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30	30	1. Dynamics of the model, and execution of a parameter study
31	31	1. Summary of the simulation results for the whole cohort
32	32
33		-Link to the notebook:
34		-
35		-* [[virtual_ageing/notebooks/1_BNM_for_resting_state.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/virtual_ageing/notebooks/1_BNM_for_resting_state.ipynb]]
36		-
37	37	[[image:image-20220103100841-2.png]]
38	38
39		-== Virtual ageing trajectories ==
40	40
41		-The second steps shows the investigation of virtual ageing trajectory for each subject. In this context, we are going to show
42		-
43		-1. What we mean by virtual ageing and what is the empirical basis to investigate this approach
44		-1. How we can virtually age a subject using whole-brain modelling
45		-1. How the increase structure-function relationship relates to virtual ageing
46		-
47		-Link to the notebook:
48		-
49		-* [[virtual_ageing/notebooks/2_virtual_ageing_trajectories.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/virtual_ageing/notebooks/2_virtual_ageing_trajectories.ipynb]]
50		-
51		-[[image:image-20220103101022-3.png]]
52		-
53		-(% class="wikigeneratedid" %)
54		-== Inference with SBI ==
55		-
56		-Last step of the inter-individual variability workflow
57		-
58		-
59		-Link to the notebook:
60		-
61		-* [[virtual_ageing/notebooks/3_inference_with_SBI.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/virtual_ageing/notebooks/3_inference_with_SBI.ipynb]]
62		-
63	63	== Regional variability data ==
64	64
65	65	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: 1) structural connectivity matrices, 2) GABA and AMPA receptor densities at each region, and 3) empirical resting-state fMRI data for fitting and validation of the simulations. The three datasets shall be characterised in the same parcellation.