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Abstract #5330

Region-specific modeling of heart rate and respiratory volume signal contributions  in whole-brain high-spatial resolution resting-state fMRI at 7 Tesla

Joana Pinto1, Sandro Nunes1, Marta Bianciardi2, Afonso Dias1, Luis Miguel Silveira3, Lawrence Wald2, and Patricia Figueiredo1

1Institute for Systems and Robotics - Lisbon and Department of Bioengineering, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal, 2Department of Radiology, A.A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States, 3INESC-ID and Department of Electrical and Computer Engineering, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal

Several strategies have been proposed for correcting physiological noise in rs-fMRI, including different models of respiratory volume (RV) and heart rate (HR) effects. Although group-level model optimization has often been employed, it has been reported that these effects are highly variable across subjects and brain regions. Here, we investigated the impact of optimizing the time-lags of RV and HR physiological noise contributions at different levels of specificity in 7 Tesla rs-fMRI. We found that a regional optimization based on a clustering approach taking into account the time-lags’ individual spatial variability explained more fMRI signal variance than group or subject-based optimizations.

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