The NIRS Brain AnalyzIR Toolbox

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650–900 nm) to measure changes in cerebral blood volume and oxygenation. Over the last several decades, this technique has been utilized in a growing number of functional and resting-...

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Bibliographic Details
Published inAlgorithms Vol. 11; no. 5; p. 73
Main Authors Santosa, Hendrik, Zhai, Xuetong, Fishburn, Frank, Huppert, Theodore
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.05.2018
Subjects
Blood volume
Brain
Confining
Data management
Functional near-infrared spectroscopy
Image reconstruction
Infrared analysis
Infrared spectra
Light levels
Magnetic resonance imaging
Medical imaging
Near infrared radiation
Neurology
Object oriented programming
Oxygenation
Source code
Statistical analysis
toolbox
Uniqueness
toolbox
statistical analysis
Functional near-infrared spectroscopy
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Summary:Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650–900 nm) to measure changes in cerebral blood volume and oxygenation. Over the last several decades, this technique has been utilized in a growing number of functional and resting-state brain studies. The lower operation cost, portability, and versatility of this method make it an alternative to methods such as functional magnetic resonance imaging for studies in pediatric and special populations and for studies without the confining limitations of a supine and motionless acquisition setup. However, the analysis of fNIRS data poses several challenges stemming from the unique physics of the technique, the unique statistical properties of data, and the growing diversity of non-traditional experimental designs being utilized in studies due to the flexibility of this technology. For these reasons, specific analysis methods for this technology must be developed. In this paper, we introduce the NIRS Brain AnalyzIR toolbox as an open-source Matlab-based analysis package for fNIRS data management, pre-processing, and first- and second-level (i.e., single subject and group-level) statistical analysis. Here, we describe the basic architectural format of this toolbox, which is based on the object-oriented programming paradigm. We also detail the algorithms for several of the major components of the toolbox including statistical analysis, probe registration, image reconstruction, and region-of-interest based statistics.
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Author Contributions: H.S., X.Z., and F.F. made the figures, updated several modules in the AnalyzIR toolbox periodically, and contributed to the text file. Theodore Huppert supervised the toolbox, updated most of the modules, and corrected the entire manuscript. All the authors read and approved the final manuscript.
ISSN:1999-4893
1999-4893
DOI:10.3390/a11050073