Related Experiment Video
Updated: Jul 27, 2025

Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation
Published on: July 16, 2014
Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain
Laura Alva1, Elena Bernasconi1, Flavie Torrecillos2
1Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
Objective:
Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal.
Methods:
STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated.
Results:
The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation).
Conclusions:
Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns.
Significance:
A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.
More Related Videos
07:14A Novel Approach to Assess Motor Outcome of Deep Brain Stimulation Effects in the Hemiparkinsonian Rat: Staircase and Cylinder Test
Published on: May 31, 2016
06:32Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
Published on: July 14, 2023