The identification of biomarkers for Parkinson’s disease is crucial for understanding its pathophysiology, as well as for development of effective treatments. Current efforts to optimise DBS treatment use the amplitude of beta band oscillations as a signal feature to be controlled in an adaptive/closed-loop setting (Little et al., 2013a). Given that beta band power can be both more readily picked up (due to the higher amplitude of beta activity over HFO) with ultra-low power amplifiers and more readily computed from recorded time series, we believe that it is potentially more suitable to use in adaptive DBS applications than beta–HFO PAC. However, our findings make important contributions to understanding the neuronal mechanisms that might lead to movement impairments. The robust link between low-beta power and HFO suggests that beta band oscillations constrain the pro-kinetic HFO to stereotypic activity patterns. Reducing low-beta power might indirectly lead to an improvement of symptoms by facilitating the initiation of movement-related activity.
