NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis

Abstract

Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies. Aim: We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS. Approach: We developed a MATLAB toolbox called NIRS-KIT that works for both resting-state analysis and task activation detection. 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. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided. Additionally, NIRS-KIT also supports activation analysis for task fNIRS. Conclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/or task fNIRS data in one suite. 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. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.

Keywords: data analysis; functional near-infrared spectroscopy; near-infrared spectroscopy-KIT; resting-state; task activation; toolbox.

Fig. 1

User interfaces of NIRS-KIT: (a) the main interface window of NIRS-KIT; (b) subwindow for the resting-state fNIRS analysis module; and (c) subwindow for the task fNIRS analysis module.

Fig. 2

Main processing pipeline in NIRS-KIT. FC, functional connectivity; GLM, general linear model; ALFF, amplitude of low-frequency fluctuation; and fALFF, fractional amplitude of low-frequency fluctuation.

Fig. 3

User interface for data preparation module with supported data sources.

Fig. 4

The Data Viewer module for resting-state fNIRS. A 7-min resting-state fNIRS dataset ($n=9$) using two standard $3\times 5$ probes (total 44 channels) is shown as an example.

Fig. 5

The data preprocessing interface and demonstrations of processing methods on real data. (a) GUI of the data preprocessing module; (b) demonstration of the effect of detrending (linear detrending); (c) demonstration of motion correction using TDDR method; and (d) demonstration of filtering by a third-order IIR Butterworth bandpass filter (0.01 to 0.08 Hz).

Fig. 6

Individual-level analysis interfaces for resting-state fNIRS data in NIRS-KIT: (a) GUI for individual-level analysis of resting-state fNIRS and (b) interface for analyzing ALFF and fALFF.

Fig. 7

The diagram for computing individual ALFF and fALFF.

Fig. 8

Group-level analysis interfaces: (a) the main GUI for group-level statistics and (b) one-sample $t$-test is shown as an example.

Fig. 9

Examples of visualization for resting-state analysis results: (a) group-level zfALFF map (interpolation mode); (b) ROI2Whole FC map (non-interpolation mode, and channel 12 is the seed channel); (c) non-interpolated channel-wise 3D visualization for group-level zfALFF result using the NFRI toolbox; (d) 2D whole brain FC matrix map; and (e) 3D visualization of whole brain connectivity matrix by BrainNet Viewer using the node and edge files generated by NIRS-KIT. Note: All above color bars represent group-level ($n=9$) one-sample $t$-test statistical values, and the color axis limits are set for illustration only. In A and B panels, only the left hemisphere probe (channels 1 to 22) is displayed to reduce clutter.

Fig. 10

The Data Viewer module for task fNIRS. Task design information is shown in the task option panel (lower left). Dashed green lines indicate reference signal time series (upper right) or the periodogram (lower middle) of the selected task condition.

Fig. 11

Individual-level analysis interfaces for task fNIRS. (a) The individual-level analysis interface for task fNIRS with manual input of task design (when design is the same for all participants). (b) The individual-level analysis interface for task fNIRS with different designs per participants; one column of randomly generated covariates is added into the GLM as an illustration.

Fig. 12

Example visualizations for task fNIRS analysis results: (a) 2D group-level statistical map for task activation (interpolation mode); (b) non-interpolation 3D visualization on a standard brain surface; (c) visualization using MRIcroGL via overlaying the NIFTI file generated by NIRS-KIT; and (d) interpolated 3D visualization on a standard brain surface using EasyTopo. All colors represent the $t$-statistic values of group-level one-sample $t$-test.