The neuro-current response function visualization using the MNE library (EEG/MEG)
Creators: name: Borodin, Nikita
name: Kharlamov, Alexander
name: Verkhlyutov, Vitaly
Publisher: name: Zenodo
Year: 2024

description: The TRF is a widely used method for analyzing EEG and MEG in the study of overt and covert speech (Di Liberto et al., 2015; Cross et al., 2016; Brodbeck et al., 2018; Bhuvanakantham et al., 2024). The localization and properties of TRF sources have been poorly studied. To solve this problem, a number of authors have proposed a method for assessing TRF combined with localization (Das et al., 2018, 2020), where the Champ-Lasso algorithm is implemented which iteratively selects current sources in the cerebral cortex that reproduce the original MEG signal and TRF in dynamics when solving the direct problem.

We tried to run the code that the authors presented in their latest work on GIThub (https://github.com/proloyd/neuro-currentRF). We didn’t succeed right away, but then, following the instructions of the first author, we ran the main part of the code, which calculated the behavior of fixed dipoles orthogonal to the surface of the cortex.

However, we were interested in the opportunity to study freely rotating dipoles, which in our opinion may indicate moving fronts of traveling waves in the sulci of the brain (Verkhlyutov et al., 2021). And here the first author helped us too.

Unfortunately, we were unable to visualize the results due to problems with the eelbrain library (Brodbeck et al., 2023). Then, we successfully used the tools and templates of the MNE library (Gramfort et al., 2013, 2014), which allows us to visualize the results of calculations of both fixed and free dipoles.

Here we present our version of the MNE-python code and initialization environment for this purpose.

Acknowledgments

This study was supported by the Russian Science Foundation - Grant no. 23-78-00011.

The authors are grateful to Proloy Das for help in running the code.

References

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