DOI: 10.5061/dryad.8kprr4z0t
title: fNIRS and demographic data for 3- to 9-month infants with congenital sensorineural hearing loss

description: Auditory exposure plays a crucial role in shaping brain development, but
 little is known about whether and how an initial lack of auditory exposure
 might disrupt the development of functional network lateralization. We
 addressed this issue by acquiring functional near infrared spectroscopy
 data from infants aged 3–9 months with congenital sensorineural hearing
 loss (SNHL) and typically developing controls.
description: # fNIRS and demographic data for 3- to 9-month infants with congenital
 sensorineural hearing loss Dataset DOI:
 [10.5061/dryad.8kprr4z0t](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](https://github.com/lihongxun/FC-NIRS). **Download:** To obtain FC-NIRS, please visit [https://www.nitrc.org/projects/fcnirs](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 -&gt; Add Shortcut to Desktop-&gt;Next Step -&gt; Next Step -&gt; 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-&gt;Next Step -&gt; Next Step -&gt;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.