This repository contains code and resources for working with special '.snirf' files.
'SNIRF' stands for Standardized Near-Infrared Spectroscopy Data Format. These files are commonly used in functional Near-Infrared Spectroscopy (fNIRS) research. fNIRS is a non-invasive neuroimaging technique that measures changes in blood oxygenation in the brain by sending near-infrared light through the scalp. '.snirf' files are used to store and manage fNIRS data, making them a crucial component of fNIRS research.
- Data Storage: '.snirf' files are used to store raw fNIRS data, including information on light sources, detectors, and the recorded signals.
- Data Sharing: Researchers use '.snirf' files to share fNIRS data, ensuring data consistency and compatibility across different software and platforms.
- Analysis: The standardized format of '.snirf' files simplifies data analysis, as multiple software packages support this format, allowing researchers to process and analyze fNIRS data efficiently.
- Meta-Analysis: Researchers and the broader scientific community can use '.snirf' files to conduct meta-analyses, combining data from multiple studies to draw broader conclusions.
This repository includes code and tools for working with the 'mne' module.
The 'mne' module, short for MNE-Python, is a powerful open-source software for working with electrophysiological and neuroimaging data, including Magnetoencephalography (MEG) and Electroencephalography (EEG). It provides a comprehensive set of functions for data preprocessing, analysis, and visualization.
- Neuroimaging Data Processing: The 'mne' module is used to preprocess and analyze MEG and EEG data, which are essential for studying brain function and understanding neural activity.
- Source Localization: Researchers can apply the 'mne' module to estimate the sources of brain activity, helping identify the regions responsible for specific cognitive functions.
- Functional Connectivity Analysis: It allows for the investigation of how different regions of the brain communicate and synchronize their activities.
- Brain Imaging Visualization: The 'mne' module provides tools to create visualizations and brain maps, aiding in the interpretation of neuroimaging results.
- Statistical Analysis: Researchers use 'mne' for statistical analysis to draw conclusions and infer relationships between neural activity and behavioral or cognitive processes.