{"doi":"10.1016/j.brs.2025.05.065","title":"Stochastic Approximator of Motor Threshold for Transcranial Magnetic Stimulation (SAMT): Performance in Clinical Trials","abstract":"Stochastic approximation (SA) is a new method for determining the motor threshold (MT) of transcranial magnetic stimulation (TMS), with excellent performance demonstrated via simulations.We implemented the SA method together with features for detection of inaccurate estimation in an online app called SAMT and validated its performance in clinical studies.MTs of finger muscles were collected with SAMT and their accuracy was assessed by comparison to the MT estimated with a sigmoidal response model.SAMT obtained MTs with high accuracy by 25 pulses, with errors less than 1.1% maximum stimulator output (absolute) or 3.0% (relative) and within the model's confidence intervals.This supports the practicality and accuracy of the SA thresholding method and the SAMT app for TMS in human subjects.","journal":"Brain stimulation","year":2025,"id":534348,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.958,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1417457,"name":"Vedarsh Shah","orcid":null,"position":1,"is_corresponding":false},{"id":356378,"name":"Lari M. Koponen","orcid":"0000-0002-8054-2699","position":2,"is_corresponding":false},{"id":1413583,"name":"Stefan Goetz","orcid":"0000-0003-1520-9352","position":3,"is_corresponding":false},{"id":808344,"name":"Andrada D. Neacsiu","orcid":"0000-0002-9779-7276","position":4,"is_corresponding":false},{"id":1260717,"name":"Jessica Y. Choi","orcid":null,"position":5,"is_corresponding":false},{"id":294684,"name":"Zafiris J. Daskalakis","orcid":"0000-0001-9502-0538","position":6,"is_corresponding":false},{"id":230805,"name":"Paul B. Fitzgerald","orcid":"0000-0003-4217-8096","position":7,"is_corresponding":false},{"id":389866,"name":"Lawrence G. Appelbaum","orcid":"0000-0002-3184-6725","position":8,"is_corresponding":false},{"id":720579,"name":"Itay Hadas","orcid":"0000-0001-7518-1182","position":9,"is_corresponding":false},{"id":1399967,"name":"H. E. Daniels","orcid":null,"position":10,"is_corresponding":false},{"id":1417458,"name":"Katie Rodrigues","orcid":null,"position":11,"is_corresponding":false},{"id":1416959,"name":"Efstathia Stephanie Gotsis","orcid":"0000-0002-9652-7266","position":12,"is_corresponding":false},{"id":304895,"name":"Neil W. Bailey","orcid":"0000-0002-8483-1068","position":13,"is_corresponding":false},{"id":1417459,"name":"Jeydhurga Raveendran","orcid":null,"position":14,"is_corresponding":false},{"id":1410192,"name":"Alexander T. Gallo","orcid":"0000-0001-8647-4968","position":15,"is_corresponding":false},{"id":1417460,"name":"Shona Brinley","orcid":null,"position":16,"is_corresponding":false},{"id":106054,"name":"Angel V. Peterchev","orcid":"0000-0002-4385-065X","position":17,"is_corresponding":false},{"id":815600,"name":"Boshuo Wang","orcid":"0000-0003-1680-5957","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:51:47.434742Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}