Abstract #2417

Resting-state fMRI functional connectivity is confounded by the hemodynamic response function (HRF)

Rangaprakash Deshpande^1,2, Guo-Rong Wu^3,4, Daniele Marinazzo³, Xiaoping Hu⁵, and Gopikrishna Deshpande^2,6,7

¹Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States, ²Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, United States, ³Department of Data Analysis, University of Ghent, Ghent, Belgium, ⁴Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China, ⁵Department of Bioengineering, University of California Riverside, Riverside, CA, United States, ⁶Department of Psychology, Auburn University, Auburn, AL, United States, ⁷Alabama Advanced Imaging Consortium, Auburn University and University of Alabama Birmingham, Auburn, AL, United States

Functional MRI is an indirect measure of neural activity, as it is the convolution of the hemodynamic-response function (HRF) and latent neural response. Recent studies show variability in HRF across brain regions and individuals, with the potential to confound resting-state functional connectivity (FC) if HRF variability were ignored. Using resting-state fMRI obtained at 7T (N=47), we estimated HRF parameters using deconvolution, and tested the hypothesis that HRF variability confounds FC. We found evidence, with simulations (up to 50% error in FC) and experimental data (mean/median error = 30.5/11.5% in FC) quantifying the impact the HRF variability on FC.

This abstract and the presentation materials are available to members only; a login is required.

Join Here