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The NIRS Brain AnalyzIR Toolbox.

Hendrik Santosa1, Xuetong Zhai2, Frank Fishburn3

  • 1Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA.

Algorithms
|July 3, 2024
PubMed
Summary
This summary is machine-generated.

Functional near-infrared spectroscopy (fNIRS) analysis is challenging. The NIRS Brain AnalyzIR toolbox offers an open-source solution for fNIRS data management, pre-processing, and statistical analysis.

Keywords:
Functional near-infrared spectroscopystatistical analysistoolbox

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Area of Science:

  • Neuroimaging
  • Biomedical Engineering
  • Cognitive Neuroscience

Background:

  • Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique measuring cerebral blood volume and oxygenation using near-infrared light.
  • Its portability, lower cost, and versatility make fNIRS suitable for pediatric populations and studies outside traditional laboratory settings, unlike fMRI.
  • Analyzing fNIRS data presents unique challenges due to its physics, data properties, and diverse experimental designs.

Purpose of the Study:

  • Introduce the NIRS Brain AnalyzIR toolbox, an open-source Matlab package.
  • Provide a comprehensive solution for fNIRS data management, pre-processing, and statistical analysis.
  • Address the analytical challenges inherent in fNIRS data.

Main Methods:

  • Developed an open-source Matlab-based toolbox named NIRS Brain AnalyzIR.
  • Utilized an object-oriented programming paradigm for the toolbox architecture.
  • Implemented algorithms for statistical analysis, probe registration, image reconstruction, and ROI-based statistics.

Main Results:

  • The NIRS Brain AnalyzIR toolbox facilitates data management, pre-processing, and statistical analysis for fNIRS studies.
  • The toolbox supports both single-subject (first-level) and group-level (second-level) analyses.
  • Detailed algorithms for key components ensure robust data processing and analysis.

Conclusions:

  • The NIRS Brain AnalyzIR toolbox provides a necessary and specific analysis solution for fNIRS data.
  • Its open-source nature and comprehensive features support the growing use of fNIRS in neuroscience research.
  • The toolbox aims to overcome the analytical hurdles associated with fNIRS data, enhancing its utility.