ArticleGeroScience2024
The effect of aperiodic components in distinguishing Alzheimer's disease from frontotemporal dementia.
Article in GeroScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of Aperiodic Neural Activity in Clinical Investigations.The European journal of neuroscience · 2025Pooled it
- Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis.Frontiers in aging neuroscience · 2025Pooled it
- The AHEPA EEG benchmark: setting the standard for machine learning in dementia diagnosis, a scoping review.Cognitive neurodynamics · 2026Article
- Alzheimer's Disease Detection Using Combined EEG Source Connectivity and Microstate Features.Brain sciences · 2026Article
- Abnormal periodic and aperiodic resting-state electroencephalographic markers in Lewy body and Alzheimer's diseases with cognitive decline.GeroScience · 2026Article
- Peripheral Mitochondrial Energetics are Associated with Cortical Neurophysiological Alterations in Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2026Article
- Multi-Entropy Feature Concatenation for Data-Efficient Cross-Subject Classification of Alzheimer's Disease and Frontotemporal Dementia from Single-Channel EEG.Entropy (Basel, Switzerland) · 2026Article
- Multi-dimensional EEG analysis reveals distinct neurophysiological patterns in Alzheimer's and frontotemporal dementia.Journal of neuroengineering and rehabilitation · 2026Article
- EEG-based classification of alzheimer's disease and frontotemporal dementia using functional connectivity.Scientific reports · 2026Article
- Early aperiodic EEG changes in preclinical and prodromal Alzheimer's disease.Alzheimer's research & therapy · 2026Article
- Epilepsy and EEG abnormalities in neurodegenerative dementias: toward a system epilepsy framework.Frontiers in aging neuroscience · 2026Review
- Buspirone regulates cortico-striatal gamma oscillations to ameliorate dyskinesia.Journal of Parkinson's disease · 2025Article
- Neurophysiological signatures of default mode network dysfunction and cognitive decline in Alzheimer's disease.Science advances · 2025Article
- Enhancing Alzheimer's Diagnosis with Machine Learning on EEG: A Spectral Feature-Based Comparative Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Evaluating EEG complexity and spectral signatures in Alzheimer's disease and frontotemporal dementia: evidence for rostrocaudal asymmetry.npj aging · 2025Article
- Alpha rhythm and Alzheimer's disease: Has Hans Berger's dream come true?Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- A Novel CNN-Based Framework for Alzheimer's Disease Detection Using EEG Spectrogram Representations.Journal of personalized medicine · 2025Article
- Altered periodic and aperiodic activities in patients with disorders of consciousness.Frontiers in neuroscience · 2025Article
- Aperiodic EEG signatures: unveiling the interplay between APOE ε4 and mild cognitive impairment subtypes.Frontiers in aging neuroscience · 2025Article
- Amyloid-β deposition predicts oscillatory slowing of magnetoencephalography signals and a reduction of functional connectivity over time in cognitively unimpaired adults.Brain communications · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Distinguishing between Alzheimer's disease (AD) and frontotemporal dementia (FTD) presents a clinical challenge. Inexpensive and accessible techniques such as electroencephalography (EEG) are increasingly being used to address this challenge. In particular, the potential relevance between aperiodic components of EEG activity and these disorders has gained interest as our understanding evolves. This study aims to determine the differences in aperiodic activity between AD and FTD and evaluate its potential for distinguishing between the two disorders. A total of 88 participants, including 36 patients with AD, 23 patients with FTD, and 29 healthy controls (CN) underwent cognitive assessment and scalp EEG acquisition. Neuronal power spectra were parameterized to decompose the EEG spectrum, enabling comparison of group differences in different components. A support vector machine was employed to assess the impact of aperiodic parameters on the differential diagnosis. Compared with the CN group, both the AD and FTD groups showed varying degrees of increased alpha power (both periodic and raw power) and theta alpha power ratio. At the channel level, theta power (both periodic and raw power) in the frontal regions was higher in the AD group compared to the FTD group, and aperiodic parameters (both exponents and offsets) in the frontal, temporal, central, and parietal regions were higher in the AD group than in the FTD group. Importantly, the inclusion of aperiodic parameters led to improved performance in distinguishing between the two disorders. These findings highlight the significance of aperiodic components in discriminating dementia-related diseases.
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