Computational study of rhythm propagation induced by TMS stimuli in different brain regions

Filippo Cona, Melissa Zavaglia, Marcello Massimini, Mario Rosanova, Mauro Ursino

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent data [1] suggest that different regions in the brain may exhibit distinct rhythms when perturbed by Transcranial Magnetic Stimulation (TMS). Knowledge of these rhythms may be of value to understand how the brain realizes its functions and to assess brain connectivity. In this work we implemented a neural mass model [2] of three interconnected cortical regions (Brodmann Area (BA) 19 (occipital lobe), BA 7 (parietal lobe) and BA 6 (frontal lobe)) to fit the impulse responses in three ROIs during an experiment of TMS stimulation on a single subject. First, the natural rhythm of each region was mimicked acting on the local parameters, which reproduce the number of synaptic contacts among neural populations. Then, rhythm propagation from one region to another was simulated (at three different intensities of TMS stimulation) acting on infra-region connectivity parameters. Results show that the model can reproduce the natural rhythms of the three regions, and most rhythm changes induced by stimulation of another region, by using quite a simple connectivity pattern. This pattern is scarcely affected by the stimulus intensity.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
Pages389-403
Number of pages15
Volume399
DOIs
Publication statusPublished - 2012

Publication series

NameStudies in Computational Intelligence
Volume399
ISSN (Print)1860949X

Keywords

  • Cortical rhythms
  • Neural mass models
  • Transcranial magnetic stimulation

ASJC Scopus subject areas

  • Artificial Intelligence

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    Cona, F., Zavaglia, M., Massimini, M., Rosanova, M., & Ursino, M. (2012). Computational study of rhythm propagation induced by TMS stimuli in different brain regions. In Studies in Computational Intelligence (Vol. 399, pp. 389-403). (Studies in Computational Intelligence; Vol. 399). https://doi.org/10.1007/978-3-642-27534-0_26