TMS motor thresholds correlate with TDCS electric field strengths in hand motor area

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Details

Original languageEnglish
Article number426
Number of pages10
JournalFrontiers in Neuroscience
Volume12
Issue numberJUN
Publication statusPublished - 25 Jun 2018
MoE publication typeA1 Journal article-refereed

Researchers

Research units

  • Fujita Health University
  • Nagoya Institute of Technology
  • Hamamatsu University School of Medicine
  • National Institute for Physiological Sciences

Abstract

Transcranial direct current stimulation (TDCS) modulates cortical activity and influences motor and cognitive functions in both healthy and clinical populations. However, there is large inter-individual variability in the responses to TDCS. Computational studies have suggested that inter-individual differences in cranial and brain anatomy may contribute to this variability via creating varying electric fields in the brain. This implies that the electric fields or their strength and orientation should be considered and incorporated when selecting the TDCS dose. Unfortunately, electric field modeling is difficult to perform; thus, a more-robust and practical method of estimating the strength of TDCS electric fields for experimental use is required. As recent studies have revealed a relationship between the sensitivity to TMS and motor cortical TDCS after-effects, the aim of the present study was to investigate whether the resting motor threshold (RMT), a simple measure of transcranial magnetic stimulation (TMS) sensitivity, would be useful for estimating TDCS electric field strengths in the hand area of primary motor cortex (M1). To achieve this, we measured the RMT in 28 subjects. We also obtained magnetic resonance images from each subject to build individual three-dimensional anatomic models, which were used in solving the TDCS and TMS electric fields using the finite element method (FEM). Then, we calculated the correlation between the measured RMT and the modeled TDCS electric fields. We found that the RMT correlated with the TDCS electric fields in hand M1 (R2 = 0.58), but no obvious correlations were identified in regions outside M1. The found correlation was mainly due to a correlation between the TDCS and TMS electric fields, both of which were affected by individual's anatomic features. In conclusion, the RMT could provide a useful tool for estimating cortical electric fields for motor cortical TDCS.

    Research areas

  • Electric field estimation, FEM, Resting motor threshold, TDCS, TMS

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