MEG Work


Methods Development

Methods development at the MEG Center takes a first-principles physics approach to solving problems faced by M/EEG researchers around the world. Our unique focus on the challenges arising from infant neuroimaging has led to pioneering solutions for noise and movement suppression that allow researchers to maximize scientific insight even when data is collected under difficult conditions.
  • Head movement compensation and interference suppression
  • eSSS
    • We have extended the SSS method to model and suppress artifacts that are not clearly of external origin. While tSSS is efficient against most of these artifacts, certain types of signal components, such as vibration artifacts may go undetected by tSSS. The extended SSS (eSSS), developed in collaboration with Aalto University, Finland, utilizes a linear algebra method to merge computational and experimental signal bases and thereby simultaneously achieves the benefits of SSS and signal space projection (SSP) without introducing any adverse effects on MEG data. More details can be found here: https://ieeexplore.ieee.org/document/9268467
  • OTP
    • We have developed the oversampled temporal projection (OTP) method that uses a cross-validation method to identify random sensor noise and artifacts, which are suppressed from the data in the time domain. This is useful for the detection of high frequency oscillations (HFO) and signals arising from deep structures of the brain, such as the brainstem. See here for more information: https://ieeexplore.ieee.org/document/7997929, https://doi.org/10.1016/j.jneumeth.2020.108700
  • TPS 
    • The temporal projection via singular value decomposition (TPS) is a method that projects artifact signals out in the time domain, just like tSSS, but it differs from tSSS in the sense that TPS does not require as many sensors or an accurate spatial model for brain signals. Therefore, TPS is better suited for EEG recording and perhaps some of the early OPM systems as well. 
  • First-principle physics approaches, e.g., Taulu, S., & Larson, E. (2020). Unified expression of the quasi-static electromagnetic field: Demonstration with MEG and EEG signals. IEEE Transactions on Biomedical Engineering68(3), 992-1004. https://ieeexplore.ieee.org/abstract/document/9140322

Open-Source Tools

The MEG Team contributes to the development of many free and open-source scientific software tools. The most prominent of these is MNE-Python, which has hundreds of contributors and is used by thousands of researchers worldwide. Two I-LABS MEG Team members are on the MNE-Python Steering Council and several others are current or past contributors.

Research Support

This is an area where we will describe research support.

Publications

Yeatman, J. D., McCloy, D. R., Caffarra, S., Clarke, M. D., Ender, S., Gijbels, L., ... & Taulu, S. (2024). Reading instruction causes changes in category-selective visual cortex. Brain Research Bulletin212, 110958.

Meltzoff, A. N., Ramírez, R. R., Saby, J. N., Larson, E., Taulu, S., & Marshall, P. J. (2018). Infant brain responses to felt and observed touch of hands and feet: an MEG study. Developmental science21(5), e12651. 

Taulu, S., & Larson, E. (2020). Unified expression of the quasi-static electromagnetic field: Demonstration with MEG and EEG signals. IEEE Transactions on Biomedical Engineering68(3), 992-1004. https://ieeexplore.ieee.org/abstract/document/9140322

Ferjan Ramírez, N., Ramírez, R.R., Clarke, M., Taulu, S. and Kuhl, P.K. (2017), Speech discrimination in 11-month-old bilingual and monolingual infants: a magnetoencephalography study. Dev Sci, 20: e12427. https://doi.org/10.1111/desc.12427

Bosseler AN, Taulu S, Pihko E, Mäkelä JP, Imada T, Ahonen A and Kuhl PK (2013) Theta brain rhythms index perceptual narrowing in infant speech perception. Front. Psychol4:690. doi: 10.3389/fpsyg.2013.00690 https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2013.00690/full