8000 GitHub - gblackburne/Pyfurcate: Whole-brain modelling with Hopf bifurcations in PyTorch
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Pyfurcate

Code for phenomenological modelling of fMRI BOLD signals using coupled Stuart-Landau oscillators susceptible to pertubation.

Includes optimize_GEC_torch for optimising generative effective connectivity using stochastic gradient descent.

Citation

If you use this code in your research, kindly cite:

  • Deco (2017) The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core.
  • Deco (2019) Awakening: Predicting external stimulation to force transitions between different brain states.
  • Sanz Perl (2022) Strength-dependent perturbation of whole-brain model working in different regimes reveals the role of fluctuations in brain dynamics.
  • Ponce-Alvarez (2024) The Hopf whole-brain model and its linear approximation.
  • Luppi (2025) Competitive interactions shape brain dynamics and computation across species.

George Blackburne, Hanna Tolle, 2025.

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Whole-brain modelling with Hopf bifurcations in PyTorch

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