Wiki source code of Mapping of relevant HBP atlas data to TVB simulation inputs
Last modified by dicksche on 2022/05/23 22:23
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1 | == Mapping of relevant HBP atlas data to necessary TVB simulation inputs == | ||
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3 | ==== Authors: L. Zehl, H. Wang, J. Fousek, S. Köhnen, V. Jirsa, T. Dickscheid ==== | ||
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5 | === Parcellation === | ||
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7 | Requirement: TVB requires a full coverage parcellation of the cortex and subcortical structures providing the following information for each parcel/region: | ||
8 | |||
9 | * label | ||
10 | * centroid | ||
11 | * volume | ||
12 | * surface area | ||
13 | * classification into cortical or subcortical region | ||
14 | |||
15 | Suitable data: The HBP atlas uses the JuBrain probabilistic cytoarchitectonic maps as the most important structural parcellation, which will achieve full coverage in the version planned for release at end of SGA2 [previous versions with partial coverage parcellation: https:~/~/doi.org/10.25493%2FQ3ZS-NV6, https:~/~/doi.org/10.25493%2F8EGG-ZAR]. This full coverage parcellation will be provided to TVB with the above listed information for the reference space MNI ICBM 152 [2009c, nonlinear, asymmetric]. | ||
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17 | === Connectivity matrices === | ||
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19 | Requirement: TVB requires two connectivity matrices defined for the parcellation above: | ||
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21 | * connectivity weight matrix | ||
22 | * connectivity delay matrix | ||
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24 | Suitable data: For the regions of the JuBrain cytoarchitectonic atlas, the HBP atlas can provide structural connectivity from different cohorts. The initial solution will be based on the 1000 brains cohort [doi.org/10.25493/61QA-KP8]. The atlas can provide: | ||
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26 | * average length of DTI tractograms connecting two regions (connectivity delay) [based on the storage requirements of corresponding calculations this measurement has to be performed on an HPC platform; the necessary HPC access has to be requested] | ||
27 | * number of fibre bundles connecting two regions (connectivity weight) [preliminary results were already measured] | ||
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29 | The publication of both connectivity matrices of the 1000Brains study is planned. | ||
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31 | === Regional microstructural characterizations === | ||
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33 | Requirement: For carrying out multiscale simulations, the TVB model can be enriched with cellular or electrophysiological parameters for the regions in a full coverage parcellation of the cortex and subcortical structures. | ||
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35 | Suitable data: In principle, the HBP atlas can provide data with cellular or electrophysiological parameters for the JuBrain regions from different cohorts. An initial selection could be: | ||
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37 | * Samples of density measurements (average and standard deviation) for a selection of 16 receptors for regions defined via the same cytoarchitectonic mapping technique used in the JuBrain cytoarchitectonic atlas. Note: The type of selected receptors could differ between regions, and the receptor density measurements are not yet available for a subset of 31 brain regions. Find here the total list of receptors and measured regions: | ||
38 | ** receptor (binding site for … , labelled with … ): | ||
39 | ** AMPA (glutamate; [³H]AMPA) | ||
40 | ** kainate (glutamate; [³H]kainate) | ||
41 | ** NMDA (glutamate; [³H]MK-801) | ||
42 | ** mGluR2/3 (glutamate; [³H] LY 341 495) | ||
43 | ** GABAA (GABA; [³H]muscimol) | ||
44 | ** GABAB (GABA; [³H] CGP54626) | ||
45 | ** GABAA/BZ (benzodiazepine; [³H]flumazenil) | ||
46 | ** muscarinic M₁ (acetylcholine; [³H]pirenzepine) | ||
47 | ** muscarinic M₂ (acetylcholine; [³H]oxotremorine-M) | ||
48 | ** muscarinic M₃ (acetylcholine; [³H]4-DAMP) | ||
49 | ** nicotinic α₄β₂ (acetylcholine; [³H]epibatidine) | ||
50 | ** α₁ (noradrenalin; [³H]prazosin) | ||
51 | ** α₂ (noradrenalin; [³H]UK-14,304) | ||
52 | ** 5-HT₁A (serotonin; [³H]8-OH-DPAT) | ||
53 | ** 5-HT₂ (serotonin; [³H]ketanserin) | ||
54 | ** D₁ (dopamine; [³H]SCH23390) | ||
55 | * measured brain regions (currently released dataset): | ||
56 | ** Area 3b (https:~/~/doi.org/10.25493%2FTZBY-96W) | ||
57 | ** Area 4p (https:~/~/doi.org/10.25493%2FJ5JR-YH0) | ||
58 | ** Area 7A (https:~/~/doi.org/10.25493%2FDQJ7-KC8) | ||
59 | ** Area 9 (https:~/~/doi.org/10.25493%2F97BA-87Y) | ||
60 | ** Area 44d (https:~/~/doi.org/10.25493%2FYQCR-1DQ) | ||
61 | ** Area 44v (https:~/~/doi.org/10.25493%2FP82M-PVM) | ||
62 | ** Area 45 (https:~/~/doi.org/10.25493%2FQFSY-YWC) | ||
63 | ** Area 46 (https:~/~/doi.org/10.25493%2FJHA2-ACG) | ||
64 | ** Area 47 (https:~/~/doi.org/10.25493%2F4M1R-KCP) | ||
65 | ** Area FG1 (https:~/~/doi.org/10.25493%2FQN6K-CHN) | ||
66 | ** Area FG2 (https:~/~/doi.org/10.25493%2FVFCW-HXZ) | ||
67 | ** Area hOc1 (https:~/~/doi.org/10.25493%2FP8SD-JMH) | ||
68 | ** Area PF (https:~/~/doi.org/10.25493%2FVSFY-EYF) | ||
69 | ** Area PFcm (https:~/~/doi.org/10.25493%2F5QDP-ARH) | ||
70 | ** Area PFm (https:~/~/doi.org/10.25493%2FFS3T-2R8) | ||
71 | ** Area PFop (https:~/~/doi.org/10.25493%2F9G1P-02S) | ||
72 | ** Area PFt (https:~/~/doi.org/10.25493%2FE7PM-FDC) | ||
73 | ** Area PGa (https:~/~/doi.org/10.25493%2F62W8-RYF) | ||
74 | ** Area PGp (https:~/~/doi.org/10.25493%2FX71T-HZ) | ||
75 | ** Area Te1 (https:~/~/doi.org/10.25493%2FAHX0-9PU) | ||
76 | ** Area Te2 (https:~/~/doi.org/10.25493%2FC279-428) | ||
77 | ** Globus Pallidus (https:~/~/doi.org/10.25493%2FTPRG-5VH) | ||
78 | ** Hippocampus, CA - stratum cellulare (https:~/~/doi.org/10.25493/4SFG-TX) | ||
79 | ** Hippocampus, CA - stratum moleculare (https:~/~/doi.org/10.25493/W6VW-Z00) | ||
80 | ** Hippocampus, CA1 (https:~/~/doi.org/10.25493/6YHV-3BT) | ||
81 | ** Hippocampus, CA2 (https:~/~/doi.org/10.25493/TFY5-0R4) | ||
82 | ** Hippocampus, CA3 (https:~/~/doi.org/10.25493/W5N5-PVX) | ||
83 | ** Hippocampus, DG (https:~/~/doi.org/10.25493/4ZFH-RPU) | ||
84 | ** Putamen (https:~/~/doi.org/10.25493%2F4GZ1-SHH) | ||
85 | ** Thalamic nucleus, anterior (https:~/~/doi.org/10.25493%2FKKTT-1TK) | ||
86 | ** Thalamic nucleus, mediodorsal (https:~/~/doi.org/10.25493%2FGKY8-NZR) | ||
87 | * The HBP atlas include the BigBrain, a high-resolution whole brain 3D model reconstructed from histological sections that were stained for neuronal cell bodies. To compute cell densities for JuBrain regions, it is necessary to define 3D maps in the BigBrain, which correspond to the cytoarchitectonic areas defined for the JuBrain atlas. | ||
88 | ** optical cell density measurement: the image intensities and resolution of the BigBrain provide the possibility to estimate optically neuronal cell densities. Therefore the atlas can provide region-specific statistics of gray-values. | ||
89 | ** direct cell density measurement (SGA3): by computing even higher resolution reconstructions at the level of 1 micrometer for regions of interest of the BigBrain, segmentation of individual neuronal cells is possible and could provide more realistic measures of cell density. Such data is available for some first samples of visual areas, and will be collected for more areas and sample locations in SGA3. | ||
90 | * Also anchored to the HBP atlas is a large number of sEEG recording sites of different cohorts. For SGA3 it is planned to aggregate potentially interesting electrophysiological parameters of sites located in each JuBrain region (e.g., dominant frequency band in resting state conditions). | ||
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92 | (% class="col-xs-12 col-sm-4" %) | ||
93 | ((( | ||
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