{"doi":"10.1007/978-3-031-15451-5_4","title":"Experimental Verification of a Computational Real-Time Neuronavigation System for Multichannel Transcranial Magnetic Stimulation","abstract":"Abstract Multichannel Transcranial Magnetic Stimulation (mTMS) provides the capability of stimulating multiple cortical areas simultaneously or in rapid succession by electronic shifting of the E-field hotspots. However, in order to target the desired brain region with intended intensity, the intracranial E-field distribution for all coil elements needs to be determined and subsequently combined to electronically synthesize a ‘hot spot’. Here, we assessed the performance of a computational TMS navigation system that was used to track the position of a 2×3-axis TMS coil array with respect to subject’s head and was integrated with a real-time high-resolution E-field calculation engine to predict the activated cortical regions as the array is moved around the subject’s head. For fast evaluation of the E-fields with high-resolution head models, we employed our previously proposed Magnetic Stimulation Profile (MSP) approach. Our preliminary tests demonstrated the capability of this system to precisely calculate and render E-fields with a frame rate of 6 Hz (6 frames/second). Furthermore, we utilized two z-elements from the 3-axis coils to form a figure of eight coil type and utilized it for suprathreshold stimulation of the hand first dorsal interosseous (FDI) muscle on a healthy human. The recorded motor evoked potentials (MEPs) showed clear activation of the FDI muscle comparable to the activation elicited by a commercial TMS coil. The estimated cortical E-field distributions showed a good agreement between the commercial TMS coil and the two z-elements of the 2×3-axis array.","journal":null,"year":2022,"id":280017,"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":0.9602,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":312667,"name":"Lucia Navarro de Lara","orcid":"0000-0002-6793-4831","position":1,"is_corresponding":false},{"id":510032,"name":"Qinglei Meng","orcid":"0000-0002-5173-3007","position":2,"is_corresponding":false},{"id":313385,"name":"Sergey N. Makarov","orcid":null,"position":3,"is_corresponding":false},{"id":954065,"name":"Işıl Uluç","orcid":"0000-0001-9515-486X","position":4,"is_corresponding":false},{"id":250071,"name":"Jyrki Ahveninen","orcid":"0000-0001-9058-8669","position":5,"is_corresponding":false},{"id":312672,"name":"Tommi Raij","orcid":"0000-0001-7439-7491","position":6,"is_corresponding":false},{"id":297460,"name":"Aapo Nummenmaa","orcid":"0000-0002-6452-7958","position":7,"is_corresponding":false},{"id":312668,"name":"Mohammad Daneshzand","orcid":"0000-0002-4237-5535","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-19T00:28:59.341002Z","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":[]}