Last modified by fousekjan on 2022/05/23 22:36
From version 15.3
edited by fousekjan
on 2020/06/26 15:44
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To version 4.1
edited by fousekjan
on 2020/06/12 17:42
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Summary

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1 -tvb|the virtual brain|resting state|fmri|eeg
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2 2  (((
3 3  (% class="container" %)
4 4  (((
5 -= TVB resting state dataset =
5 += My Collab's Extended Title =
6 6  
7 -Synthetic resting state recordings of simultaneous fMRI + EEG
7 +My collab's subtitle
8 8  )))
9 9  )))
10 10  
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12 12  (((
13 13  (% class="col-xs-12 col-sm-8" %)
14 14  (((
15 -This dataset contains 10 minutes of resting state fMRI and EEG time series simulated with  brain network model (Sanz-Leon et al., 2015, 2013) implemented in [[The Virtual Brain>>url:https://www.thevirtualbrain.org/]]. More precise information on the model used to generate these data is deliberately not provided here. The data will be available for a period of time without the model description to get unbiased feedback from the community analyzing empirical data. The model description will be published in a separate document.
15 += What can I find here? =
16 16  
17 -== Parcellation and Structural Connectivity ==
17 +* Notice how the table of contents on the right
18 +* is automatically updated
19 +* to hold this page's headers
18 18  
19 -{{code}}
20 -sub-<label>/connectivity/
21 -├── sub-<label>_atlas-dk_conndata-network_connectivity.json
22 -├── sub-<label>_atlas-dk_desc-distance_conndata-network_connectivity.tsv
23 -└── sub-<label>_atlas-dk_desc-weight_conndata-network_connectivity.tsv
24 -{{/code}}
21 += Who has access? =
25 25  
26 -The structural connectivity is stored in two separate .tsv files containing the weights (au) and tract lengths (mm) matrices ordered as sources x targets. The 84 regions are defined by the FreeSurfer parcellation by Desikan-Killiany Atlas (Desikan et al, 2006). Mapping of region labels to names is defined in **dk_atlas.tsv**.
27 -
28 -(% style="text-align:center" %)
29 -[[image:sub-001_connectome.png||alt="connectome"]]
30 -
31 -== BOLD fMRI ==
32 -
33 -{{code}}
34 -sub-<label>/func/
35 -├── sub-<label>_task-rest_atlas-dk_desc-sim_timeseries.json
36 -└── sub-<label>_task-rest_atlas-dk_desc-sim_timeseries.tsv.gz
37 -{{/code}}
38 -
39 -The simulated BOLD (TR=2) time series for the ROIs is stored as compressed **.tsv** file with columns defined in the json sidecar.
40 -
41 -(% style="text-align:center" %)
42 -[[image:sub-001_bold_with_fc.png||alt="bold"]]
43 -
44 -== EEG ==
45 -
46 -{{code}}
47 -sub-<label>/eeg
48 -├── sub-<label>_task-rest_desc-sim_coordsystem.json
49 -├── sub-<label>_task-rest_desc-sim_eeg.eeg
50 -├── sub-<label>_task-rest_desc-sim_eeg.json
51 -├── sub-<label>_task-rest_desc-sim_eeg.vhdr
52 -├── sub-<label>_task-rest_desc-sim_eeg.vmrk
53 -└── sub-<label>_task-rest_desc-sim_electrodes.tsv
54 -{{/code}}
55 -
56 -The EEG was simulated using a montage for HydroCel Geodesic Sensor Net with 256 electrodes. The raw data sampled at 256Hz was only high-pass filtered (FIR window length 845 samples, 1Hz cutoff), and stored in the [[BrainVision triplet format>>url:https://mne.tools/stable/generated/mne.io.read_raw_brainvision.html]] (**.eeg**, **.vmrk**, **.vhdr**). The electrode labels and locations are listed in the ***_electrodes.tsv** file.
57 -
58 -(% style="text-align:center" %)
59 -[[image:sub-001_eeg_traces.png||alt="eeg traces"]]
60 -
61 -(% style="text-align:center" %)
62 -[[image:sub-002_eeg_psd.png||alt="eeg psd"]]
63 -
64 -== [[image:sub-002_sensors.png||alt="eeg sensors"]] ==
65 -
66 -== References ==
67 -
68 -Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., Albert, M. S., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980.
69 -
70 -Sanz-Leon, P., Knock, S. A., Woodman, M. M., Domide, L., Mersmann, J., McIntosh, A. R., & Jirsa, V. (2013). The Virtual Brain: a simulator of primate brain network dynamics. Frontiers in neuroinformatics, 7.
71 -
72 -Sanz-Leon, P., Knock, S. A., Spiegler, A., & Jirsa, V. K. (2015). Mathematical framework for large-scale brain network modeling in The Virtual Brain. NeuroImage, 111, 385–430.
23 +Describe the audience of this collab.
73 73  )))
74 74  
26 +
75 75  (% class="col-xs-12 col-sm-4" %)
76 76  (((
77 77  {{box title="**Contents**"}}
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