Changes for page SGA3 D1.2 Showcase 1
Last modified by fousekjan on 2022/07/04 18:31
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... ... @@ -18,13 +18,7 @@ 18 18 19 19 The Jupyter notebooks in this collab will load all required Python modules including Siibra and The Virtual Brain, and the interfaces for launching the computationally demanding parts in the HPC infrastructure. 20 20 21 -(% class="box infomessage" %) 22 -((( 23 -(% class="box" %) 24 -((( 25 -Running the notebooks requires an EBRANS account with permissions to access the Lab and programmatic access to the Knowledge Graph API. In addition, to interact with the HPC infrastructure, the user needs access to an active allocation on the corresponding FENIX site. Lastly, the virtual ageing brain notebooks write data to the Bucket storage—please make a private working copy of this Collab using the notebook [[copy_showcase1_collab.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/copy_showcase1_collab.ipynb]]. 26 -))) 27 -))) 21 +Running the notebooks requires an EBRANS account with permissions to access the Lab and programmatic access to the Knowledge Graph API. In addition, to interact with the HPC infrastructure, the user needs access to an active allocation on the corresponding FENIX site. 28 28 29 29 == Simulation of resting-state activity == 30 30 ... ... @@ -67,7 +67,7 @@ 67 67 68 68 == Regional variability data == 69 69 70 -The first step of the regional variability workflow consists inloadingthe data from the Knowledge Graph,includingthe regional bias on the model. In this case we require:64 +The first step of the regional variability workflow loads the data from the Knowledge Graph and defines the regional bias on the model. In this case we require: 71 71 72 72 1. Structural connectivity matrices, 73 73 1. GABA and AMPA receptor densities for each brain region, and ... ... @@ -75,20 +75,20 @@ 75 75 76 76 Link to the notebook: 77 77 78 -* [[regional_variability/notebooks/1_ load_data.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/regional_variability/notebooks/1_load_data.ipynb]]72 +* [[regional_variability/notebooks/1_data_setup.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/regional_variability/notebooks/1_data_setup.ipynb]] 79 79 80 80 (% style="text-align:center" %) 81 -[[image: download-2022-02-10T130815.902.png||alt="region-wise gene expression heterogeneity"]]75 +[[image:image-20220103095424-1.png]] 82 82 83 83 == Fitting model parameters for models with regional bias == 84 84 85 -A series of simulations of the whole-brain network model are launched in the EBRAINS HPC facilities in order to identify the optimal model parameters leading to simulated resting-state brain activity that best resembles the empirically observed activity. In this branch of the showcase, brain regions are simulated using the Balanced Excitation-Inhibition model which allows to tune the E-I balance for every region individually, according to the empirically observed GABA and AMPA neuroreceptor densities.79 +A series of simulations of the whole-brain network model are launched in the EBRAINS HPC facilities in order to identify the optimal model parameters leading to simulated resting-state brain activity that best resembles the empirically observed activity. 86 86 87 87 Link to the notebook: 88 88 89 -* [[regional_variability/notebooks/2_parameter_swep.ipynb>>https://lab.ch.ebrains.eu/ hub/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/regional_variability/notebooks/2_parameter_swep.ipynb]]83 +* [[regional_variability/notebooks/2_parameter_swep_proto.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/regional_variability/notebooks/2_parameter_swep_proto.ipynb]] 90 90 91 -[[image: download-2022-02-10T131102.033.png||alt="regional bias vs goodness of fit"]]85 +[[image:image-20220103095948-1.png]] 92 92 ))) 93 93 94 94
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