results publications & models

Selected publications

Dynamic causal modelling in probabilistic programming languages: Nina Baldy, Marmaduke Woodman, Viktor K. Jirsa, Meysam Hashemi; June 4 2025; Journal of the Royal Society Interface / DOI: 10.1098/rsif.2024.0880
Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models: Abolfazl Ziaeemehr, Marmaduke Woodman, Lia Domide, Spase Petkoski, Viktor Jirsa, Meysam Hashemi; May 21 2025; eLife / DOI: 10.7554/eLife.106194.1
The virtual multiple sclerosis patient: Sorrentino P, Pathak A, Ziaeemehr A, Lopez ET, Cipriano L, Romano A, Sparaco M, Quarantelli M, Banerjee A, Sorrentino G, Jirsa V.; May 24 2024; iScience / DOI: 10.1016/j.isci.2024.110101

The virtual multiple sclerosis patient: This repository contains the code and data accompanying the paper "The Virtual Multiple Sclerosis Patient"
Inference on macroscopic dynamic of spiking neurons: This is a repo to make inference on a mean-filed model of spiking QIF neurons, using Optimization (DE/PSO), Simulation-based Inference (SBI), Hamiltonian Monte Carlo (HMC), and Neural ODEs.
Simulation-based inference on virtual brain models of disorders: This repository contains the code for Bayesian estimation of generative parameters in virtual brain disorders using deep neural density estimators
Dynamic Causal Modeling in Probabilistic Programming Languages: This repository provides automatic Dynamical Causal Modeling of Event-Related Potentials, using the SATO Probabilistic Programming Languages.
Virtual Brain Inference (VBI): This open source toolkit provides fast simulations, taxonomy of feature extraction, and probabilistic ML algorithms, for the state-of-the-art whole-brain network models.