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Adaptive Recruitment Curve Analysis Using Bayesian Modeling

Columbia University · with National Institute of Neurological Disorders and Stroke (NINDS) · NCT07561372

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Opens the official ClinicalTrials.gov record, with the study team’s contacts. Bored Studies doesn’t enroll anyone.

Key facts

Compensation
Not posted. Ask the study team before screening.
Who can join
Ages 18–90 · All sexes
Healthy volunteers
Accepted
Study type
Interventional · Not applicable
Target enrollment
14
US sites recruiting
1
Study start
September 1, 2026
Record last updated
August 14, 2026

Status re-checked against ClinicalTrials.gov within the last 12 hours.

What the study is about

The purpose of this study is to better understand how electrical or magnetic stimulation affect the nervous system by optimizing the way researchers measure muscle responses. The relationship between stimulation intensity and muscle response is described by "neural recruitment curves," which are critical for monitoring the state of the nervous system during therapies like transcranial magnetic stimulation (TMS) and spinal cord stimulation (SCS).

This study tests a new, real-time computational approach based on our previously developed methods (Hierarchical Bayesian models) to estimate these recruitment curves more efficiently. The primary goal is to use this model to dynamically guide the experiment, automatically selecting the optimal stimulation intensities to test.

The investigators hypothesize that this optimized approach will accurately estimate the entire recruitment curve, or specific targets components of it like the motor threshold, using significantly fewer samples than standard methods. By reducing the number of measurements required, this approach aims to decrease experimental time and minimize participant burden, making future TMS and SCS therapies and experiments more feasible and efficient.

Being studied: Algorithm: Uniform Sampling; Algorithm: hbMEP-adaptive algorithm (version 1); Algorithm: hbMEP-adaptive algorithm (version 2); ML-PEST; MagPro X100 Transcranial Magnetic Stimulation; Digitimer DS8R Transcutaneous Electrical stimulation

Conditions: Modeling of Recruitment Curves

Eligibility criteria

Copied from the official record. The study team makes the final decision at screening.

Show full criteria

Inclusion Criteria

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

Exclusion Criteria

  • 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.

Recruiting US locations

  • Columbia University Irving Medical Center

    New York, NY 10032

    Site contact: James R McIntosh, PhD · 9294352335 · jrm2263@cumc.columbia.edu

Study contacts (from the official record)

  • James R McIntosh, PhD · +19294352335 · jrm2263@cumc.columbia.edu
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Adaptive Recruitment Curve Analysis Using Bayesian Modeling (NCT07561372) | Bored Studies