. Transcranial magnetic stimulation (TMS) is a promising tool for the treatment of a large number of neuropsychiatric disorders including depression, obsessive-compulsive disorder, Alzheimer?s disease, and addiction. In fact, TMS has already been approved by the Food and Drug Administration (FDA) for depres- sion treatment, testifying to its effectiveness. However, the effects of TMS are known to vary substantially be- tween subjects, thus reducing its therapeutic efficacy. Traditionally, the large variability in TMS responsiveness has been seen as an inevitable limitation of the technique. On the other hand, computational ?state-based? the- ories postulate that the effects of TMS critically depend on a combination of the pre-TMS state of the targeted network and the strength of stimulation. State-based theories imply that it is possible to reduce the variability of TMS and enhance its therapeutic effectiveness by taking into account the state of the brain right before stimula- tion. However, the notion that the pre-TMS state can qualitatively alter the behavioral effects of TMS has not been examined directly by actual recordings of pre-TMS brain activity. The current proposal will perform the first direct test of these theories by an innovative combination of TMS and concurrent functional magnetic resonance imaging (fMRI). Delivering precisely-targeted TMS inside the MRI environment and obtaining artifact-free fMRI data is difficult but the Georgia Tech research group has already built a setup and collected pilot data from three different protocols demonstrating ability to conduct such experiments and obtain high-quality data. Existing pilot data comes from experiments characterizing the effects of TMS on the area under the coil by applying TMS at rest. To directly test state-based theories, the current proposal will employ concurrent TMS-fMRI with two distinct tasks in a large sample of healthy young adults.
Aim 1 will examine how the pre-TMS activity in the targeted area influences the effect of TMS on behavior and whether the level of this activity interacts with the intensity of TMS. Based on state-based theories, it is expected that low pre-TMS activity coupled with low-intensity TMS will lead to performance improvement, whereas high pre-TMS activity coupled with high-intensity TMS will lead to perfor- mance impairment. However, the effectiveness of TMS is likely determined not just by the activity of the area under the TMS coil but also by the state of large brain networks. Therefore, Aim 2 will additionally test how the pattern of connectivity in large brain networks affects the behavioral effects of TMS. Further, it will be examined whether the global brain state is important in determining the effect of TMS and whether particular networks can be identified that influence TMS effectiveness. The proposed research will thus test a long-standing hypothesis regarding the state-dependency of TMS effects by an innovative use of concurrent TMS-fMRI. The findings from this proposal are expected to have immediate applications in already existing efforts to use TMS as a therapeutic device.
The project will investigate how the pre-TMS brain state can be used to predict the effectiveness of TMS on behavior. The proposed research is relevant to public health because it will inform existing efforts to use TMS as a treatment tool for a number of neuropsychiatric disorders such as depression, obsessive-compulsive disor- der, Alzheimer?s disease, and addiction. Thus, the proposal is relevant to NIH?s mission of developing funda- mental knowledge that can be applied to reduce the burden of human disability.
