9, 10 FNIRS has been successfully applied to various neuroscience domains, including areas such as motor-related studies with large bodily movements, social cognitive neuroscience, and neurodevelopment.
Validation studies using simultaneous fNIRS and fMRI scanning have shown fNIRS to be effective for both task-driven activation detection 4 – 8 and resting-state brain function research. These advantages make it an ideal alternative for detecting human brain activity in both healthy people (from newborns to the elderly) and patients with neurological or psychiatric conditions, in both laboratory and natural contexts. 1 – 3 Compared to other neuroimaging techniques, fNIRS has several specific advantages: acceptable spatial resolution lower cost, silent, higher temporal resolution, lower sensitivity to head motion, and fewer physical constraints compared to functional magnetic resonance imaging (fMRI) portability/mobility and few restrictions on use location. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.Īs a promising non-invasive neuroimaging technique, functional near-infrared spectroscopy (fNIRS) has seen increasing use in neuroscientific studies over the last decades. It contains several key features: (1) good compatibility, supporting multiple fNIRS recording systems, data formats of NIRS-SPM and Homer2, and the shared near-infrared spectroscopy format data format recommended by the fNIRS society (2) flexibility, supporting customized preprocessing scripts (3) ease-to-use, allowing processing fNIRS signals in batch manner with user-friendly graphical user interfaces and (4) feature-packed data viewing and result visualization. Additionally, NIRS-KIT also supports activation analysis for task fNIRS.Ĭonclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/or task fNIRS data in one suite. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided.
Results: NIRS-KIT implements common and necessary processing steps for performing fNIRS data analysis, including data preparation, quality control, preprocessing, individual-level analysis, group-level statistics with several popular statistical models, and multiple comparison correction methods, and finally results visualization. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies.Īim: We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS.Īpproach: We developed a MATLAB toolbox called NIRS-KIT that works for both resting-state analysis and task activation detection. Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state.
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