Locating activation sites of TMS with opposite current directions using probabilistic modelling and biophysical axon models

Ilkka Laakso*, Juhani Kataja, Noora Matilainen, Timo Roine, Thomas Tarnaud, Yoshikazu Ugawa

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Background: Motor responses evoked by transcranial magnetic stimulation (TMS) using posterior–anterior (PA) and anterior–posterior (AP) current directions have distinct latencies and thresholds. However, the underlying reasons for these differences remain unclear. Objective: To quantify the differences in activation sites between PA- and AP-TMS. Methods: Motor evoked potentials (MEPs) were recorded from five hand and arm muscles in nine healthy participants using both PA- and AP-TMS. Active motor thresholds were determined at 11 magnetic coil positions on the scalp. Probabilistic modelling was used to combine the measured threshold data with calculated electric field data from individual MRI-based models. This approach constructed 70 probability distributions of the activation site, dependent on the muscle and TMS direction. Results: Modelling indicated that both PA- and AP-TMS more likely activated structures in white matter than in grey matter. PA-TMS activation sites were primarily in the white or grey matter in the precentral gyrus, while the AP-TMS activations were deeper and more posterior and lateral, likely within white matter under the postcentral and/or precentral gyri. Tractography and biophysical axon models provided a potential explanation on the location of activation sites: AP-TMS may activate the bends of white matter axons farther from M1 than PA-TMS, such that the conduction velocity along the neural tract could potentially explain the longer MEP latency of AP-TMS. The differences in activation sites among the five hand and arm muscles were small. Conclusion: While a direct experimental confirmation of the activation sites is still needed, the results suggest that electric field analysis combined with tractography and biophysical axon modelling could be a useful computational tool for analysing and optimizing TMS.

Original languageEnglish
Pages (from-to)215-224
Number of pages10
JournalBrain Stimulation
Volume18
Issue number2
DOIs
Publication statusPublished - Mar 2025
MoE publication typeA1 Journal article-refereed

Keywords

  • Active motor threshold
  • Computational modelling
  • Latency
  • Motor-evoked potential
  • Primary motor cortex
  • Transcranial magnetic stimulation

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