[Eeglablist] Brain network&EEG

[Tarik S Bel-Bahar]

Hello Sadatnejad, Some quick notes and some recent literature (right
below) where
you might find some useful tools or ideas. all the best.

>
> Sounds like a cool project@ ICA-EEG provides a source space with a good
> number of brain network nodes. One can of course also go into "distributed
> source space", where tools built for fmri voxel space can be used on it.
> Brainstorm, Fieldtrip, and MNE Python are various ways to get distributed
> source estimates for your  network analyses, and it's possible to import
> eeglab data into them. I believe EEGNET (see below) goes from eeglab into
> brainstorm and then Brain Connectivity Toolbox. See also Calhoun's group at
> Mind research network for cool approaches to dynamic functional networks.
> If you find a pipeline that works for you, please consider sharing your
> solution with the list so users can benefit from your experience.
>
> All citations below easily googlable.
> //
>
> Pezoulas, V. C., Athanasiou, A., Nolte, G., Zervakis, M., Fratini, A.,
> Fotiadis, D. I., & Klados, M. A. (2018, March). FCLAB: An EEGLAB module for
> performing functional connectivity analysis on single-subject EEG data. In Biomedical
> & Health Informatics (BHI), 2018 IEEE EMBS International Conference on
> (pp. 96-99). IEEE.
>
>
> Hassan, M., Shamas, M., Khalil, M., El Falou, W., & Wendling, F. (2015).
> EEGNET: an open source tool for analyzing and visualizing M/EEG connectome. PloS
> one, 10(9), e0138297.
>
> Fahrenfort, J. J., Van Driel, J., Van Gaal, S., & Olivers, C. N. (2018).
> From ERPs to MVPA using the Amsterdam Decoding and Modeling toolbox (ADAM). Frontiers
> in neuroscience, 12.
>
> Bahrami, M., Laurienti, P. J., & Simpson, S. L. (2019). A MATLAB toolbox
> for multivariate analysis of brain networks. Human brain mapping, 40(1),
> 175-186.
>
>
>

> Allen, E. A., Damaraju, E., Eichele, T., Wu, L., & Calhoun, V. D. (2018).
> EEG signatures of dynamic functional network connectivity states. *Brain
> topography*, *31*(1), 101-116.
>



>
>
> //
>
> Wang, B. C., Norcia, A. M., & Kaneshiro, B. (2017). MatClassRSA: A Matlab
> toolbox for M/EEG classification and visualization of proximity matrices.
> bioRxiv, 194563.
>
> Baggio, H. C., Abos, A., Segura, B., Campabadal, A., Garcia‐Diaz, A.,
> Uribe, C., ... & Junque, C. (2018). Statistical inference in brain graphs
> using threshold‐free network‐based statistics. Human brain mapping, 39(6),
> 2289-2302.
>
> Heitmann, S., Aburn, M. J., & Breakspear, M. (2018). The Brain Dynamics
> Toolbox for Matlab. *Neurocomputing*, *315*, 82-88.
>
>
>
> Soch, J., & Allefeld, C. (2018). MACS–a new SPM toolbox for model
> assessment, comparison and selection. Journal of neuroscience methods.
>
> Dong, L., Luo, C., Liu, X., Jiang, S., Feng, H., Li, J., ... & Yao, D.
> (2018). Neuroscience information toolbox: an open source toolbox for
> EEG-fMRI multimodal fusion analysis. Frontiers in neuroinformatics, 12,
> 56.
>
> Bode, S., Feuerriegel, D., Bennett, D., & Alday, P. M. (2018). The
> Decision Decoding ToolBOX (DDTBOX)–A multivariate pattern analysis toolbox
> for event-related potentials. Neuroinformatics, 1-16.
>
> //
>
>
>
> Sizemore, A. E., & Bassett, D. S. (2018). Dynamic graph metrics: Tutorial,
> toolbox, and tale. *NeuroImage*, *180*, 417-427.
>
> Mijalkov, M., Kakaei, E., Pereira, J. B., Westman, E., Volpe, G., &
> Alzheimer's Disease Neuroimaging Initiative. (2017). BRAPH: A graph theory
> software for the analysis of brain connectivity. PloS one, 12(8),
> e0178798.
>
> Wang, J., Wang, X., Xia, M., Liao, X., Evans, A., & He, Y. (2015). GRETNA:
> a graph theoretical network analysis toolbox for imaging connectomics. *Frontiers
> in human neuroscience*, *9*, 386.
>
> Kruschwitz, J. D., List, D., Waller, L., Rubinov, M., & Walter, H. (2015).
> GraphVar: A user-friendly toolbox for comprehensive graph analyses of
> functional brain connectivity. *Journal of neuroscience methods*, *245*,
> 107-115.
>
>
>
> Liao, W., Wu, G. R., Xu, Q., Ji, G. J., Zhang, Z., Zang, Y. F., & Lu, G.
> (2014). DynamicBC: a MATLAB toolbox for dynamic brain connectome analysis. *Brain
> connectivity*, *4*(10), 780-790.
>
>
> \\
>
>
> Moezzi, B., Hordacre, B., Berryman, C., Ridding, M. C., & Goldsworthy, M.
> R. (2018). Test-retest reliability of functional brain network
> characteristics using resting-state EEG and graph theory. *bioRxiv*,
> 385302.
>
> Colclough, G. L., Woolrich, M. W., Harrison, S. J., López, P. A. R.,
> Valdes-Sosa, P. A., & Smith, S. M. (2018). Multi-subject hierarchical
> inverse covariance modelling improves estimation of functional brain
> networks. *NeuroImage*, *178*, 370-384.
>
> Bassett, D. S., Zurn, P., & Gold, J. I. (2018). On the nature and use of
> models in network neuroscience. *Nature Reviews Neuroscience*, 1.
>
> Gili, T., Ciullo, V., & Spalletta, G. (2018). Metastable states of
> multiscale brain networks are keys to crack the timing problem. *Frontiers
> in computational neuroscience*, *12*.
>
> Khambhati, A. N., Sizemore, A. E., Betzel, R. F., & Bassett, D. S. (2018).
> Modeling and interpreting mesoscale network dynamics. *NeuroImage*, *180*,
> 337-349.
>
> Avena-Koenigsberger, A., Misic, B., & Sporns, O. (2018). Communication
> dynamics in complex brain networks. *Nature Reviews Neuroscience*, *19*(1),
> 17.
>
>
>
> Nüßing, A., Piastra, M. C., Schrader, S., Miinalainen, T., Brinck, H.,
> Wolters, C. H., & Engwer, C. (2019). duneuro-A software toolbox for forward
> modeling in neuroscience. arXiv preprint arXiv:1901.02874.
>
> Vorwerk, J., Oostenveld, R., Piastra, M. C., Magyari, L., & Wolters, C. H.
> (2018). The FieldTrip-SimBio pipeline for EEG forward solutions. Biomedical
> engineering online, 17(1), 37.
>
> Gonzalez-Moreira, E., Paz-Linares, D., Martinez-Montes, E., & Valdes-Sosa,
> P. A. (2018). Third Generation MEEG Source Connectivity Analysis Toolbox
> (BC-VARETA 1.0) and Validation Benchmark. arXiv preprint arXiv:1810.11212.
>
>
>
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