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Updated: Mar 2, 2026

Author Spotlight: Insights into Remotely Supervised Neuromodulation Procedure for Phantom Limb Pain
Published on: March 1, 2024
Cyclization of Motor Cortex Stimulation for Neuropathic Pain: A Prospective, Randomized, Blinded Trial
Zurab Ivanishvili1, Anujan Poologaindran1, Christopher R Honey1
1Department of Surgery, Division of Neurosurgery, The University of British Columbia, Vancouver, Canada.
Objectives:
Programming guidelines for motor cortex stimulation (MCS) in neuropathic pain requires further investigation. After optimizing voltage as a percentage of motor threshold, we evaluated the effect of cyclizing time of stimulation on pain relief for chronic neuropathic pain.
Methods:
Six patients were enrolled into this trial. In a prospective, randomized, double-blinded manner, patients were programmed to receive stimulation 100, 83.3, 66.7, or 50% of the time in 30-min intervals. Outcomes were assessed after 14 days on each setting with a visual analogue scale (VAS) for pain and the SF36 quality of life questionnaire.
Results:
There was no significant difference (p > 0.05) between the different cyclized settings as measured by the VAS, MGPQ, or SF36 in our cohort. There were two distinct subgroups: responders (n = 4) and nonresponders (n = 2) to cyclization. Responders continued to have pain relief when stimulation was reduced to only 50% of the time (15 min ON/15 min off). Interestingly, this group subjectively preferred the 50% stimulation timing compared to 100%. Nonresponders could not tolerate cyclizing because of increased pain.
Conclusions:
In this small cohort, cyclization of MCS settings revealed two distinct subgroups: responders and nonresponders. Responders tolerated stimulation in all settings and 50% stimulation (15 min ON/15 min off) was their subjectively preferred setting. Cyclization in responders will prolong battery life and delay the need for INS replacement and may offer improved pain relief. Building from our previous work, we recommend clinicians consider following the Vancouver MCS programming algorithm presented in this manuscript.

