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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| Veröffentlicht in: | Algorithms Jg. 11; H. 5; S. 73 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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MDPI AG
01.05.2018
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| 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. |
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| 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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