Last modified by mhashemi on 2024/12/03 18:26
From version 17.1
edited by mhashemi
on 2024/12/03 18:26
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To version 7.1
edited by mhashemi
on 2024/11/27 18:02
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1 -This tool was developed at INS in Marseille.
2 -Authors: M Hashemi, A Ziaeemehr, MM Woodman, J Fousek, S Petkoski, VK Jirsa
1 +{{{The integration of an individual’s brain
2 +imaging data in VBMs has improved patient-specific predictivity, although Bayesian
3 +estimation of spatially distributed parameters remains challenging even with state-
4 +of-the-art Monte Carlo sampling. VBMs imply latent nonlinear state space models
5 +driven by noise and network input, necessitating advanced probabilistic machine
6 +learning techniques for widely applicable Bayesian estimation. Here we present
7 +Simulation-based Inference on Virtual Brain Models (SBI-VBMs), and demonstrate
8 +that training deep neural networks on both spatio-temporal and functional fea-
9 +tures allows for accurate estimation of generative parameters in brain disorders.
10 +The systematic use of brain stimulation provides an effective remedy for the non-
11 +identifiability issue in estimating the degradation limited to smaller subset of con-
12 +nections. By prioritizing model structure over data, we show that the hierarchical
13 +structure in SBI-VBMs renders the inference more effective, precise and biologically
14 +plausible. This approach could broadly advance precision medicine by enabling fast
15 +and reliable prediction of patient-specific brain disorders.
3 3  
4 -Virtual Brain Models imply latent nonlinear state space models
5 -driven by noise and network input, necessitating advanced probabilistic
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 -functional features allows for accurate estimation of generative parameters in brain disorders.
17 +Code:
18 +}}}
10 10  
11 11  
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 -
14 -(% style="text-align: justify;" %)
15 15  Ref: [[https:~~/~~/iopscience.iop.org/article/10.1088/2632-2153/ad6230>>https://iopscience.iop.org/article/10.1088/2632-2153/ad6230]]
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 -}}}