The infant motor system predicts actions based on visual statistical learning

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2019-01, Vol.185, p.947-954
• Main Authors: Monroy, Claire D., Meyer, Marlene, Schröer, Lisanne, Gerson, Sarah A., Hunnius, Sabine
• Format: Article
• Language: English
• Subjects: Action prediction; Anticipation, Psychological - physiology; Babies; Brain - physiology; EEG; Electroencephalography; Female; Humans; Hypotheses; Infant; Infants; Knowledge; Learning - physiology; Male; Motor Activity; Motor skill learning; Mu rhythm; Sensorimotor integration; Statistical learning; Statistics; Studies; Visual discrimination learning
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2017.12.016

Motor theories of action prediction propose that our motor system combines prior knowledge with incoming sensory input to predict other people's actions. This prior knowledge can be acquired through observational experience, with statistical learning being one candidate mechanism. But can knowledge learned through observation alone transfer into predictions generated in the motor system? To examine this question, we first trained infants at home with videos of an unfamiliar action sequence featuring statistical regularities. At test, motor activity was measured using EEG and compared during perceptually identical time windows within the sequence that preceded actions which were either predictable (deterministic) or not predictable (random). Findings revealed increased motor activity preceding the deterministic but not the random actions, providing the first evidence that the infant motor system can use knowledge from statistical learning to predict upcoming actions. As such, these results support theories in which the motor system underlies action prediction. •We investigated whether statistical learning can result in predictive motor activation in the infant brain.•Mu rhythm suppression, an index of motor activation, occurred prior to actions that were statistically deterministic•These findings show that knowledge gained via observation translates into action predictions generated in the motor system•The functional role of infant statistical learning skills extends to the development of the human action-observation network.