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Using diffusion tensor imaging to effectively target TMS to deep brain structures

Authors :
Bruce Luber
Simon W. Davis
Zhi-De Deng
David Murphy
Andrew Martella
Angel V. Peterchev
Sarah H. Lisanby
Source :
NeuroImage, Vol 249, Iss , Pp 118863- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

TMS has become a powerful tool to explore cortical function, and in parallel has proven promising in the development of therapies for various psychiatric and neurological disorders. Unfortunately, much of the inference of the direct effects of TMS has been assumed to be limited to the area a few centimeters beneath the scalp, though clearly more distant regions are likely to be influenced by structurally connected stimulation sites. In this study, we sought to develop a novel paradigm to individualize TMS coil placement to non-invasively achieve activation of specific deep brain targets of relevance to the treatment of psychiatric disorders. In ten subjects, structural diffusion imaging tractography data were used to identify an accessible cortical target in the right frontal pole that demonstrated both anatomic and functional connectivity to right Brodmann area 25 (BA25). Concurrent TMS-fMRI interleaving was used with a series of single, interleaved TMS pulses applied to the right frontal pole at four intensity levels ranging from 80% to 140% of motor threshold. In nine of ten subjects, TMS to the individualized frontal pole sites resulted in significant linear increase in BOLD activation of BA25 with increasing TMS intensity. The reliable activation of BA25 in a dosage-dependent manner suggests the possibility that the careful combination of imaging with TMS can make use of network properties to help overcome depth limitations and allow noninvasive brain stimulation to influence deep brain structures.

Details

Language :
English
ISSN :
10959572
Volume :
249
Issue :
118863-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.98b9c401d37145acb28bb774c9c2b59a
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2021.118863