Connectionists: Release of laMEG: a toolbox for laminar MEG

[James Bonaiuto]

Dear colleagues,
Apologies for the cross-posting. I'm extremely pleased to announce the
first release of laMEG: a toolbox for performing non-invasive inference of
laminar-specific activity with MEG. My collaborators and I have been
working on methods for laminar MEG for several years now, and we've finally
put them all together in an easy-to-install toolbox. It includes test data,
and tutorial jupyter notebooks to reproduce the simulations and analyses in
all of our key papers:

- Laminar inference using model comparison with either free energy or cross
validation error, as well as power-based ROI analysis

Bonaiuto, James J., Holly E. Rossiter, Sofie S. Meyer, Natalie Adams, Simon
Little, Martina F. Callaghan, Fred Dick, Sven Bestmann, and Gareth R.
Barnes. "Non-invasive laminar inference with MEG: Comparison of methods and
source inversion algorithms." *Neuroimage* 167 (2018): 372-383.
Bonaiuto, James J., Sofie S. Meyer, Simon Little, Holly Rossiter, Martina
F. Callaghan, Frederic Dick, Gareth R. Barnes, and Sven Bestmann.
"Lamina-specific cortical dynamics in human visual and sensorimotor
cortices." *Elife* 7 (2018): e33977.

- Free energy model comparison in a sliding time window with priors

Bonaiuto, James J., Simon Little, Samuel A. Neymotin, Stephanie R. Jones,
Gareth R. Barnes, and Sven Bestmann. "Laminar dynamics of high amplitude
beta bursts in human motor cortex." *NeuroImage* 242 (2021): 118479.

- Surface post-processing, following up from FreeSurfer recon-all, to
downsample multiple surfaces and compute link vectors to constrain dipole
orientations

Bonaiuto, James J., Fardin Afdideh, Maxime Ferez, Konrad Wagstyl, Jérémie
Mattout, Mathilde Bonnefond, Gareth R. Barnes, and Sven Bestmann.
"Estimates of cortical column orientation improve MEG source inversion."
*Neuroimage* 216 (2020): 116862.

laMEG includes the ability to run any of these analyses on an
arbitrary number of layer surfaces (not just pial versus white matter),
interactive 3d surface visualization, an experimental "CSD" laminar
analysis, and SPM compiled as a python library - no matlab license required.

Github: https://github.com/danclab/laMEG
Documentation: https://danclab.github.io/laMEG/
PyPI: https://pypi.org/project/lameg/

Best wishes,
Jimmy Bonaiuto


---------------------
James Bonaiuto
Group leader | Institut des Sciences Cognitives | CNRS / Université Claude
Bernard Lyon
DANC lab <http://danclab.com/> | @danc_labo <https://twitter.com/danc_labo>
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