Adaptive deep brain stimulation (aDBS) using a brain-computer interface (BCI) to control stimulation based on beta oscillations in local field potentials (LFPs) showed improved efficacy and efficiency in patients with advanced Parkinson's disease (PD). The study tested aDBS in 8 PD patients, comparing it with conventional continuous DBS (cDBS) and random intermittent stimulation. Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% and 27% better than cDBS, respectively. aDBS also reduced stimulation time by 56% and energy use, and was more effective than no stimulation and random intermittent stimulation. The BCI system used beta activity in the LFP recorded from the stimulation electrode to trigger stimulation, which was more efficient and effective than conventional continuous neuromodulation. The study demonstrated that aDBS could reduce stimulation time and energy use while improving motor function. The results suggest that aDBS could be a more efficient and effective treatment for PD, potentially extending battery life and reducing side effects. The study also showed that aDBS could lead to adaptive effects, reducing beta bursts over time, which may indicate a long-term benefit. The findings support the potential of aDBS as a promising treatment for PD and other neurological conditions. The study was funded by the Wellcome Trust and other organizations, and the authors have disclosed potential conflicts of interest. The study highlights the importance of feedback control in DBS and the potential for further improvements in aDBS technology.Adaptive deep brain stimulation (aDBS) using a brain-computer interface (BCI) to control stimulation based on beta oscillations in local field potentials (LFPs) showed improved efficacy and efficiency in patients with advanced Parkinson's disease (PD). The study tested aDBS in 8 PD patients, comparing it with conventional continuous DBS (cDBS) and random intermittent stimulation. Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% and 27% better than cDBS, respectively. aDBS also reduced stimulation time by 56% and energy use, and was more effective than no stimulation and random intermittent stimulation. The BCI system used beta activity in the LFP recorded from the stimulation electrode to trigger stimulation, which was more efficient and effective than conventional continuous neuromodulation. The study demonstrated that aDBS could reduce stimulation time and energy use while improving motor function. The results suggest that aDBS could be a more efficient and effective treatment for PD, potentially extending battery life and reducing side effects. The study also showed that aDBS could lead to adaptive effects, reducing beta bursts over time, which may indicate a long-term benefit. The findings support the potential of aDBS as a promising treatment for PD and other neurological conditions. The study was funded by the Wellcome Trust and other organizations, and the authors have disclosed potential conflicts of interest. The study highlights the importance of feedback control in DBS and the potential for further improvements in aDBS technology.