The NIRS Brain AnalyzIR Toolbox
The NIRS Brain AnalyzIR Toolbox
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DOI：
10.3390/a11050073
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发表时间：
2018-05-01
期刊：
影响因子：
2.3
通讯作者：
Huppert, Theodore
中科院分区：
文献类型：
--
作者：
Santosa, Hendrik;Zhai, Xuetong;Huppert, Theodore
功能性近红外光谱(FNIRS)是一种非侵入性的神经成像技术，它使用弱光(650-900 nm)来测量大脑血液容量和氧合的变化。在过去的几十年里，这项技术已经被越来越多的功能和静息状态的大脑研究所使用。该方法较低的操作成本、便携性和通用性使其成为儿科和特殊人群研究以及不受仰卧和静止采集装置的限制的研究的功能磁共振成像方法的替代方法。然而，对fNIRS数据的分析提出了几个挑战，这源于该技术的独特物理特性、数据的独特统计特性以及由于该技术的灵活性而在研究中使用的非传统实验设计的日益多样化。出于这些原因，必须为这项技术开发具体的分析方法。在本文中，我们介绍了NIRS Brain AnalyzIR工具箱，它是一个基于MatLab的开源分析包，用于fNIRS数据管理、前处理以及第一和第二级别(即，单主题和组级别)统计分析。在这里，我们描述了这个工具箱的基本体系结构格式，它基于面向对象的编程范例。我们还详细介绍了工具箱的几个主要组成部分的算法，包括统计分析、探头配准、图像重建和基于感兴趣区域的统计。
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.