rsHRF: A toolbox for resting-state HRF estimation and deconvolution

• Published in: NeuroImage (Orlando, Fla.) Vol. 244; p. 118591
• Main Authors: Wu, Guo-Rong, Colenbier, Nigel, Van Den Bossche, Sofie, Clauw, Kenzo, Johri, Amogh, Tandon, Madhur, Marinazzo, Daniele
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.12.2021; Elsevier Limited; Elsevier
• Subjects: Adult; Algorithms; BIDS; Blood; Brain - diagnostic imaging; brain connectivity; Brain mapping; deconvolution; Female; Fourier transforms; Functional magnetic resonance imaging; Hemodynamics - physiology; HRF; Humans; Magnetic Resonance Imaging - methods; Male; MATLAB; Middle Aged; Neural networks; Neuroimaging; Python; Research Design; resting-state fMRI; Statistical analysis; Young Adult; brain connectivity; deconvolution; BIDS; resting-state fMRI; HRF; MATLAB; Python
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2021.118591

The hemodynamic response function (HRF) greatly influences the intra- and inter-subject variability of brain activation and connectivity, and might confound the estimation of temporal precedence in connectivity analyses, making its estimation necessary for a correct interpretation of neuroimaging studies. Additionally, the HRF shape itself is a useful local measure. However, most algorithms for HRF estimation are specific for task-related fMRI data, and only a few can be directly applied to resting-state protocols. Here we introduce rsHRF, a Matlab and Python toolbox that implements HRF estimation and deconvolution from the resting-state BOLD signal. We first provide an overview of the main algorithm, practical implementations, and then demonstrate the feasibility and usefulness of rsHRF by validation experiments with a publicly available resting-state fMRI dataset. We also provide tools for statistical analyses and visualization. We believe that this toolbox may significantly contribute to a better analysis and understanding of the components and variability of BOLD signals.