rsHRF (Python)

rsHRF (Python) estimates and deconvolves resting-state hemodynamic response functions (HRFs) from BOLD fMRI signals to enable analysis of HRF variability in resting-state neuroimaging.

Key Features:

• Cross-Platform Implementation: Implemented in Matlab and Python.
• HRF Estimation and Deconvolution: Estimates HRFs and performs deconvolution from resting-state BOLD signals and resting-state fMRI data.
• Statistical Analysis Tools: Provides statistical analysis tools to assess variability and components of BOLD signals in resting-state studies.
• Visualization Capabilities: Provides visualization options to display HRFs and related data.

Scientific Applications:

• Resting-state fMRI interpretation: Improves interpretation of resting-state fMRI by providing HRF estimates for signal origin assessment.
• Variability reduction: Reduces intra- and inter-subject variability in activation and connectivity measurements.
• Connectivity and temporal precedence: Supports connectivity analyses by improving temporal precedence estimates in resting-state studies.

Methodology:

rsHRF employs a well-defined algorithm for HRF estimation and deconvolution tailored to resting-state protocols and has been validated using publicly available resting-state fMRI datasets.