Particle Swarm Optimization for Positioning the Coil of Transcranial Magnetic Stimulation.

The distribution of the induced electric field (E-field) during transcranial magnetic stimulation (TMS) depends on the individual anatomical structure of the brain as well as coil positioning. Inappropriate stimulation may degrade the efficacy of TMS or even induce adverse effects. Therefore, optimi...

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Publicado en:BioMed Research International pp. 1 - 13
Autores principales: Li, Congsheng, Liu, Chang, Yang, Lei, He, Luyang, Wu, Tongning
Formato: diagnostic images equations & formulas pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell 11/3/2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 11/3/2019
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2019/9461018
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        atl: Particle Swarm Optimization for Positioning the Coil of Transcranial Magnetic Stimulation.
      aug:
        au:
          Li, Congsheng
          Liu, Chang
          Yang, Lei
          He, Luyang
          Wu, Tongning
        affil: China Academy of Information and Communications Technology, Beijing, China
      sug:
        subj:
          Transcranial Magnetic Stimulation
          Particle Swarm Optimization
          Head Anatomy and Histology
          Neural Networks (Computer)
          Human
          Models, Anatomic
      ab: The distribution of the induced electric field (E-field) during transcranial magnetic stimulation (TMS) depends on the individual anatomical structure of the brain as well as coil positioning. Inappropriate stimulation may degrade the efficacy of TMS or even induce adverse effects. Therefore, optimizing the E-field according to individual anatomy and clinical need has become a research focus. In this paper, particle swarm optimization (PSO) was applied for the first time to the positioning of TMS coils with anatomical head models. We discuss the parameters of the PSO algorithm, which were optimized to achieve a reasonable convergence time suitable for in-time treatment planning. The optimizer improved the distribution of the induced E-field strength at the dedicated cortical region, with a mean value of 48.31% compared with that from the conventional treatment position. The optimization terminated after 4–11 iterations for 13 head models. The applicability and performance of the optimizer for a large population are discussed in terms of cortical complexity. This study could benefit not only clinics but also research on brain modulation.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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