Published December 30, 2025 | Version v1.1.0
Software Open

TranCIT: Transient Causal Interaction Toolbox

Authors/Creators

  • 1. School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
  • 2. International Center for Primate Brain Research (ICPBR), Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences (CAS), Shanghai, China
  • 3. Computational Neuroscience, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden 01307, Germany; Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen 72076, Germany

Description

A Python package for quantifying causal relationships in multivariate time series data, with a focus on transient neural events and neuroscience applications. TranCIT implements advanced causality measures including Dynamic Causal Strength (DCS), relative Dynamic Causal Strength (rDCS), Granger causality, and transfer entropy, specifically designed for analyzing transient neural interactions.

Files

CMC-lab/TranCIT-v1.1.0.zip

Files (2.5 MB)

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Additional details

Related works

Is documented by
https://trancit.readthedocs.io (URL)
Is identical to
https://pypi.org/project/trancit/ (URL)
Is supplement to
https://github.com/CMC-lab/TranCIT (URL)

Software

Repository URL
https://github.com/CMC-lab/TranCIT