This repository contains all the code used in our study to assess signal variability, oscillatory patterns, and electrode behavior, offering a modular, flexible framework for brain signal exploration. This toolkit was designed to evaluate cortical delamination through multi-electrode array (MEA) signal analysis.
We believe that understanding baseline electrical activity is key to characterizing oscillatory heterogeneity, which can signal early markers of pathological responses like seizures. While this work focuses on cortical dysplasia and delamination, the analysis pipeline can be generalized to other models and signal processing tasks.
So dive in, try it out, and feel free to reach out if you hit any roadblocks or have questions! 💬
Here’s a quick overview of the workflow:
Make sure to install the required Python libraries in a fresh environment.
👉 You can use a enviroment.yml or a virtual environment setup.
Convert your acquisition software output to HDF5 format using the MCS Py Data Tools.
Run Preprocessing.py to clean and prepare your raw LFP data. This step is essential 🧼
Use SlepianTapers.py for robust time-frequency decomposition using multitaper methods.
Run ElectrodeClustering.py to cluster electrodes based on extracted features.
Before diving deep, I highly encourage you to explore CommonBand.py — a method for extracting common oscillatory activity across your recordings. This is especially useful when comparing conditions like control vs. disease, as it reveals consistent rhythms that might otherwise be hidden 🧭.
Want to go further? Check out these optional but powerful scripts:
SignalClassification.py: Track how signal dynamics evolve over time using the electrode class labels.MI_signalModules.py: Quantify mutual information between different signal features.DirectMI.py: Reveal directed relationships in your data using transfer entropy 🔁
Found a bug? Have an idea? Curious about applying this to your own dataset? Don’t hesitate to get in touch — collaboration and curiosity are always welcome! 🌱
📫 Contact: