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Adaptive Recruitment Curve Analysis Using Bayesian Modeling

This study aims to improve how researchers measure muscle responses to brain stimulation, like transcranial magnetic stimulation (TMS). Researchers are testing new computer algorithms, including "hbMEP-adaptive algorithm (version 1)" and "hbMEP-adaptive algorithm (version 2)," along with "ML-PEST," to find the best way to understand how stimulation intensity affects muscle response. This understanding, called a "neural recruitment curve," is important for monitoring the nervous system during treatments. The study will compare these new algorithms to a standard method called "Uniform Sampling" using the "MagPro X100 Transcranial Magnetic Stimulation" device. They are looking for healthy adults between 18 and 90 years old who do not have neurological disorders, a history of seizures, or metal implants. The main goal is to see how accurately these different methods can estimate the muscle response curve.

Study design
This interventional study plans to enroll 10 participants. It will compare several different algorithms for measuring muscle responses to stimulation.
What's involved
Participants will have one study visit, which is expected to last about 1 hour.
Compensation
Not stated in the trial record.
Follow-up
Not specified.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07561372

Adaptive Recruitment Curve Analysis Using Bayesian Modeling

Recruiting
NAAges 18–90InterventionalBasic science
Columbia University
~14 participants
Updated 2026-08-14 on ClinicalTrials.gov
What's tested:Algorithm: Uniform SamplingAlgorithm: hbMEP-adaptive algorithm (version 1)Algorithm: hbMEP-adaptive algorithm (version 2)ML-PESTMagPro X100 Transcranial Magnetic StimulationDigitimer DS8R Transcutaneous Electrical stimulation

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Number of stimuli to reach a pre-defined threshold error
Measured over Through completion of the study visit, 2-4 hours.
+1 more outcome measured

Conditions

Modeling of Recruitment Curves

Explore related trials

Healthy

Where it's being run

1 sites across 1 states
New York1

Study leadership

  • James R McIntosh, PhD · PRINCIPAL_INVESTIGATOR · Columbia University

Who to contact

James R McIntosh, PhD
[email protected]
+19294352335
Email the study team

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Eligibility criteria

Inclusion

Healthy adult volunteers aged 18 years and older.
Able to understand study procedures and provide written informed consent.

Exclusion

1\. History of adverse reaction to Transcranial Magnetic Stimulation (TMS) or non-invasive neurostimulation.
2\. History of seizures, epilepsy, or family history of epilepsy.
3\. History of stroke, brain injury, or illness causing brain injury.
4\. History of head injury or neurosurgery.
5\. History of neurological diseases, or central nervous system lesions.
6\. Presence of metallic implants or foreign bodies in the head (outside of dental work/fillings).
7\. Presence of implanted electronic or medical devices (e.g., cardiac pacemakers, medical pumps, implanted stimulators).
8\. Current pregnancy or possibility of pregnancy.
9\. Currently taking medications that alter cortical excitability or lower seizure threshold.

What this trial measures

  • Number of stimuli to reach a pre-defined threshold errorThrough completion of the study visit, 2-4 hours.

    Number of stimuli required for the compared methods to reach a pre-defined error threshold relative to the ground truth, computed from recruitment curves fitted after sampling using aggregated data.

  • Number of stimuli to reach a pre-defined predictive curve errorThrough completion of the study visit, 2-4 hours.

    Number of stimuli required for the compared methods to reach a pre-defined error threshold relative to the ground truth, computed from recruitment curves fitted after sampling using aggregated data.