Evidence map›Paper›PMID 42226747›Full record

ArticleTranscranial magnetic stimulation (2024)2026

Stochastic Approximator of Motor Threshold (SAMT) for Transcranial Magnetic Stimulation: Online Software and Its Performance in Clinical Studies.

Boshuo Wang, Vedarsh U Shah, Lari M Koponen, Andrada D Neacsiu, Zafiris J Daskalakis, Paul B Fitzgerald, Lawrence G Appelbaum, Jessica Y Choi, Nimesha Gerlus, Yiru Li and 12 more

Abstract read
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In one paragraph

Article in Transcranial magnetic stimulation (2024), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

Boshuo WangDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.
Vedarsh U ShahDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.
Lari M KoponenInstitute for Gravitational Wave Astronomy, School of Physics and Astronomy, University of Birmingham, Birmingham, B15 2TT, UK.
Andrada D NeacsiuDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.
Zafiris J DaskalakisDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Paul B FitzgeraldSchool of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, ACT 2601, Australia.
Lawrence G AppelbaumDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Jessica Y ChoiDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.
Nimesha GerlusDepartment of Psychology and Neuroscience, Trinity College of Arts Sciences, Duke University, Durham, NC 27708, USA.
Yiru LiDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.
Itay HadasDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Yinming SunDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Mohsen PoorganjiDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Hadley DanielsDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Katie RodriguezDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
Efstathia Stephanie GotsisSchool of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, ACT 2601, Australia.
Neil W BaileyCognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Victoria 3125, Australia.
Jeydhurga RaveendranSchool of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, ACT 2601, Australia.
Shona K BrinleySchool of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, ACT 2601, Australia.
Alexander T GalloSchool of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, ACT 2601, Australia.
Stefan M GoetzDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.
Angel V PeterchevDepartment of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC 27710, USA.

Funding

Biology and Biophysics of the Cortical Response to Transcranial Magnetic StimulationR01NS117405 · NINDS · DUKE UNIVERSITY · PI PETERCHEV, ANGEL V, SOMMER, MARC A · 2020 to 2024
$3.3M
Neurostimulation Enhanced Cognitive Restructuring for Transdiagnostic Emotional Dysregulation: A Component AnalysisR01MH129302 · NIMH · DUKE UNIVERSITY · PI Andrada Delia Neacsiu · 2023 to 2026
$3.0M
MPS-TMS: Modular Pulse Synthesizer for Transcranial Magnetic Stimulation with Fully Adjustable Pulse Shape and SequenceTBDRF1MH124943 · NIMH · DUKE UNIVERSITY · PI PETERCHEV, ANGEL V · 2020 to 2020
$1.6M
Frequency and E-field Enhancement of iTBS for Depression (FREED)R61MH129471 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DASKALAKIS, ZAFIRIS J., FITZGERALD, PAUL · 2023 to 2024
$1.6M
NIMH NIH HHS R01 MH129302NIMH NIH HHS R61 MH129471NIMH NIH HHS RF1 MH124943NINDS NIH HHS R01 NS117405
6 · The paper itself

Abstract

Background: The motor threshold (MT) plays a central role in probing brain excitability and individualizing transcranial magnetic stimulation (TMS). Previously, we proposed stochastic approximation (SA) as a new method for determining TMS MT and demonstrated its excellent speed and accuracy via simulations. SA also has low computational requirements and is theoretically robust to potential model flaws. Objective: This project aimed to develop a practical SA thresholding method and assess its performance in clinical studies. Methods: The SA thresholding method was implemented as an online software application-SAMT (Stochastic Approximator of MT)-that incorporates features for warning against likely inaccurate MT estimates. Two clinical studies used SAMT and collected 365 small hand muscle MTs from 179 participants to date. SAMT's misestimation warning method marked MTs of 7 thresholding trials as likely inaccurate, and SAMT's performance in the remaining 358 trials was assessed by comparing the MT at each step to the threshold estimated by fitting a sigmoidal probability distribution to the complete muscle response data from the session using maximum likelihood estimation (MLE). Results: By the 25 Conclusions: We provide the TMS community with a new thresholding tool, SAMT. Combined with the prior simulation results, the experimental assessment presented here supports the practicality and accuracy of the SA thresholding method and the SAMT software.

Indexed as

clinical studymaximum likelihood estimationmotor thresholdstochastic approximationtranscranial magnetic stimulation

Identifiers

PMID42226747
PMCPMC13221086

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.