ArticleAlzheimer's research & therapy2026
Early aperiodic EEG changes in preclinical and prodromal Alzheimer's disease.
Article in Alzheimer's research & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Altered rhythmic and arrhythmic electroencephalographic activity during non-rapid eye movement sleep in amnestic mild cognitive impairment.Brain communications · 2026Article
- Oscillatory dynamics as the coordination layer of the organism: waves, Markov blankets, and the virtual space of cognition.Frontiers in neuroscience · 2026Article
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9 authors.
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Abstract
backgroundAlzheimer’s disease (AD) is characterized by a gradual buildup of beta amyloid (Aβ) and tau proteins, which disrupt the balance between neuronal excitation and inhibition (E-I), leading to dysfunction in neural network activity. In this study, we examined the aperiodic exponent as a putative marker of neuronal E-I balance in cognitively unimpaired amyloid negative and amyloid positive individuals, as well as in patients with prodromal AD, and assessed its association with tau pathology.
methodsHigh-density electroencephalography (EEG) data was recorded in response to visual gamma stimulation, and 100-minute tau PET scans were obtained from 64 individuals, 33 across the AD continuum (16 individuals in the biomarker-proven prodromal AD stage and 17 cognitively unimpaired amyloid positive) and 31 cognitively unimpaired amyloid negative individuals.
resultsOur results show a significant between-group difference in the aperiodic exponent and reveal distinct patterns of E-I balance across different brain regions. Furthermore, we demonstrate that the aperiodic exponent can distinguish prodromal AD individuals from cognitively unimpaired peers and is negatively associated with tau PET load in brain regions typically affected in the early stages of AD.
conclusionsOur findings suggest that the E-I imbalance may already emerge during the asymptomatic and prodromal AD stages and can vary across brain regions. While further validation is needed, our results support the potential of EEG-based methods as a noninvasive tool for capturing early neural changes due to AD.
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