Wiki source code of Simulation-based Inference on Virtual Brain Models of Disorders (SBI-VBMs)
Last modified by mhashemi on 2024/12/03 18:26
Hide last authors
| author | version | line-number | content |
|---|---|---|---|
 |
17.1 | 1 | This tool was developed at INS in Marseille. |
| 2 | Authors: M Hashemi, A Ziaeemehr, MM Woodman, J Fousek, S Petkoski, VK Jirsa | ||
| 3 | |||
| |
14.2 | 4 | Virtual Brain Models imply latent nonlinear state space models |
| |
9.1 | 5 | driven by noise and network input, necessitating advanced probabilistic |
| |
14.2 | 6 | machine learning techniques for widely applicable Bayesian estimation. |
| 7 | Here we present Simulation-based Inference on Virtual Brain Models (SBI-VBMs), | ||
| 8 | and demonstrate that training deep neural networks on both spatio-temporal and | ||
| |
9.1 | 9 | functional features allows for accurate estimation of generative parameters in brain disorders. |
| |
1.1 | 10 | |
| 11 | |||
| |
17.1 | 12 | Code: [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/SBI-VBM>>https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/SBI-VBM]] |
| |
13.2 | 13 | |
| |
8.1 | 14 | (% style="text-align: justify;" %) |
| |
7.1 | 15 | Ref: [[https:~~/~~/iopscience.iop.org/article/10.1088/2632-2153/ad6230>>https://iopscience.iop.org/article/10.1088/2632-2153/ad6230]] |
| |
17.1 | 16 | |
| 17 | {{{ | ||
| 18 | @article{SBI-VBM, | ||
| 19 | title={Simulation-based inference on virtual brain models of disorders}, | ||
| 20 | author={Hashemi, Meysam and Ziaeemehr, Abolfazl and Woodman, Marmaduke M and Fousek, Jan and Petkoski, Spase and Jirsa, Viktor K}, | ||
| 21 | journal={Machine Learning: Science and Technology}, | ||
| 22 | volume={5}, | ||
| 23 | number={3}, | ||
| 24 | pages={035019}, | ||
| 25 | year={2024}, | ||
| 26 | publisher={IOP Publishing} | ||
| 27 | } | ||
| 28 | }}} |