teppy 0.1.7

TMS-EEG Evoked Potential Analysis Framework

TEPpy

TMS-EEG Evoked Potential Analysis Framework
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Table of Contents

1. About The Project
   • Key Features
2. Getting Started
   • Dependencies
   • Installation
3. Usage
4. Citation
5. License
6. Contact

About The Project

TEPpy is a Python package for analyzing Transcranial Magnetic Stimulation combined with Electroencephalography (TMS-EEG) data. It provides tools for characterizing TMS-EEG evoked potential (TEP) temporal and spectral features, with automated peak detection and time-frequency analysis methods.

Key Features

• Convert MNE-Python Epochs objects to TEP objects
• Automatic detection of TEP peaks
• Automatic selection of most reponsive channels
• Time-frequency analysis using Stockwell transform
• Extraction of temporal and spectral features
• Visualization of temporal and spectral features
• Customizable analysis parameters for research flexibility

Analysis Workflow

Typical TEPpy analysis workflow from MNE Epochs to extracted features

Getting Started

Dependencies

• numpy>=2.0.1
• scipy>=1.14.0
• mne>=1.9.0
• matplotlib>=3.9.1
• stockwell>=1.2

Installation

Install from PyPI:

pip install teppy

Usage

import mne
from teppy import TEP

TEP.plot_summary()

timef = TEP.compute_timefreq()
timef.plot_natfreq1()

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Citation

License

Contact