lucasplagwitz / fmri-clustering

Task-based fMRI Clustering: Unveiling Activity Patterns

fMRI Clustering

This repository features Python code designed to perform data-driven analysis of sensory cortical processing, as detailed in the research paper titled Data-driven signal analysis of sensory cortical processing using high-resolution fMRI across different studies.

Tutorials

We offer a suite of analytical workflows specifically designed for data-driven examination of functional magnetic resonance imaging (fMRI) data. These workflows are demonstrated in notebooks that employ simulated data as examples. Currently, the repository encompasses the following types of analyses:

1. Line-Scanning - Amplitude (Correlation-based)
2. Line-Scanning - Amplitude (Euclidean-based)
3. Line-Scanning - Rise (Euclidean-based)
4. Slice - Amplitude (Correlation-based)
5. Slice - Amplitude (Euclidean-based)
6. Slice - Rise (Euclidean-based)

To accurately replicate the results presented in the paper, please submit a request for the data via email.

Citation

@article{Plagwitz23DDSA,
  author = {Lucas Plagwitz, Sangcheon Choi, Xin Yu, Daniel Segelcke, Esther Pogatzki-Zahn, Julian Varghese, Cornelius Faber, Bruno Pradier},
  title = {Data-driven signal analysis 
of sensory cortical processing using high-resolution 
fMRI across different studies},
  doi = {https://doi.org/10.1101/2023.08.01.551587}
  year = {2023},
}