title: A neuronal network model for simulating the effects of repetitive transcranial magnetic stimulation on local field potential power spectra.
abstract: Repetitive transcranial magnetic stimulation (rTMS) holds promise as a non-invasive therapy for the treatment of neurological disorders such as depression, schizophrenia, tinnitus, and epilepsy. Complex interdependencies between stimulus duration, frequency and intensity obscure the exact effects of rTMS stimulation on neural activity in the cortex, making evaluation of and comparison between rTMS studies difficult. To explain the influence of rTMS on neural activity (e.g. in the motor cortex), we use a neuronal network model. The results demonstrate that the model adequately explains experimentally observed short term effects of rTMS on the band power in common frequency bands used in electroencephalography (EEG). We show that the equivalent local field potential (eLFP) band power depends on stimulation intensity rather than on stimulation frequency. Additionally, our model resolves contradictions in experiments.
authors.affiliation: Department of Computer and Information Science, University of Konstanz, Konstanz, Germany. alina.bey@uni-konstanz.de
authors.forename: Alina
authors.initials: A
authors.lastname: Bey
authors.forename: Stefan
authors.initials: S
authors.lastname: Leue
authors.forename: Christian
authors.initials: C
authors.lastname: Wienbruch
mesh_terms: D001674:Bioelectric Energy Sources; D003198:Computer Simulation; D004569:Electroencephalography; D006801:Humans; D009044:Motor Cortex / Q000473:pathology / Q000503:physiopathology; D009415:Nerve Net; D009422:Nervous System Diseases / Q000473:pathology / Q000503:physiopathology / Q000628:therapy; D016571:Neural Networks, Computer; D013569:Synapses; D050781:Transcranial Magnetic Stimulation