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81	81	(% class="wikigeneratedid" %)
82	82	== (b) Regional variability ==
83	83
84		-Aims at demonstrating the construction of whole-brain network models of the brain's activity, accounting for differences in receptor densities across cortical regions.
	84	+Aims at demonstrating the construction of whole-brain network models of the brain's activity accounting for differences in receptor densities across cortical regions.
85	85
86		-=== Loading the data from EBRAINS ===
	86	+=== Loading the data from EBRAINS via the //siibra// interface ===
87	87
88		-The first step of this workflow consists in loading the data from the Knowledge Graph via the //siibra interface//, including the regional bias on the model. In this case we require:
	88	+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:
89	89
90	90	1. Structural connectivity matrices,
91		-1. GABAa and AMPA receptor densities for each brain region, and
92		-1. empirical resting-state fMRI data for fitting and validation of the simulations.
	91	+1. GABA and AMPA receptor densities for each brain region, and
	92	+1. empirical resting-state fMRI data for fitting and validation of the simulations. The three datasets shall be characterised in the same parcellation.
93	93
94		-The three datasets shall be characterised in the same parcellation. Link to the notebook:
	94	+Link to the notebook:
95	95
96	96	* [[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]]
97	97
...	...	@@ -98,9 +98,9 @@
98	98	(% style="text-align:center" %)
99	99	[[image:download - 2022-02-10T130815.902.png||alt="region-wise gene expression heterogeneity"]]
100	100
101		-=== Fitting model parameters for models with regional bias ===
	101	+== Fitting model parameters for models with regional bias ==
102	102
103		-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 mean-field AdEx population model; specifically modified to account for the regional densities of GABAa and AMPA neuroreceptors. See the details following document.
	103	+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.
104	104
105	105	Link to the notebook:
106	106