Adaptive mapping of stimulation–response curves with Bayesian modeling
Enhancing Speed and Accuracy of Motor Evoked Potential Recruitment Curve Analysis Using Hierarchical Bayesian Modeling
This project tests a real-time Bayesian method to map how magnetic or electrical stimulation affects muscle responses in healthy adults using fewer measurements.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 10 (estimated) |
| Ages | 18 Years to 90 Years |
| Sex | All |
| Sponsor | Columbia University Academic / other |
| Locations | 1 site (New York, New York) |
| Trial ID | NCT07561372 on ClinicalTrials.gov |
What this trial studies
Researchers will compare several computer-guided sampling algorithms (uniform sampling, expected information gain, focused EIG/variance-reduction, ML-PEST) while delivering transcranial magnetic or spinal stimulation and recording muscle responses. A hierarchical Bayesian model will run in real time to choose the next stimulation intensity to estimate the full neural recruitment curve or specific parameters like motor threshold with fewer samples. Experiments will use the MagPro X100 TMS device in healthy adult participants and benchmark the proposed approach against existing methods. Primary outcomes include accuracy of curve estimates, number of stimuli required, and overall experimental efficiency.
Who should consider this trial
Good fit: Healthy adults without neurological disorders, history of seizures, autonomic dysfunction, metal implants, prior neurosurgery, or use of seizure‑threshold lowering medications.
Not a fit: People with neurological conditions, a seizure history, autonomic dysfunction, metal implants, prior neurosurgery, or on seizure‑risk medications are excluded and will not directly benefit from participation.
Why it matters
Potential benefit: If successful, this method could reduce the number of stimulations and time needed to characterize neural recruitment, lowering participant burden and speeding research that informs therapies.
How similar studies have performed: Hierarchical Bayesian and adaptive sampling approaches have shown promise in simulations and some pilot experiments, but real-time application in human neurostimulation across multiple algorithms is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria \- Healthy adults Exclusion Criteria * Presence of any neurological disorder * History of seizures * History of autonomic dysfunction * Current use of seizure-threshold lowering medications * Presence of metal implants * History of prior neurosurgical interventions
Where this trial is running
New York, New York
- Columbia University Irving Medical Center — New York, New York, United States (Recruiting)
Study contacts
- Principal investigator: James R McIntosh, PhD — Columbia University
- Study coordinator: James R McIntosh, PhD
- Email: jrm2263@cumc.columbia.edu
- Phone: +19294352335
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.