Changes for page SGA3 D1.2 Showcase 1

Last modified by fousekjan on 2022/07/04 18:31
From version 21.1
edited by fousekjan
on 2022/02/10 12:11
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To version 17.1
edited by gorkazl
on 2022/01/31 20:15
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61 61  
62 62  == Regional variability data ==
63 63  
64 -The first step of the regional variability workflow consists in loading the data from the Knowledge Graph, including the 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:
65 65  
66 66  1. Structural connectivity matrices,
67 67  1. GABA and AMPA receptor densities for each brain region, and
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69 69  
70 70  Link to the notebook:
71 71  
72 -* [[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]]
73 73  
74 74  (% style="text-align:center" %)
75 -[[image:download - 2022-02-10T130815.902.png||alt="region-wise gene expression heterogeneity"]]
75 +[[image:image-20220103095424-1.png]]
76 76  
77 77  == Fitting model parameters for models with regional bias ==
78 78  
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. 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.
80 80  
81 81  Link to the notebook:
82 82  
83 -* [[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]]
84 84  
85 -[[image:download - 2022-02-10T131102.033.png||alt="regional bias vs goodness of fit"]]
85 +[[image:image-20220103095948-1.png]]
86 86  )))
87 87  
88 88  
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