Data analysis for Gauthey et al. 2025 [1]. This repository contains the code to reproduce the figures in [1] and a signal extraction pipeline. The raw data for a representative trial can be found at https://doi.org/10.5281/zenodo.17613016 and the preprocessed data can be found at https://doi.org/10.5281/zenodo.17618684. Both can also be found at https://doi.org/10.34770/s5hx-1x75.

Dependencies

To run the analysis code you will need scipy, numpy, pandas, scikit-learn. For the signal extraction pipeline you will need ANTsPy (https://github.com/ANTsX/ANTsPy.git). For visualizing ROIs on slices you will need the packages included in roi_plotting_requirements.txt.

Signal extraction pipeline

To run the signal extraction pipeline you need to follow these steps:

1. Run Sliding_window.m on raw TIFF files to have the data in the right ordering
2. Run batch_tiff_to_dff_mean_brain_RigE.sh to create a mean brain
3. Run batch_tiff_to_dff_mc_RigE.sh to compute motion correction
4. Run batch_tiff_to_dff_concat_RigE.sh
5. Run batch_signal_to_supervoxel_roi_RigE.sh to extract signal

Reference

[1] Gauthey W., Lin A., Ahmed O.M., Leifer A.M., Murthy M., Thiberge S.Y., 2025 (https://www.biorxiv.org/content/10.1101/2025.06.18.660371v1)

Credits

Albert Lin, Wayan Gauthey, Sama Ahmed