rsHRF (MATLAB)

rsHRF estimates hemodynamic response functions (HRFs) and performs deconvolution of resting-state BOLD signals to support analysis of neurovascular coupling and functional connectivity.

Key Features:

• HRF Estimation and Deconvolution: Estimates HRFs from resting-state BOLD signals and performs deconvolution to recover putative underlying neural activity.
• Validation and Feasibility: Validated on publicly available resting-state fMRI datasets.
• Statistical Analysis Tools: Provides integrated statistical analyses for HRF parameters and BOLD signal components.
• Visualization Capabilities: Includes routines to visualize estimated HRFs and deconvolution results.
• Cross-Platform Compatibility: Implements algorithms in both MATLAB and Python.

Scientific Applications:

• HRF characterization in resting-state fMRI: Characterizing region-wise and subject-wise HRF shapes in resting-state fMRI data.
• Functional connectivity analysis: Reducing HRF-related confounds in functional connectivity and temporal precedence analyses.
• Separation of hemodynamic and neural signals: Enabling more accurate interpretation of resting-state BOLD signals by separating hemodynamic and neural components.

Methodology:

Estimation and deconvolution of HRFs from resting-state BOLD signals, statistical analysis of HRF parameters, visualization of results, and validation on publicly available resting-state fMRI datasets; implementations provided in MATLAB and Python.