Dynamic Causal Modeling in Probabilistic Programming Languages
The aim is to provide inference services for Dynamical Causal Modeling of Event-Related Potentials (ERPs) measured with EEG/MEG, using SATO Probabilistic Programming Languages (PPLs):
Numpyro: https://num.pyro.ai/en/stable/
Blackjax: https://blackjax-devs.github.io/blackjax/
PyMC: https://www.pymc.io/welcome.html
Stan: https://mc-stan.org/
Notebooks:
https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/DCM_ERP_NumPyro
@article{Baldy2024AutoDCM, title={Dynamic Causal Modeling in Probabilistic Programming Languages}, author={Baldy, Nina and Woodman, Marmaduke and Jirsa, Viktor and Hashemi, Meysam}, journal={bioRxiv}, pages={2024--11}, year={2024}, publisher={Cold Spring Harbor Laboratory} }