NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy

Area of Science:

• Neuroscience
• Biomedical Engineering
• Medical Imaging

Background:

• Near-infrared spectroscopy (NIRS) is a non-invasive brain imaging technique measuring hemoglobin oxygenation.
• NIRS offers complementary temporal resolution to fMRI's spatial resolution.
• Existing NIRS statistical tools lack quantitative analysis capabilities for simultaneous fMRI studies.

Purpose of the Study:

• To introduce NIRS-SPM, a novel public domain statistical toolbox for NIRS data analysis.
• To enable quantitative analysis of NIRS signals, particularly in conjunction with fMRI.
• To overcome limitations of current NIRS statistical analysis tools.

Main Methods:

• NIRS-SPM utilizes the general linear model (GLM) and Sun's tube formula for statistical analysis.
• P-values are computed using excursion probabilities on a representation manifold.
• The toolbox analyzes oxy-, deoxy-, and total hemoglobin concentration changes.

Main Results:

• NIRS-SPM facilitates the creation of activation maps for hemodynamic changes.
• The toolbox enables super-resolution localization of brain activity, surpassing conventional methods.
• Experimental validation using finger tapping and memory tasks confirmed the method's viability.

Conclusions:

• NIRS-SPM provides a robust framework for quantitative NIRS data analysis.
• The toolbox enhances the integration of NIRS and fMRI for improved brain activity measurement.
• NIRS-SPM offers advanced localization capabilities for neuroimaging research.