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Abstract #3905

Evaluation of GLM fit dependency on the temporal sampling rate and the applied HRF model in BOLD fMRI

Virág Darányi1, Petra Hermann1, Zoltán Nagy2, Zoltán Vidnyánszky1, and Ádám Ottó Kettinger1

1Brain Imaging Centre, Hungarian Academy of Sciences Research Centre for Natural Sciences, Budapest, Hungary, 2Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland

Modeling the haemodynamic response in fMRI is still subject of research. Recent developments in accelerated MRI enabled subsecond whole-brain fMRI. In this work we aim to examine the dependency of BOLD signal analysis on the temporal sampling rate and the applied HRF model by numerically undersampling a fast acquisition. Standard GLM fits with different HRF models were performed, followed by group-level statistical analyses and goodness-of-fit computations. The results indicate that variance across HRF models is increased in the undersampled datasets, while the low-pass-filtered undersampling also shows a possibility to enhance the statistical power on the group level.

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