{"doi":"10.1016/j.brs.2021.09.004","title":"Multi-scale modeling toolbox for single neuron and subcellular activity under Transcranial Magnetic Stimulation","abstract":"BACKGROUND: Transcranial Magnetic Stimulation (TMS) is a widely used non-invasive brain stimulation method. However, its mechanism of action and the neural response to TMS are still poorly understood. Multi-scale modeling can complement experimental research to study the subcellular neural effects of TMS. At the macroscopic level, sophisticated numerical models exist to estimate the induced electric fields. However, multi-scale computational modeling approaches to predict TMS cellular and subcellular responses, crucial to understanding TMS plasticity inducing protocols, are not available so far. OBJECTIVE: We develop an open-source multi-scale toolbox Neuron Modeling for TMS (NeMo-TMS) to address this problem. METHODS: NeMo-TMS generates accurate neuron models from morphological reconstructions, couples them to the external electric fields induced by TMS, and simulates the cellular and subcellular responses of single-pulse and repetitive TMS. RESULTS: We provide examples showing some of the capabilities of the toolbox. CONCLUSION: NeMo-TMS toolbox allows researchers a previously not available level of detail and precision in realistically modeling the physical and physiological effects of TMS.","journal":"Brain stimulation","year":2021,"id":157283,"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":51,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9443,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":560633,"name":"Nicholas Hananeia","orcid":"0000-0002-2813-708X","position":1,"is_corresponding":false},{"id":560634,"name":"James Rosado","orcid":"0000-0003-1542-3711","position":2,"is_corresponding":false},{"id":663723,"name":"Harry Tran","orcid":"0000-0003-2847-151X","position":3,"is_corresponding":false},{"id":560635,"name":"Christos Galanis","orcid":"0000-0002-6469-7201","position":4,"is_corresponding":false},{"id":482460,"name":"Andreas Vlachos","orcid":"0000-0002-2646-3770","position":5,"is_corresponding":false},{"id":560636,"name":"Peter Jedlička","orcid":"0000-0001-6571-5742","position":6,"is_corresponding":false},{"id":560637,"name":"Gillian Queisser","orcid":"0000-0003-4691-5276","position":7,"is_corresponding":false},{"id":240702,"name":"Alexander Opitz","orcid":"0000-0002-4851-1243","position":8,"is_corresponding":false},{"id":314174,"name":"Sina Shirinpour","orcid":"0000-0002-8267-6527","position":0,"is_corresponding":true}],"reference_count":90,"raw_metadata":null,"created_at":"2026-07-18T23:44:17.471040Z","pmid":"34562659","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":[]}