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Author

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1		-XWiki.fousekjan
	1	+XWiki.gorkazl

Content

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78	78	* [[virtual_ageing/notebooks/3_inference_with_SBI.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/virtual_ageing/notebooks/3_inference_with_SBI.ipynb]]
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	80	+== ==
	81	+
80	80	== b. Regional variability – Receptor density maps ==
81	81
82	82	Aims at demonstrating the construction of whole-brain network models of the brain's activity, accounting for differences in receptor densities across cortical regions.
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91	91
92	92	The three datasets are characterised in the same parcellation. Link to the notebook:
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94		-* [[regional_variability/notebooks/1_load_data.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/notebooks/1_load_data.ipynb]]
	96	+* [[regional_variability/1_load_fMRI_data.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/1_load_fMRI_data.ipynb]]
	97	+* [[regional_variability/2_retrieve_receptor_maps.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/2_retrieve_receptor_maps.ipynb]]
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96	96	[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/download%20-%202022-02-10T130815.902.png?rev=1.1||alt="region-wise gene expression heterogeneity"]]
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98	98	=== Fitting model parameters with regional bias ===
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100		-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 in the 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 mean-field AdEx population model; specifically modified to account for the regional densities of GABAa and AMPA neuroreceptors. We provide two versions of the calculations, developed during the course of SGA3 of the HBP, in order to accelerate vast parametric sweeps over standard TVB simulation. The first employs the "RateML" to run TVB simulation on GPUs and the second is based on a novel TVB backend running on C++.
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102		-Link to the notebook:
	105	+Link to the notebooks:
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104		-* [[regional_variability/notebooks/2_parameter_swep.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/notebooks/2_parameter_swep.ipynb]]
	107	+* [[regional_variability/notebooks/3a_vast_paramsweep_GPU.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/3a_vast_paramsweep_GPU.ipynb]]
	108	+* [[regional_variability/notebooks/3b_vast_paramsweep_TVBCpp.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/3b_vast_paramsweep_TVBCpp.ipynb]]
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106	106	[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/download%20-%202022-02-10T131102.033.png?rev=1.1||alt="regional bias vs goodness of fit"]]
107	107	)))