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An implementation of several well-known dynamic Functional Connectivity assessment methods.

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pydfc

An implementation of several well-known dynamic Functional Connectivity (dFC) assessment methods.

Simply install pydfc using the following steps:
  • conda create --name pydfc_env python=3.11
  • conda activate pydfc_env
  • pip install pydfc

The dFC_methods_demo.ipynb illustrates how to load data and apply each of the dFC methods implemented in the pydfc toolbox individually. The multi_analysis_demo.ipynb illustrates how to use the pydfc toolbox to apply multiple dFC methods at the same time on a dataset and compare their results.

For more details about the implemented methods and the comparison analysis see our paper.

  • Mohammad Torabi, Georgios D Mitsis, Jean-Baptiste Poline, On the variability of dynamic functional connectivity assessment methods, GigaScience, Volume 13, 2024, giae009, https://doi.org/10.1093/gigascience/giae009.

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An implementation of several well-known dynamic Functional Connectivity assessment methods.

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