel GilleMohamed AfsharHugues PellerinKevin BaillyMohamed ChetouaniLaurence RobelBernard GolseRima NabboutIsabelle DesguerreMariana Guergova-KurasDavid CohenPublished in: Translational psychiatry (2020)
Automated behavior analysis are promising tools to overcome current assessment limitations in psychiatry. At 9 months of age, we recorded 32 infants with West syndrome (WS) and 19 typically developing (TD) controls during a standardized mother-infant interaction. We computed infant hand movements (HM), speech turn taking of both partners (vocalization, pause, silences, overlap) and motherese. Then, we assessed whether multimodal social signals and interactional synchrony at 9 months could predict outcomes (autism spectrum disorder (ASD) and intellectual disability (ID)) of infants with WS at 4 years. At follow-up, 10 infants developed ASD/ID (WS+). The best machine learning reached 76.47% accuracy classifying WS vs. TD and 81.25% accuracy classifying WS+ vs. WS-. The 10 best features to distinguish WS+ and WS- included a combination of infant vocalizations and HM features combined with synchrony vocalization features. These data indicate that behavioral and interaction imaging was able to predict ASD/ID in high-risk children with WS.
Keyphrases
- intellectual disability
- autism spectrum disorder
- attention deficit hyperactivity disorder
- machine learning
- high resolution
- magnetic resonance
- hepatitis c virus
- mental health
- big data
- high throughput
- mass spectrometry
- human immunodeficiency virus
- computed tomography
- adipose tissue
- single molecule
- living cells
- diffusion weighted imaging
- electronic health record
- hiv infected
- fluorescent probe
- sensitive detection
- hiv testing