title: Characterization of infant mu rhythm immediately before crawling: A high-resolution EEG study.
abstract: Crawling is an important milestone in infant motor development. However, infants with developmental motor disorders can exhibit delays, or even miss, in the acquisition of crawling skill. And little information is available from the neurodevelopmental domain about the changes in brain function with intervention. The mu rhythm can potentially play a substantial role in understanding human motor development at early ages in infants, as it has in adults. Studies about the mu rhythm in infants were in coarse temporal resolution with longitudinal samples taken months or years apart. Details about the infant mu rhythm at a fine age resolution has not been fully revealed, which leads to contradictory evidence about its formulation and developmental changes of its spectral origins and, therefore, impedes the full understanding of motor brain development before crawling skill acquisition. The present study aims to expand knowledge about the infant mu rhythm and its spatio-spectral pattern shifts along maturation immediately before crawling. With high-density EEG data recorded on a weekly basis and simultaneous characterization of spatio-spectral patterns of the mu rhythm, subtle developmental changes in its spectral peak, frequency range, and scalp topography are revealed. This mu rhythm further indicates a significant correlation to the crawling onset while powers from other frequency bands do not show such correlations. These details of developmental changes about the mu rhythm provide an insight of rapid changes in the human motor cortex in the first year of life. Our results are consistent with previous findings about the peak frequency shifting of the mu rhythm and further depict detailed developmental curves of its frequency ranges and spatial topographies. The infant mu rhythm could potentially be used to assess motor brain deficiencies at early ages and to evaluate intervention effectiveness in children with neuromotor disorders.
authors.affiliation: School of Electrical and Computer Engineering, University of Oklahoma, United States.
authors.forename: Ran
authors.initials: R
authors.lastname: Xiao
authors.affiliation: School of Electrical and Computer Engineering, University of Oklahoma, United States.
authors.forename: Xiao
authors.initials: X
authors.lastname: Qi
authors.affiliation: School of Electrical and Computer Engineering, University of Oklahoma, United States.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Patino
authors.affiliation: School of Computer Science, University of Oklahoma, United States; Stephenson School of Biomedical Engineering, University of Oklahoma, United States.
authors.forename: Andrew H
authors.initials: AH
authors.lastname: Fagg
authors.affiliation: Department of Rehabilitation Sciences, University of Oklahoma Health Sciences Center, United States.
authors.forename: Thubi H A
authors.initials: THA
authors.lastname: Kolobe
authors.affiliation: School of Aerospace and Mechanical Engineering, University of Oklahoma, United States; Stephenson School of Biomedical Engineering, University of Oklahoma, United States.
authors.forename: David P
authors.initials: DP
authors.lastname: Miller
authors.affiliation: School of Electrical and Computer Engineering, University of Oklahoma, United States; Stephenson School of Biomedical Engineering, University of Oklahoma, United States. Electronic address: leiding@ou.edu.
authors.forename: Lei
authors.initials: L
authors.lastname: Ding
mesh_terms: D058256:Brain Waves; D002540:Cerebral Cortex / Q000502:physiology; D002657:Child Development; D004569:Electroencephalography; D005260:Female; D006801:Humans; D007223:Infant; D008124:Locomotion; D008297:Male; D009044:Motor Cortex / Q000254:growth & development* / Q000502:physiology*; D009068:Movement
keywords: Crawling; High resolution; Infant EEG; Motor development; Mu rhythm