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Adaptive Recruitment Curve Analysis Using Bayesian Modeling

12. august 2026 opdateret af: James McIntosh, Columbia University

Enhancing Speed and Accuracy of Motor Evoked Potential Recruitment Curve Analysis Using Hierarchical Bayesian Modeling

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.

Studieoversigt

Status

Rekruttering

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

Transcranial magnetic stimulation and other types of neurostimulation play a crucial role in advancing the understanding and manipulation of neural activity for both research and therapeutic purposes. The proposed approach to sampling recruitment curves in real-time promises to significantly improve the efficiency and precision of experiments that use electrical or electromagnetic stimulation techniques, reducing the experimental burden for participants as well as experimenters. By enhancing experimental efficiency in multiple experimental settings and techniques, this research directly contributes to accelerating the translation of scientific discoveries into clinical applications. This study will benchmark the relative performance of different methods against each other by testing existing and proposed algorithms using neurostimulation in people, and comparing the resultant estimates in recruitment curve parameters, and the number of samples required to reach predefined tolerances on these parameters.

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

14

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Studiesteder

  • Forenede Stater
    • New York
      • New York, New York, Forenede Stater, 10032
        • Rekruttering
        • Columbia University Irving Medical Center
        • Kontakt:
        • Ledende efterforsker:
          • James R McIntosh, PhD

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ja

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Grundvidenskab
  • Tildeling: N/A
  • Interventionel model: Enkelt gruppeopgave
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: Test of developed methods
Participants undergo distinct experiments within a single session to compare different neurostimulation sampling algorithms. Each experiment involves recruitment curve sampling with different methods (e.g., Uniform, Expected Information Gain) to evaluate the accuracy and efficiency of motor threshold.
Andet: Algorithm: Uniform Sampling
Standard uniform distribution sampling used as a baseline comparison.
Andet: ML-PEST
Algorithm: Adaptive threshold hunting using the Parameter Estimation by Sequential Testing (PEST) algorithm.
Enhed: MagPro X100 Transcranial Magnetic Stimulation
The proposed algorithms will deliver stimulation by using this magnetic stimulation methodology.
Enhed: Digitimer DS8R Transcutaneous Electrical stimulation
The proposed algorithms will deliver stimulation by using this electrical stimulation methodology.
Andet: Algorithm: hbMEP-adaptive algorithm (version 1)
An active sampling algorithm for recruitment curve estimation.
Andet: Algorithm: hbMEP-adaptive algorithm (version 2)
An alternative active sampling algorithm for recruitment curve estimation.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Number of stimuli to reach a pre-defined threshold error
Tidsramme: Through 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.
Through completion of the study visit, 2-4 hours.
Number of stimuli to reach a pre-defined predictive curve error
Tidsramme: Through 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.
Through completion of the study visit, 2-4 hours.

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Mean absolute error in a given parameter (e.g. threshold, predictive curve, slope) for a given number of stimuli
Tidsramme: Through completion of the study visit, 2-4 hours.
The error of the methods under comparison, with the ground truth computed from recruitment curves fitted subsequent to sampling using aggregated data.
Through completion of the study visit, 2-4 hours.

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Columbia University

Samarbejdspartnere

National Institute of Neurological Disorders and Stroke (NINDS)

Efterforskere

  • Ledende efterforsker: James R McIntosh, PhD, Columbia University

Publikationer og nyttige links

Den person, der er ansvarlig for at indtaste oplysninger om undersøgelsen, leverer frivilligt disse publikationer. Disse kan handle om alt relateret til undersøgelsen.

Generelle publikationer

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Anslået)

1. september 2026

Primær færdiggørelse (Anslået)

31. marts 2027

Studieafslutning (Anslået)

31. marts 2027

Datoer for studieregistrering

Først indsendt

20. april 2026

Først indsendt, der opfyldte QC-kriterier

24. april 2026

Først opslået (Faktiske)

1. maj 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

14. august 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

12. august 2026

Sidst verificeret

1. august 2026

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Andre undersøgelses-id-numre

  • AAAV6853
  • 1R03NS141040-01A1 (U.S. NIH-bevilling/kontrakt)

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

JA

IPD-planbeskrivelse

De-identified MEP data and analysis code and algorithms.

IPD-delingstidsramme

Together with publication at the end of this study (04/2027).

IPD-delingsadgangskriterier

Open access repository (e.g. Zenodo and Github).

IPD-deling Understøttende informationstype

  • ANALYTIC_CODE

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

Studerer et amerikansk FDA-reguleret lægemiddelprodukt

Ingen

Studerer et amerikansk FDA-reguleret enhedsprodukt

Ja

produkt fremstillet i og eksporteret fra U.S.A.

Ingen

Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

Abonner