{"doi":"10.1101/2025.07.31.667968","title":"Single pointwise samples of electric field on a neuron model cannot predict activation threshold by brain stimulation","abstract":"BACKGROUND: Some computational models of neural activation by transcranial magnetic stimulation overestimate the electric field (E-field) threshold compared to in vivo measurements. A recent study proposed a statistical method to account for the influence of microscopic perturbations to the E-field. The method, however, relies on the unsubstantiated assumption that thresholds can be predicted by single pointwise samples of the E-field strength along neural cables. OBJECTIVE: We analyzed neural responses to E-field with microscopic perturbations and demonstrate via theoretical derivation and simulations that neural activation is not determined by pointwise E-field amplitude but rather by spatial integration of the E-field along the neural cable. Therefore, the influence of microscopic E-field perturbations is negligible due to the spatiotemporal filtering by the neural membrane and axoplasm. METHODS: We derive the axial and transmembrane currents in a neural cable for an imposed E-field with microscopic perturbations. We simulate neural activation thresholds of unmyelinated and myelinated axons in two stimulation scenarios and compare thresholds for E-field activation with and without perturbations. RESULTS: In the theoretical derivation, the perturbation terms average out to zero on larger spatial scales indicating that they do not influence neural activation thresholds. Simulated thresholds with the E-field spatial perturbations present had negligible differences (< 3.4%) compared to those without. CONCLUSION: Single point samples of the microscopic E-field on a neural cable cannot predict neural activation thresholds. Neural simulations should be used to determine any influence of the E-field spatial perturbations. The latter, however, are unlikely to account for the difference between experimental and simulated E-field thresholds.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":571563,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9544,"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":1211194,"name":"M. Hussain","orcid":"0000-0002-4833-7046","position":1,"is_corresponding":false},{"id":1388764,"name":"Torge Worbs","orcid":"0009-0004-0187-6108","position":2,"is_corresponding":false},{"id":240155,"name":"Axel Thielscher","orcid":"0000-0002-4752-5854","position":3,"is_corresponding":false},{"id":235899,"name":"Warren M. Grill","orcid":"0000-0001-5240-6588","position":4,"is_corresponding":false},{"id":106054,"name":"Angel V. Peterchev","orcid":"0000-0002-4385-065X","position":5,"is_corresponding":false},{"id":815600,"name":"Boshuo Wang","orcid":"0000-0003-1680-5957","position":0,"is_corresponding":true}],"reference_count":11,"raw_metadata":null,"created_at":"2026-07-19T02:57:15.755535Z","pmid":"40766622","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":[]}