Dataset DOI: 10.5061/dryad.8kprr4z0t

Description of the data and file structure

fNIRS and demographic data were collected from 3–9-month-old infants with congenital SNHL and age-matched typically developing (TD) controls to examine developmental differences in brain network lateralization.

Files and variables

File: sub_info.xlsx

Description: 

Variables

• group: Indicates the type of participant — infants with sensorineural hearing loss (SNHL) or typically developing (TD) controls.
• ID: A numerical identifier assigned to each infant.
• age: Age range in months of each infant.
• ABR: Auditory brainstem response (ABR) threshold values for each infant.

File: SNHL_nirs.zip

Description: fnirs data of infants with sensorineural hearing loss. Each .nirs file includes:

• d: data matrix (time × channels, raw light intensity)
• t: time vector (seconds)
• s: stimulus markers (time × conditions)
• SD: probe geometry (sources, detectors, measurement list, wavelengths)

File: TD_nirs.zip

Description: fnirs data of typically developing infants. Each .nirs file includes:

• d: data matrix (time × channels, raw light intensity)
• t: time vector (seconds)
• s: stimulus markers (time × conditions)
• SD: probe geometry (sources, detectors, measurement list, wavelengths)

File: read_nirs.py

Description: To ensure unrestricted access, we provide a Python script read_nirs.py that allows users to open and inspect the .nirs files.

Requirements: Install Python packages (open-source, license-free):

    pip install numpy scipy matplotlib

Usage: Run the script with a .nirs file as input:

    python read_nirs.py SNHL_nirs/sub01.nirs

Example Output (terminal log): see terminal_log.png for details.

Output: PNG plot (*_plot.png) showing the first three channels over time.

Example Plot (PNG): see signal_plot.png for details.

Code/software

The data can be viewed and analyzed using FC-NIRS, a free toolbox specifically developed for functional connectivity analysis of fNIRS data. The software supports raw signal preprocessing, construction of functional brain networks, and computation of graph theory metrics. The current dataset is compatible with FC-NIRS, which can be accessed via https://www.nitrc.org/projects/fcnirs.

Download: To obtain FC-NIRS, please visit https://www.nitrc.org/projects/fcnirs. Click “See All Files” and download the most recent release of FC-NIRS for your operating system (Windows or macOS).

Installation: Windows 64 bit or Mac OS operation system on your computer to run FC-NIRS. For optimal performance and compatibility, we recommend using Windows.

Installation for Windows 

1.Double click FC-NIRS.exe 

2.Click “Next Step -> Add Shortcut to Desktop->Next Step -> Next Step -> Install” to run the installation. 

Installation for Mac OS

1.Double click FC-NIRS.app 

2.Input the password of Mac OS then click “Next Step->Next Step -> Next Step ->Install” to run the installation 

Run FC-NIRS

Double-click the FC-NIRS desktop shortcut or the FC-NIRS application file to launch the program. The main interface will appear as shown in  FC_NIRS_main.png .

View .nirs data

Click the “Preprocessing” button to open the Preprocessing interface shown in FC_NIRS_preprocessing.png, where you can view and access the .nirs data.

After selecting the input files and output directory, you can view the raw light intensity signals and the probe geometry distribution. For details on preprocessing and further analysis, please download FC_NIRS_Manual_V3_0.pdf from the same page where you obtained FC-NIRS, which provides instructions for preprocessing and functional connectivity analysis of fNIRS data.

Human subjects data

All data have been properly de-identified in accordance with applicable ethical and legal standards. I confirm that I obtained explicit informed consent from all participants for their de-identified data to be shared in a public repository. Personally identifiable information (PII), such as names or contact information, has been removed. Participants are represented using numeric IDs instead of names or other identifiers.