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Role of Computational Modeling for Dose Determination

  • Ricardo Salvador
  • Dennis Q. Truong
  • Marom Bikson
  • Alexander Opitz
  • Jacek Dmochowski
  • Pedro C. MirandaEmail author
Chapter

Abstract

This chapter provides a broad introduction to computational models that inform and optimize tDCS for both clinical researchers and translational engineers. The first section introduces the rationale for modeling; the next two sections address technical features of modeling relevant to engineers (and to clinicians interested in the limitations of modeling); the following three sections address the use of modeling in clinical practice, and the final section illustrates the application of models in dose design through case studies. Computational “forward” models predict the flow of current throughout the head during tDCS, as with other brain stimulation techniques. Because the relationship between stimulation dose (defined as those electrode and waveform parameters controlled by the operator) and resulting brain current flow is complex and non-intuitive, computational forward models are essential to the rational design of stimulation protocols. Though model validation efforts are ongoing, these models already represent a standard tool to predict brain current flow and optimize tDCS dose, and so inform clinical practice and behavior research. Yet despite increased interest in tDCS modeling, as supported by the number of tDCS publications about or including a modeling component, access to modeling tools by clinicians remains highly limited. Ironically, much of the effort to enhance the relevance of modeling through increased sophistication (complexity) in fact hinders both reproduction and dissemination. This chapter therefore addresses not only the state-of-the-art in modeling techniques, but also how models can be immediately leveraged by researchers and clinicians.

Keywords

Computational model Finite element method Optimization Targeting 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Ricardo Salvador
    • 1
  • Dennis Q. Truong
    • 2
  • Marom Bikson
    • 3
  • Alexander Opitz
    • 4
  • Jacek Dmochowski
    • 5
  • Pedro C. Miranda
    • 6
    Email author
  1. 1.NeuroelectricsBarcelonaSpain
  2. 2.Department of Biomedical EngineeringThe City College of the City University of New YorkNew YorkUSA
  3. 3.Department of Biomedical EngineeringThe City College of New YorkNew YorkUSA
  4. 4.Department of Biomedical Engineering, University of MinnesotaMinneapolisUSA
  5. 5.Neural Engineering Laboratory, Department of Biomedical Engineering, Grove School of EngineeringThe City College of the City University of New YorkNew YorkUSA
  6. 6.Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de LisboaLisbonPortugal

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