| The Bayesian Virtual Epileptic Patient: A probabilistic framework designed to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread M Hashemi, AN Vattikonda, V Sip, M Guye, F Bartolomei, MM Woodman, ... NeuroImage 217, 116839, 2020 | 115 | 2020 |
| Delineating epileptogenic networks using brain imaging data and personalized modeling in drug-resistant epilepsy HE Wang, M Woodman, P Triebkorn, JD Lemarechal, J Jha, B Dollomaja, ... Science Translational Medicine 15 (680), eabp8982, 2023 | 67 | 2023 |
| On the influence of prior information evaluated by fully Bayesian criteria in a personalized whole-brain model of epilepsy spread M Hashemi, AN Vattikonda, V Sip, S Diaz-Pier, A Peyser, H Wang, ... PLoS computational biology 17 (7), e1009129, 2021 | 38 | 2021 |
| Multi-scale dynamic mean field model (MDMF) relates resting-state brain dynamics with local cortical excitatory–inhibitory neurotransmitter homeostasis A Naskar, A Vattikonda, G Deco, D Roy, A Banerjee Network Neuroscience, 1-55, 2021 | 37 | 2021 |
| Data-driven method to infer the seizure propagation patterns in an epileptic brain from intracranial electroencephalography V Sip, M Hashemi, AN Vattikonda, MM Woodman, H Wang, J Scholly, ... PLOS Computational Biology 17 (2), e1008689, 2021 | 37 | 2021 |
| Does the regulation of local excitation–inhibition balance aid in recovery of functional connectivity? A computational account A Vattikonda, BR Surampudi, A Banerjee, G Deco, D Roy Neuroimage 136, 57-67, 2016 | 33 | 2016 |
| Amortized Bayesian inference on generative dynamical network models of epilepsy using deep neural density estimators M Hashemi, AN Vattikonda, J Jha, V Sip, MM Woodman, F Bartolomei, ... Neural Networks 163, 178-194, 2023 | 31 | 2023 |
| Identifying spatio-temporal seizure propagation patterns in epilepsy using Bayesian inference AN Vattikonda, M Hashemi, V Sip, MM Woodman, F Bartolomei, VK Jirsa Communications biology 4 (1), 1244, 2021 | 31 | 2021 |
| Fully Bayesian estimation of virtual brain parameters with self-tuning Hamiltonian Monte Carlo J Jha, M Hashemi, AN Vattikonda, H Wang, V Jirsa Machine Learning: Science and Technology 3 (3), 035016, 2022 | 21 | 2022 |
| Simulation-Based Inference for Whole-Brain Network Modeling of Epilepsy using Deep Neural Density Estimators M Hashemi, AN Vattikonda, J Jha, V Sip, MM Woodman, F Bartolomei, ... medRxiv, 2022.06. 02.22275860, 2022 | 12 | 2022 |
| Virtual Epileptic Patient (VEP): Data-driven probabilistic personalized brain modeling in drug-resistant epilepsy HE Wang, M Woodman, P Triebkorn, JD Lemarechal, J Jha, B Dollomaja, ... medRxiv, 2022.01. 19.22269404, 2022 | 3 | 2022 |
| Improving epileptogenic zone estimation using Bayesian inference on neural field models AN Vattikonda, MM Woodman, JD Lemarechal, D Daini, M Hashemi, ... medRxiv, 2023.10. 01.23296377, 2023 | 2 | 2023 |
| Effects of the spatial resolution of the Virtual Epileptic Patient on the identification of epileptogenic networks JD Lemaréchal, P Triebkorn, AN Vattikonda, M Hashemi, M Woodman, ... Imaging Neuroscience 2, 1-22, 2024 | 1 | 2024 |
| A method for inferring epileptogenicity of a brain region V Jirsa, M Hashemi, MM Woodman, V Sip, AN Vattikonda US Patent App. 17/916,128, 2023 | | 2023 |
| Model inversion techniques for seizure spread in individual brain networks V Sip, V Jirsa, M Hashemi, A Vattikonda, J Jha JOURNAL OF COMPUTATIONAL NEUROSCIENCE 49 (SUPPL 1), S95-S95, 2021 | | 2021 |
Meysam HashemiInstitut de Neurosciences des Systèmes Aix-Marseille UniversitéПотвърден имейл адрес: univ-amu.fr
