Title
In Silico Prediction of Changes in Intrinsic Network Functional Connectivity Following Repetitive Transcranial Magnetic Stimulation
Files
Download Breanna Shen Original Presentation File (3.3 MB)
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Publication Date
Summer 8-6-2020
College, Institute, or Department
MD/PhD Scholars Program
Faculty Mentor
Dr. David Warren
Research Mentor
Connor Phipps
Document Type
Poster
Abstract
Targeted transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that can influence brain activity, psychiatric features, and cognitive performance. While TMS has been reported to affect cognitive performance across a variety of domains, substantial gaps in knowledge remain regarding the association of these TMS-based cognitive changes and functional connectivity in the brain. In this project, we aim to build a computational model to simulate the effects of TMS on functional associations between a stimulated brain region and the brain networks connected to that brain region. Using data from the Human Connectome Project as the basis for the brain’s functional connectivity, we built a prototypical matrix that models all cortical brain regions (“parcels”) and the functional connections between them. From this starting point, our computational model predicts the effects of stimulating a specific parcel with TMS. Further, our model includes variable parameters to support estimation of functional effects associated with differences in TMS delivery (applying excitatory or inhibitory stimulation), stimulation intensity, stimulation duration (days of TMS), etc. Finally, the model supports estimation of not only local results, but also whole-brain changes in functional connectivity. Based on the quantitative changes in the model estimates associated with different parameter settings, we were able to predict the effects on functional connectivity both within the parcel’s network as well as across the entire cortex. Our approach is an important first step toward individualized in silico computation of how TMS affects the brain, and our work may have implications for developing more effective treatment with TMS.
Keywords
Transcranial Magnetic Stimulation (TMS), Network Functional Connectivity, Connectomics
Recommended Citation
Shen, Breanna; Phipps, Connor; and Warren, David, "In Silico Prediction of Changes in Intrinsic Network Functional Connectivity Following Repetitive Transcranial Magnetic Stimulation" (2020). Posters: 2020 Summer Undergraduate Research Program. 24.
https://digitalcommons.unmc.edu/surp2020/24