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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Vydané v:	Algorithms Ročník 11; číslo 5; s. 73
Hlavní autori:	Santosa, Hendrik, Zhai, Xuetong, Fishburn, Frank, Huppert, Theodore
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 01.05.2018
Predmet:	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
ISSN:	1999-4893, 1999-4893
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Abstract	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.
AbstractList	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.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. 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.
Author	Huppert, Theodore Santosa, Hendrik Fishburn, Frank Zhai, Xuetong
AuthorAffiliation	4 Departments of Radiology and Bioengineering, University of Pittsburgh, Clinical Science Translational Institute, and Center for the Neural Basis of Cognition, Pittsburgh, PA 15213-2536, USA 1 Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA 2 Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA 3 Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA
AuthorAffiliation_xml	– name: 1 Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA – name: 3 Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA – name: 4 Departments of Radiology and Bioengineering, University of Pittsburgh, Clinical Science Translational Institute, and Center for the Neural Basis of Cognition, Pittsburgh, PA 15213-2536, USA – name: 2 Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213-2536, USA
Author_xml	– sequence: 1 givenname: Hendrik surname: Santosa fullname: Santosa, Hendrik – sequence: 2 givenname: Xuetong surname: Zhai fullname: Zhai, Xuetong – sequence: 3 givenname: Frank orcidid: 0000-0002-1227-2834 surname: Fishburn fullname: Fishburn, Frank – sequence: 4 givenname: Theodore surname: Huppert fullname: Huppert, Theodore
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/38957522$$D View this record in MEDLINE/PubMed
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ContentType	Journal Article
Copyright	Copyright MDPI AG 2018
Copyright_xml	– notice: Copyright MDPI AG 2018
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DOI	10.3390/a11050073
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Keywords	toolbox statistical analysis Functional near-infrared spectroscopy
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 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.
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Snippet	Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650–900 nm) to measure changes in cerebral... Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low-levels of light (650-900 nm) to measure changes in cerebral...
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SubjectTerms	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
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