fmri-toolkit 0.1.0

A comprehensive toolkit for fMRI data analysis and visualization

FMRI Toolkit

A comprehensive Python toolkit for functional Magnetic Resonance Imaging (fMRI) data analysis and visualization.

Features

Core Analysis

• Stimulus Detection: Multiple statistical tests for detecting brain activation
  • Real-valued tests: t-test, Wilcoxon, on/off difference, HRF GLM
  • Complex-valued tests: Hotelling's T², Wilks-Lambda, generalized LRT
  • Support for 1D-4D data
• Post-hoc Processing: FDR correction and spatial clustering (6-, 18-, or 26-connectivity)
• P-value Adjustment: Multiple testing correction methods (Bonferroni, Holm, Benjamini-Hochberg)

Visualization

• 3D Brain Visualization: Interactive 3D brain maps using Plotly
• 2D Slice Visualization: Sagittal, axial, and coronal slice views
• Regional Visualization: ROI-based 3D visualization
• Comparison Tools: Side-by-side comparison of multiple p-value maps (2D and 3D)

ROI Analysis

• Phase 1: Detect activated regions of interest using statistical tests
• Phase 2: ROI-based tensor-on-tensor regression analysis

Time Series Analysis

• Time Series Visualization: Interactive time series exploration
• Forecasting: Time series forecasting capabilities for fMRI data

Data Simulation

• Generate synthetic fMRI data with specified activation regions and stimulus timing

Installation

From PyPI (when published)

pip install fmri-toolkit

From source

git clone https://github.com/yourusername/fmri-toolkit.git
cd fmri-toolkit
pip install -e .

Quick Start

import fmri_toolkit as fmri

# Load fMRI data
data = fmri.fmri_load_mat('path/to/data.mat')

# Perform stimulus detection
result = fmri.fmri_stimulus_detect(
    fmridata=data,
    mask=mask,
    stimulus_idx=stimulus_indices,
    rest_idx=rest_indices,
    method='t-test'
)

# Apply post-hoc correction
processed = fmri.fmri_post_hoc(
    result,
    alpha=0.05,
    method='BH',
    spatial_cluster=True
)

# Visualize results in 3D
fmri.fmri_3dvisual(
    processed,
    title='Brain Activation Map',
    color_scheme='hot'
)

Requirements

• Python >= 3.8
• NumPy >= 1.20.0
• SciPy >= 1.7.0
• Pandas >= 1.3.0
• Matplotlib >= 3.4.0
• Plotly >= 5.0.0
• And other dependencies (see pyproject.toml)

Documentation

For detailed documentation, examples, and API reference, visit the documentation.

Examples

Check the examples/ directory for complete usage examples:

• runall.py: Full analysis pipeline demonstration

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use this toolkit in your research, please cite:

@software{fmri_toolkit,
  title={FMRI Toolkit: A Python Package for fMRI Data Analysis},
  author={Johnny In},
  year={2024},
  url={https://github.com/yourusername/fmri-toolkit}
}

Support

For issues, questions, or suggestions, please open an issue on GitHub.