Neuro Dominance Tracker

A Software for Identification and Characterization of Dominant Rhythm in Neural Time Series (e.g., EEG, LFP)

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Citation

If you use this software in your research, please cite it as follows:

N. Bahador, S. Sengupta, J. Saha, M. Lankarany, L. Zhang, F. Skinner (2024). A Software for Identification and Characterization of Theta Rhythms in the Hippocampus.

Step-by-Step Instructions for Analyzing Data using MATLAB App

1. Open MATLAB App

• Launch the MATLAB App and wait for the App Designer window to appear.
• Click on the "Run" button to open the user interface.

2. Upload Your File

• Place the "fieldtrip-master" folder and the "abfload.m" script in the same directory as the NeuroDominanceTracker GUI executable.
• Upload your file.
• Enter the sampling frequency (e.g., 5000 Hz).

3. Perform Analysis

• Click on the "Perform Analysis" button.
• The app will analyze the recording in one-minute windows.
• Messages will appear in the MATLAB command window for each window analyzed, indicating if a dominant mid-frequency is observed.
• Wait for all windows to be analyzed (e.g., 118 windows for a sample two-hour recording).

4. View Results

• Once analysis is complete, a table listing all identified episodes and their characteristics will be displayed.
• You can extract this table as an Excel sheet by clicking the appropriate button.

5. Visualize Identified Events

• Select an event and enter its corresponding minute (e.g., 109).
• Click the button to visualize the selected event.

6. Time-Frequency Analysis

• A spectrogram of the one-minute segment starting from the selected minute will be plotted.
• The normalized power of mid, low, and high-frequency bands over time will be shown.
• Dominant mid-frequency segments will be highlighted in green.
• The power spectrum of the first dominant mid-frequency segment will be plotted.

7. Save Features

• Click the button to save the features as an Excel file.

Sample EEG Data

The sample EDF (European Data Format) files used in this project were obtained from the following publication:

Brown, L. A., Hasan, S., Foster, R. G., & Peirson, S. N. (2016). The raw EEG data, 4 files (EEG_A to D), in European data format (.edf) [Data set]. Zenodo.
Available at: https://doi.org/10.5281/zenodo.160118
Direct access to the data can be found here: Zenodo Record.

FieldTrip Toolbox

This project leverages the FieldTrip toolbox to support different file formats, including FIF, EDF, and BDF.

Reference:
Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J.-M. (2011). FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. Computational Intelligence and Neuroscience, 2011, 156869.
You can access the FieldTrip toolbox here: https://www.fieldtriptoolbox.org/.