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Adaptive Recruitment Curve Analysis Using Bayesian Modeling

12. august 2026 oppdatert av: 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.

Studieoversikt

Status

Rekruttering

Forhold

Intervensjon / Behandling

Detaljert 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.

Studietype

Intervensjonell

Registrering (Antatt)

14

Fase

  • Ikke aktuelt

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Studiesteder

  • Forente stater
    • New York
      • New York, New York, Forente stater, 10032
        • Rekruttering
        • Columbia University Irving Medical Center
        • Ta kontakt med:
        • Hovedetterforsker:
          • James R McIntosh, PhD

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Voksen
  • Eldre voksen

Tar imot friske 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

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Grunnvitenskap
  • Tildeling: N/A
  • Intervensjonsmodell: Enkeltgruppeoppdrag
  • Masking: Ingen (Open Label)

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Eksperimentell: 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.
Annen: Algorithm: Uniform Sampling
Standard uniform distribution sampling used as a baseline comparison.
Annen: ML-PEST
Algorithm: Adaptive threshold hunting using the Parameter Estimation by Sequential Testing (PEST) algorithm.
Enhet: MagPro X100 Transcranial Magnetic Stimulation
The proposed algorithms will deliver stimulation by using this magnetic stimulation methodology.
Enhet: Digitimer DS8R Transcutaneous Electrical stimulation
The proposed algorithms will deliver stimulation by using this electrical stimulation methodology.
Annen: Algorithm: hbMEP-adaptive algorithm (version 1)
An active sampling algorithm for recruitment curve estimation.
Annen: Algorithm: hbMEP-adaptive algorithm (version 2)
An alternative active sampling algorithm for recruitment curve estimation.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
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
Tiltaksbeskrivelse
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.

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

Columbia University

Samarbeidspartnere

National Institute of Neurological Disorders and Stroke (NINDS)

Etterforskere

  • Hovedetterforsker: James R McIntosh, PhD, Columbia University

Publikasjoner og nyttige lenker

Den som er ansvarlig for å legge inn informasjon om studien leverer frivillig disse publikasjonene. Disse kan handle om alt relatert til studiet.

Generelle publikasjoner

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Antatt)

1. september 2026

Primær fullføring (Antatt)

31. mars 2027

Studiet fullført (Antatt)

31. mars 2027

Datoer for studieregistrering

Først innsendt

20. april 2026

Først innsendt som oppfylte QC-kriteriene

24. april 2026

Først lagt ut (Faktiske)

1. mai 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

14. august 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

12. august 2026

Sist bekreftet

1. august 2026

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Andre studie-ID-numre

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

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (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).

Tilgangskriterier for IPD-deling

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

IPD-deling Støtteinformasjonstype

  • ANALYTIC_CODE

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Ja

produkt produsert i og eksportert fra USA

Nei

Denne informasjonen ble hentet direkte fra nettstedet clinicaltrials.gov uten noen endringer. Hvis du har noen forespørsler om å endre, fjerne eller oppdatere studiedetaljene dine, vennligst kontakt register@clinicaltrials.gov. Så snart en endring er implementert på clinicaltrials.gov, vil denne også bli oppdatert automatisk på nettstedet vårt. .

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