Spread of Activity Following TMS is related to Intrinsic Resting Connectivity to the Salience Network: A Concurrent TMS-fMRI study

Publication date: Available online 30 July 2018

Source: Cortex

Author(s): Colin Hawco, Aristotle Voineskos, Jennifer K.E. Steeves, Erin W. Dickie, Joseph D. Viviano, Jonathan Downar, Daniel M. Blumberger, Zafiris J. Daskalakis

Abstract

Transcranial magnetic stimulation (TMS) modulates activity at local and regions distal to the site of simulation. TMS has also been found to modulate brain networks, and it has been hypothesized that functional connectivity may predict the neuronal changes at local and distal sites in response to a TMS pulse. However, a direct relationship between resting connectivity and change in TMS-induced brain activation has yet to be demonstrated. Concurrent TMS-fMRI is a technique to directly measure this spread activity following TMS in real time. In twenty-two participants, resting-state fMRI scans were acquired, followed by four ten minute sessions of concurrent TMS-fMRI over the left dorsolateral prefrontal cortex. Seed-based functional connectivity to the individualized TMS target was examined using the baseline resting fMRI scan data, and the change of activity resulting from TMS was determined using a general linear model (High vs Low intensity TMS). While at the group level the spatial pattern of resting connectivity related to the pattern of TMS-induced cortical changes, there was substantial variability across individuals. This variability was further probed by examining individual's connectivity from the TMS target to six resting state networks. Only connectivity between the salience network and the TMS target site correlated with the RSC-TMS score. This suggests that resting state connectivity is correlated with TMS-induced changes in activity following DLPFC stimulation, particularly when the DLPFC target interacts with the salience network. These results highlight the importance of examining such relationships at the individual level and may help to guide individual treatment in clinical populations.

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