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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.

  • Torabi M, Mitsis GD, Poline JB. On the variability of dynamic functional connectivity assessment methods. bioRxiv. 2023:2023-07.

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  • Jupyter Notebook 89.0%
  • Python 11.0%