TY - JOUR
T1 - Novel approaches to EEG and MEG in motor neurone disease
T2 - IFCN Handbook Chapter
AU - Dukic, Stefan
AU - Govaarts, Rosanne
AU - Hillebrand, Arjan
AU - de Visser, Marianne
AU - Seeck, Margitta
AU - McMackin, Roisin
N1 - Publisher Copyright:
© 2025
PY - 2025
Y1 - 2025
N2 - Motor neurone diseases (MNDs) are increasingly being acknowledged as network disorders, with cortical dysfunction and degeneration extending beyond the motor cortex. Measures of this broader cortical pathophysiology are providing promising candidates in the search for diagnostic and prognostic biomarkers of the MNDs. Electroencephalography (EEG) and magnetoencephalography (MEG) offer a direct view of neural network activity by detecting changes in electromagnetic fields of the brain. Measurements based on EEG/MEG have often been overlooked in the search for MND biomarkers, largely due to their limited spatial resolution and the perceived challenges associated with noise in these signals. However, with recent developments in sensor technology and source reconstruction algorithms, alongside substantial improvement in pipelines that address noise, EEG/MEG-based measures can now be readily employed for spatiotemporally-precise, economical and non-invasive characterisation of cortical network pathophysiology in MNDs. Here, we provide an overview of how EEG/MEG signals have been employed to quantify neural network function in MND. We outline the advantages and limitations of these measurements, discuss the most clinically promising EEG/MEG studies of MNDs to date, and highlight future directions warranted to harness the full potential of these technologies for understanding and assessing MNDs.
AB - Motor neurone diseases (MNDs) are increasingly being acknowledged as network disorders, with cortical dysfunction and degeneration extending beyond the motor cortex. Measures of this broader cortical pathophysiology are providing promising candidates in the search for diagnostic and prognostic biomarkers of the MNDs. Electroencephalography (EEG) and magnetoencephalography (MEG) offer a direct view of neural network activity by detecting changes in electromagnetic fields of the brain. Measurements based on EEG/MEG have often been overlooked in the search for MND biomarkers, largely due to their limited spatial resolution and the perceived challenges associated with noise in these signals. However, with recent developments in sensor technology and source reconstruction algorithms, alongside substantial improvement in pipelines that address noise, EEG/MEG-based measures can now be readily employed for spatiotemporally-precise, economical and non-invasive characterisation of cortical network pathophysiology in MNDs. Here, we provide an overview of how EEG/MEG signals have been employed to quantify neural network function in MND. We outline the advantages and limitations of these measurements, discuss the most clinically promising EEG/MEG studies of MNDs to date, and highlight future directions warranted to harness the full potential of these technologies for understanding and assessing MNDs.
KW - Amyotrophic lateral sclerosis
KW - Biomarkers
KW - Electroencephalography
KW - Magnetoencephalography
KW - Motor neurone disease
KW - Outcome measures
UR - https://www.scopus.com/pages/publications/105011086477
U2 - 10.1016/j.cnp.2025.07.001
DO - 10.1016/j.cnp.2025.07.001
M3 - Review article
AN - SCOPUS:105011086477
SN - 2467-981X
VL - 10
SP - 301
EP - 315
JO - Clinical Neurophysiology Practice
JF - Clinical Neurophysiology Practice
ER -