Group-level and functional-region analysis of electric-field shape during cerebellar transcranial direct current stimulation with different electrode montages

Jose Gomez-Tames, Akihiro Asai, Marko Mikkonen, Ilkka Laakso, Satoshi Tanaka, Shintaro Uehara, Yohei Otaka, Akimasa Hirata

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)

Abstract

Objective. Cerebellar transcranial direct current stimulation (ctDCS) is a neuromodulation scheme that delivers a small current to the cerebellum. In this work, we computationally investigate the distributions and strength of the stimulation dosage during ctDCS with the aim of determining the targeted cerebellar regions of a group of subjects with different electrode montages. Approach. We used a new inter-individual registration method that permitted the projection of computed electric fields (EFs) from individual realistic head models (n = 18) to standard cerebellar template for the first time. Main results. Variations of the EF on the cerebellar surface were found to have standard deviations of up to 55% of the mean. The dominant factor that accounted for 62% of the variability of the maximum EFs was the skin- cerebellum distance, whereas the cerebrospinal fluid volume explained 53% of the average EF distribution. Despite the inter-individual variations, a systematic tendency of the EF hotspot emerges beneath the active electrode in group-level analysis. The hotspot can be adjusted by the electrode position so that the most effective stimulation is delivered to a group of subjects. Significance. Targeting specific cerebellar structures with ctDCS is not straightforward, as neuromodulation depends not only on the placement/design of the electrodes configuration but also on inter-individual variability due to anatomical differences. The proposed method permitted generalizing the EFs to a cerebellum atlas. The atlas is useful for studying the mechanisms of ctDCS, planning ctDCS and explaining findings of experimental studies.

Original languageEnglish
Article number036001
JournalJournal of Neural Engineering
Volume16
Issue number3
DOIs
Publication statusPublished - 2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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