Please send any questions about the source codes directly to the maintainers of specific repositories by opening an issue in the specific repository you are interested in.

Repositories

• Alpha synchrony in visual attention [1]
  • R code for analyzing data from a visual attention task
• Fidelity-weighting
  • Improve inverse operators used with parcellations
• Hyperedges [2, 3]
  • State-of-art correction for spurious correlations in MEG connectivity data
• MultiPy: Multiple hypothesis testing in Python [4]
  • Python software for multiple hypothesis testing
• Phase-TE [5]
  • MATLAB code to measure pairwise directed connectivity between phase time-series
• Resting-state CFC [6]
  • Python code for the analysis of resting-state cross-frequency coupling
• SEEG assistant [7, 8]
  • Set of tools for post-implant processing of SEEG data including 3DSlicer plugins.
• SEEG electrode reconstruction tool [8]
  • Tool for reconstructing the positions of SEEG electrode contacts from post-implant cone-beam CT scans.

References

[1] Lobier M, Palva JM, Palva S (2018): High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention. NeuroImage 165:222–237. DOI: 10.1016/j.neuroimage.2017.10.044

[2] Wang SH, Lobier M, Siebenhühner F, Puoliväli T, Palva S, Palva JM (2018): Hyperedge bundling: A practical solution to spurious interactions in MEG/EEG source connectivity analyses. NeuroImage 173:610–622. DOI: 10.1016/j.neuroimage.2018.01.056

[3] Wang SH, Lobier M, Siebenhühner F, Puoliväli T, Palva S, Palva JM (2018): Hyperedge bundling: Data, source code, and precautions to modeling-accuracy bias to synchrony estimates. Data in Brief 18:262–275. DOI: 10.1016/j.dib.2018.03.017

[4] Puoliväli T, Palva S, Palva JM (2018): Influence of multiple hypothesis testing on reproducibility in neuroimaging research. BioRxiv. DOI: 10.1101/488353

[5] Lobier M, Siebenhühner F, Palva S, Palva JM (2014): Phase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions. NeuroImage 85 Pt 2:853–872. DOI: 10.1016/j.neuroimage.2013.08.056

[6] Siebenhühner F, Wang SH, Arnulfo G, Nobili L, Palva JM, Palva S (2019): Resting-state cross-frequency coupling networks in human electrophysiological recordings. BioRxiv. DOI: 10.1101/547638

[7] Narizzano M, Arnulfo G, Ricci S, Toselli B, Canessa A, Tisdall M, Fato MM, Cardinale F (2017): SEEG Assistant: a 3DSlicer extension to support epilepsy surgery. BMC Bioinformatics 18(1):124. DOI: 10.1186/s12859-017-1545-8

[8] Arnulfo G, Narizzano M, Cardinale F, Fato MM, Palva JM. Automatic segmentation of deep intracerebral electrodes in computed tomography scans (2015). BMC Bioinformatics 16(1):99. DOI: 10.1186/s12859-015-0511-6

External sites

• criticaloscillations.org (group main page)
• twitter.com/palvalab (group Twitter account)