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Last modified by mhashemi on 2025/03/12 11:20
From version 17.1
edited by mhashemi
on 2025/03/12 11:15
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To version 17.2
edited by mhashemi
on 2025/03/12 11:16
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17 17  This collab contains access to the notebooks and reading materials that will be used during the EBRAINS Baltic-Nordic summer school 2024 [[https:~~/~~/lsmu.lt/en/events/ebrains/>>https://lsmu.lt/en/events/ebrains/]].
18 18  
19 -The objective is to give to the participants an overview to building whole-brain network models with TVB. We will begin with the [[First steps of TVB>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/1_TVB_First_steps.ipynb||style="background-color: rgb(255, 255, 255);"]], where we will describe the building blocks of TVB through the paradigm of resting state activity. This will be followed by [[Modelling Epilepsy>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/2_TVB_Modelling_Epilepsy.ipynb||style="background-color: rgb(255, 255, 255);"]], where seizure propagation will be modeled. Then, there is one tutorial describing a deeper analysis of [[BOLD monitors>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/3_TVB_BOLD_digging_deeper.ipynb||style="background-color: rgb(255, 255, 255);"]].  Finally, a [[Bayesian approach>>https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/EITN_tutorial||style="background-color: rgb(255, 255, 255);"]] is used on synthetic data to infer the posterior of the parameters.  These can all be found in the drive and accessed through the lab.
19 +The objective is to give to the participants an overview to building whole-brain network models with TVB. We will begin with the [[First steps of TVB>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/1_TVB_First_steps.ipynb||style="background-color: rgb(255, 255, 255);"]], where we will describe the building blocks of TVB through the paradigm of resting state activity. This will be followed by [[Modelling Epilepsy>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/2_TVB_Modelling_Epilepsy.ipynb||style="background-color: rgb(255, 255, 255);"]], where seizure propagation will be modeled. Then, there is one tutorial describing a deeper analysis of [[BOLD monitors>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/TVB%20EBRAINS%20Baltic-Nordic%20school%202024/3_TVB_BOLD_digging_deeper.ipynb||style="background-color: rgb(255, 255, 255);"]].  Finally, a [[Bayesian approach>>https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/EITN_tutorial||style="background-color: rgb(255, 255, 255);"]] is used on synthetic data to infer the posterior of the parameters.  These can all be found in the drive and accessed through the lab.
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21 21  = Requirements =
22 22