Abstract
Background: Transcranial magnetic stimulation (TMS) has the potential to treat brain disorders by tonically modulating firing patterns in disease-specific neural circuits. The selection of treatment parameters for clinical repetitive transcranial magnetic stimulation (rTMS) trials has not been rule based, likely contributing to the variability of observed outcomes. Objective: To utilize our newly developed baboon (Papio hamadryas anubis) model of rTMS during position-emission tomography (PET) to quantify the brain's rate-response functions in the motor system during rTMS. Methods: We delivered image-guided, suprathreshold rTMS at 3 Hz, 5 Hz, 10 Hz, 15 Hz and rest (in separate randomized sessions) to the primary motor cortex (M1) of the lightly anesthetized baboon during PET imaging; we also administered a (reversible) paralytic to eliminate any somatosensory feedback due to rTMS-induced muscle contractions. Each rTMS/PET session was analyzed using normalized cerebral blood flow (CBF) measurements; statistical parametric images and the resulting areas of significance underwent post-hoc analysis to determine any rate-specific rTMS effects throughout the motor network. Results: The motor system's rate-response curves were unimodal and system wide - with all nodes in the network showing highly similar rate response functions - and an optimal network stimulation frequency of 5 Hz. Conclusion(s): These findings suggest that non-invasive brain stimulation may be more efficiently delivered at (system-specific) optimal frequencies throughout the targeted network and that functional imaging in non-human primates is a promising strategy for identifying the optimal treatment parameters for TMS clinical trials in specific brain regions and/or networks.
Original language | English (US) |
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Pages (from-to) | 777-787 |
Number of pages | 11 |
Journal | Brain Stimulation |
Volume | 6 |
Issue number | 5 |
DOIs | |
State | Published - Sep 2013 |
Keywords
- Animal models
- Motor cortex
- Network
- PET
- Rate
- TMS
ASJC Scopus subject areas
- Clinical Neurology
- Biophysics
- General Neuroscience