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Detectability of cerebellar activity with magnetoencephalography and electroencephalography

Author(s)
Samuelsson, JG; Sundaram, P; Khan, S; Sereno, MI; Hämäläinen, MS
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Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
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Abstract
© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. Electrophysiological signals from the cerebellum have traditionally been viewed as inaccessible to magnetoencephalography (MEG) and electroencephalography (EEG). Here, we challenge this position by investigating the ability of MEG and EEG to detect cerebellar activity using a model that employs a high-resolution tessellation of the cerebellar cortex. The tessellation was constructed from repetitive high-field (9.4T) structural magnetic resonance imaging (MRI) of an ex vivo human cerebellum. A boundary-element forward model was then used to simulate the M/EEG signals resulting from neural activity in the cerebellar cortex. Despite significant signal cancelation due to the highly convoluted cerebellar cortex, we found that the cerebellar signal was on average only 30–60% weaker than the cortical signal. We also made detailed M/EEG sensitivity maps and found that MEG and EEG have highly complementary sensitivity distributions over the cerebellar cortex. Based on previous fMRI studies combined with our M/EEG sensitivity maps, we discuss experimental paradigms that are likely to offer high M/EEG sensitivity to cerebellar activity. Taken together, these results show that cerebellar activity should be clearly detectable by current M/EEG systems with an appropriate experimental setup.
Date issued
2020-06-15
URI
https://hdl.handle.net/1721.1/141258
Department
Harvard University--MIT Division of Health Sciences and Technology
Journal
Human Brain Mapping
Publisher
Wiley
Citation
Samuelsson, JG, Sundaram, P, Khan, S, Sereno, MI and Hämäläinen, MS. 2020. "Detectability of cerebellar activity with magnetoencephalography and electroencephalography." Human Brain Mapping, 41 (9).
Version: Final published version

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