Automated optimization of TMS coil placement for personalized functional network engagement
Charles J Lynch, Immanuel G Elbau, Tommy H Ng, Danielle Wolk, Shasha Zhu, Aliza Ayaz, Jonathan D Power, Benjamin Zebley, Faith M Gunning, Conor Liston, Charles J Lynch, Immanuel G Elbau, Tommy H Ng, Danielle Wolk, Shasha Zhu, Aliza Ayaz, Jonathan D Power, Benjamin Zebley, Faith M Gunning, Conor Liston
Abstract
Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient's unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.
Keywords: electric field modeling; functional brain networks; precision functional mapping; transcranial magnetic stimulation.
Conflict of interest statement
Declaration of interests C.L. is listed as an inventor for Cornell University patent applications on neuroimaging biomarkers for depression that are pending or in preparation. C.L. has served as a scientific advisor or consultant to Compass Pathways PLC, Delix Therapeutics, Magnus Medical, and Brainify.AI.
Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.
Source: PubMed