TY - JOUR
T1 - Phasic Burst Stimulation
T2 - A Closed-Loop Approach to Tuning Deep Brain Stimulation Parameters for Parkinson’s Disease
AU - Holt, Abbey B.
AU - Wilson, Dan
AU - Shinn, Max
AU - Moehlis, Jeff
AU - Netoff, Theoden I.
N1 - Publisher Copyright:
© 2016 Holt et al.
PY - 2016/7
Y1 - 2016/7
N2 - We propose a novel, closed-loop approach to tuning deep brain stimulation (DBS) for Parkinson’s disease (PD). The approach, termed Phasic Burst Stimulation (PhaBS), applies a burst of stimulus pulses over a range of phases predicted to disrupt pathological oscillations seen in PD. Stimulation parameters are optimized based on phase response curves (PRCs), which would be measured from each patient. This approach is tested in a computational model of PD with an emergent population oscillation. We show that the stimulus phase can be optimized using the PRC, and that PhaBS is more effective at suppressing the pathological oscillation than a single phasic stimulus pulse. PhaBS provides a closed-loop approach to DBS that can be optimized for each patient.
AB - We propose a novel, closed-loop approach to tuning deep brain stimulation (DBS) for Parkinson’s disease (PD). The approach, termed Phasic Burst Stimulation (PhaBS), applies a burst of stimulus pulses over a range of phases predicted to disrupt pathological oscillations seen in PD. Stimulation parameters are optimized based on phase response curves (PRCs), which would be measured from each patient. This approach is tested in a computational model of PD with an emergent population oscillation. We show that the stimulus phase can be optimized using the PRC, and that PhaBS is more effective at suppressing the pathological oscillation than a single phasic stimulus pulse. PhaBS provides a closed-loop approach to DBS that can be optimized for each patient.
UR - http://www.scopus.com/inward/record.url?scp=84979985593&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979985593&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1005011
DO - 10.1371/journal.pcbi.1005011
M3 - Article
C2 - 27415832
AN - SCOPUS:84979985593
SN - 1553-734X
VL - 12
JO - PLoS computational biology
JF - PLoS computational biology
IS - 7
M1 - e1005011
ER -