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Activity Number: 266 - Causal Inference in Neuroimaging and Radiology
Type: Topic Contributed
Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Imaging
Abstract #322078
Title: Challenges and Opportunities of Using Interleaved TMS/fMRI Data to Personalize Treatment for Depression
Author(s): Kristin Linn*
Companies: University of Pennsylvania
Keywords: TMS; fMRI; imaging; neuroimaging; depression
Abstract:

Transcranial magnetic stimulation (TMS) is a form of non-invasive brain stimulation that can be safely delivered in trains of pulses (repetitive TMS; rTMS) to treat symptoms of depression in patients for whom standard treatments have failed. Recent advances in TMS coil technology enable rTMS to be interleaved with functional magnetic resonance imaging (fMRI), producing real-time measures of blood oxygen level dependent (BOLD) contrast in response to single pulses of TMS. Under a set of assumptions, interleaved TMS/fMRI enables estimation of individual-level causal effects of applying stimulation to accessible cortical locations. For clinical treatments, it would be useful to know if modulating brain activity in a particular region will likely alleviate a particular symptom of depression, which requires inference about population-level causal effects. Furthermore, conditional average causal effects and causal effects of multiple cortical stimulation locations are of interest in order to better personalize the treatment of depression using rTMS. In this talk, we describe challenges and opportunities that arise when working with interleaved TMS/fMRI data.


Authors who are presenting talks have a * after their name.

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