RT Journal Article
T1 High-power transient 12–30 Hz beta event features as early biomarkers of Alzheimer’s disease conversion: An MEG study
A1 Shpakivska-Bilan, Danylyna
A1 Susi, Gianluca
A1 Zhou, David W.
A1 Cabrera, Jesus
A1 Carvajal, Blanca P.
A1 Pereda, Ernesto
A1 López García, María Eugenia
A1 Bruña Fernández, Ricardo
A1 Maestu Unturbe, Fernando
A1 Jones, Stephanie R.
AB A typical pattern observed in M/EEG recordings of mild cognitive impairment (MCI) patients progressing to Alzheimer's disease (AD) is a continuous slowing of brain oscillatory activity. Definitions of oscillatory slowing are imprecise, as they average across time and frequency bands, masking the finer structure in the signal and potential reliable biomarkers of the disease progression. Recent studies show that high averaged band power can result from transient increases in power, termed "events" or "bursts." To better understand MEG oscillatory slowing in AD progression, we analyzed features of high-power oscillatory events and their relationship with cognitive decline. MEG resting-state oscillations were recorded in age-matched patients with MCI who later convert (CONV, N = 41) or do not convert (NOCONV, N = 44) to AD, in a period of 2.5 years. To distinguish future CONV from NOCONV, we characterized the rate, duration, frequency span, and power of transient high-power events in the alpha and beta band in two regions of interest in the "X" model of AD progression: anterior cingulate cortex (ACC) and precuneus (PC). Results revealed event-like patterns in resting-state power in both the alpha and beta bands, however, only beta-band features were predictive of conversion to AD, particularly in PC. Specifically, compared with NOCONV, CONV had a lower number of beta events, along with lower power events and a trend toward shorter duration events in PC (p<0.05). Beta event durations were also significantly shorter in ACC (p<0.01). Further, this reduced expression of beta events in CONV predicted lower values of mean relative beta power, increased probability of AD conversion, and poorer cognitive performance. Our work paves the way for reinterpreting M/EEG slowing and examining beta event features as a new biomarker along the AD continuum, and we discuss a potential link to theories of inhibitory control in neurodegeneration. These results may bring us closer to understanding the neural mechanisms of the disease that help guide new therapies.
PB Massachusetts Institute of Technology Press
YR 2025
FD 2025
LK https://hdl.handle.net/20.500.14352/134475
UL https://hdl.handle.net/20.500.14352/134475
LA eng
NO Danylyna Shpakivska-Bilan, Gianluca Susi, David W. Zhou, Jesus Cabrera, Blanca P. Carvajal, Ernesto Pereda, Maria Eugenia Lopez, Ricardo Bruña, Fernando Maestu, Stephanie R. Jones; High-power transient 12–30 Hz beta event features as early biomarkers of Alzheimer’s disease conversion: An MEG study. Imaging Neuroscience 2025; 3 IMAG.a.69. doi: https://doi.org/10.1162/IMAG.a.69
NO Department of Health & Human Services National Institutes of Health (Estados Unidos)
NO Collaborative Research in Computational Neuroscience (Estados Unidos)
NO Ministerio de Ciencia, Innovación y Universidades (España)
NO European Commission
NO Banco Santander
NO Universidad Complutense de Madrid
DS Docta Complutense
RD 2 may 2026