Brain activity in the beta frequency band plays a critical role in sensorimotor processing, yet how it emerges over the course of development remains largely unknown. Long interpreted as a sustained oscillation whose amplitude was slowly modulated according to task demands, beta activity is in fact organized, at the single-trial level, as transient bursts rather than continuous oscillations. These bursts closely track mean beta power, and their timing strongly predicts behavior, making them a potentially more informative marker than conventional beta power. The authors set out to chart the developmental trajectory of this sensorimotor activity, from infancy to adulthood.
To this end, the team recorded the electroencephalogram (EEG) of 9-month-old infants, 12-month-old infants, and adults, of both sexes, while they observed and performed grasping movements. The analysis of beta bursts relied on a method combining time-frequency decomposition and principal component analysis, in order to jointly examine burst rate and burst waveform shape (the "motifs") over the course of the trial. This approach makes it possible to distinguish burst types that heavily averaged power measures would obscure.
The results reveal systematic age-dependent changes in beta activity during action execution. Burst rate decreased during movement across all age groups, with the most pronounced decline observed in adults. Three principal components defined waveform-shape motifs that evolved over the trial: bursts whose shape approximated the median shape showed no modulation of their rate, whereas those that deviated from it were differentially modulated. In adults, the rate decrease of certain motifs occurred earlier during movement and was more strongly lateralized than in infants, suggesting a progressive, age-related refinement in the modulation of specific beta burst types. The authors note, however, that adults performed faster movements, which could partly account for the earlier onset observed.
The study has several acknowledged limitations: its cross-sectional rather than longitudinal design, the absence of anatomical or functional connectivity measures, the limited spatial precision of EEG, and the lack of quantification of arm and hand trajectories. From an applied standpoint, abnormal beta activity characterizes various developmental disorders and motor difficulties associated with early brain injury; examining burst shape could offer greater sensitivity for identifying and treating such individuals before behavioral symptoms emerge. More broadly, comparing beta activity in typical and atypical motor developmental trajectories would help disentangle the respective functional roles of the different burst types.