Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxymarker of excitation/inhibition imbalance in Alzheimer’s disease
Metadatos
Mostrar el registro completo del ítemAutor
Martínez-Cañada, Pablo; Pérez Valero, Eduardo; Minguillón Campos, Jesús; Pelayo Valle, Francisco José; López Gordo, Miguel Ángel; Morillas Gutiérrez, Christian AgustínEditorial
Wiley-VCH GmbH
Materia
1/f slope Alzheimer’s disease EEG
Fecha
2023-09-01Referencia bibliográfica
Martínez-Cañada P, Perez-Valero E, Minguillon J, Pelayo F, López-Gordo MA,Morillas C. Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxymarker of excitation/inhibition imbalance in Alzheimer’s disease. Alzheimer’s Dement. 2023;15:e12477. https://doi.org/10.1002/dad2.12477
Patrocinador
Ministerio de Ciencia e Innovación, Gobierno de España/Agencia Estatal de Investigación/European Regional Development Fund, Grant/Award Numbers: PID2022-137461NB-C31, PID2022-139055OA-I00, PID2021-128529OA-I00; Consejería de Universidad, Investigación e Innovación, Junta de Andalucía, Grant/Award Number: PROYEXCEL_00084; Universidad de Granada, Grant/Award Numbers: PPJIA2022.33, PP2022.PP.33, PP2021.PP-28Resumen
INTRODUCTION: Accumulation and interaction of amyloid-beta (Aβ) and tau proteins
during progression of Alzheimer’s disease (AD) are shown to tilt neuronal circuits away
from balanced excitation/inhibition (E/I). Current available techniques for noninvasive
interrogation of E/I in the intact human brain, for example, magnetic resonance
spectroscopy (MRS), are highly restrictive (i.e., limited spatial extent), have low temporal
and spatial resolution and suffer from the limited ability to distinguish accurately
between different neurotransmitters complicating its interpretation. As such, these
methods alone offer an incomplete explanation of E/I. Recently, the aperiodic component
of neural power spectrum, often referred to in the literature as the ‘1/f slope’, has
been described as a promising and scalable biomarker that can track disruptions in E/I
potentially underlying a spectrum of clinical conditions, such as autism, schizophrenia,
or epilepsy, as well as developmental E/I changes as seen in aging.
METHODS: Using 1/f slopes from resting-state spectral data and computational
modeling, we developed a newmethod for inferring E/I alterations in AD.
RESULTS: We tested our method on recent freely and publicly available electroencephalography
(EEG) and magnetoencephalography (MEG) datasets of patients with
AD or prodromal disease and demonstrated the method’s potential for uncovering
regional patterns of abnormal excitatory and inhibitory parameters.
DISCUSSION: Our results provide a general framework for investigating circuit-level
disorders in AD and developing therapeutic interventions that aim to restore the
balance between excitation and inhibition.